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Background: Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. Methods: We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Results: Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. Conclusions: The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

GE Healthcare Bio-Sciences AB i Umeå tillverkar ett flertal system, ett av systemen är vätskekromatografen. Vätskekromatografen är en kemisk separationsmetod som använder sig av en UV-monitor, UV-detektor och en UV-cell för att mäta absorptionen av en lösning och framta koncentrationen av det eftersökta ämnet. På anläggningen i Umeå tillverkas två typer av UV-celler; laborationceller och industriceller. För labbcellerna har GE utvecklat en teststation som testar och utvärderar UV och flödesegenskaper samt lagrar data i GE:s egen produktionsdatabas, Prodas. Den befintliga stationen för industriceller är äldre och omodern, en utveckling behövs för att upprätthålla högre kvalité.

Syftet med detta projekt är att uppdatera teststationen för industriella UV-celler till samma nivå som stationen för laborationsceller. Det primära målet är att konstruera och designa en teststation för industriella UV-celler som kan mäta tryck, flöde och absorption. Det sekundära målet är att upptäcka och om möjligt verkställa lösningar som kommer effektivisera och automatisera mätningarna.

En prototyp av en teststation för industriella UV-celler baserat på den för laborationceller har framtagits, och består av en adapterlösning som används för att sammanlänka ljusbanan från monitorn genom flödescellen till detektorn. Prototypen kan enbart utföra absorption och läckagemätningar. Automatisering och effektivisering har utförts i form av scripts som används för att genomföra absorptions och läckagemätning. Teststationen kräver fortsatt vidareutveckling innan den kan används i produktionslinjen.

BACKGROUND AND PURPOSE: Brain size is commonly described in relation to ICV, whereby accurate assessment of this quantity is fundamental. Recently, an optimized MR sequence (QRAPMASTER) was developed for simultaneous quantification of T1, T2, and proton density. ICV can be measured automatically within minutes from QRAPMASTER outputs and a dedicated software, SyMRI. Automatic estimations of ICV were evaluated against the manual segmentation.

MATERIALS AND METHODS: In 19 healthy subjects, manual segmentation of ICV was performed by 2 neuroradiologists (Obs1, Obs2) by using QBrain software and conventional T2-weighted images. The automatic segmentation from the QRAPMASTER output was performed by using SyMRI. Manual corrections of the automatic segmentation were performed (corrected-automatic) by Obs1 and Obs2, who were blinded from each other. Finally, the repeatability of the automatic method was evaluated in 6 additional healthy subjects, each having 6 repeated QRAPMASTER scans. The time required to measure ICV was recorded.

RESULTS: No significant difference was found between reference and automatic (and corrected-automatic) ICV (P > .25). The mean difference between the reference and automatic measurement was -4.84 ± 19.57 mL (or 0.31 ± 1.35%). Mean differences between the reference and the corrected-automatic measurements were -0.47 ± 17.95 mL (-0.01 ± 1.24%) and -1.26 ± 17.68 mL (-0.06 ± 1.22%) for Obs1 and Obs2, respectively. The repeatability errors of the automatic and the corrected-automatic method were <1%. The automatic method required 1 minute 11 seconds (SD = 12 seconds) of processing. Adding manual corrections required another 1 minute 32 seconds (SD = 38 seconds).

CONCLUSIONS: Automatic and corrected-automatic quantification of ICV showed good agreement with the reference method. SyMRI software provided a fast and reproducible measure of ICV.

In this paper, we present an approach for communication through human body tissue in the R-band frequency range. This study examines the ranges of microwave frequencies suitable for intra-body communication. The human body tissues are characterized with respect to their transmission properties using simulation modeling and phantom measurements. The variations in signal coupling with respect to different tissue thicknesses are studied. The simulation and phantom measurement results show that electromagnetic communication in the fat layer is viable with attenuation of approximately 2 dB per 20 mm.

In this paper, we investigate the use of fat tissue as a communication channel between in-body, implanted devices at R-band frequencies (1.7–2.6 GHz). The proposed fat channel is based on an anatomical model of the human body. We propose a novel probe that is optimized to efficiently radiate the R-band frequencies into the fat tissue. We use our probe to evaluate the path loss of the fat channel by studying the channel transmission coefficient over the R-band frequencies. We conduct extensive simulation studies and validate our results by experimentation on phantom and ex-vivo porcine tissue, with good agreement between simulations and experiments. We demonstrate a performance comparison between the fat channel and similar waveguide structures. Our characterization of the fat channel reveals propagation path loss of ∼0.7 dB and ∼1.9 dB per cm for phantom and ex-vivo porcine tissue, respectively. These results demonstrate that fat tissue can be used as a communication channel for high data rate intra-body networks.

Near infrared spectroscopy (NIR) and skin impedance (IMP) spectroscopy are two methods suggested for diagnoses of diseases inducing adverse effects in skin. The reproducibility of these methods and their potential value in non-invasive diagnostics were investigated. Measurements were performed in vivo on healthy skin at five anatomic body sites on eight young women. partial least squares discriminant analysis showed that both methods were useful for classification of the skin characteristics at the sites. Inter-individually the NIR model gave 100% correct classification while the IMP model provided 92%. Intra-individually the NIR model gave 88% correct classification whereas the IMP model did not provide any useful classification. The correct classification was increased to 93% when both datasets were combined, which demonstrates the value of adding information. Partial least squares discriminant analysis gave 72% correct predictions of skin sites while the combined model slightly improved to 73%.

Background/purpose: An early diagnosis of cutaneous malignant melanoma is of high importance for good prognosis. An objective, non-invasive instrument could improve the diagnostic accuracy of melanoma and decrease unnecessary biopsies. The aim of this study was to investigate the use of Near infrared and skin impedance spectroscopy in combination as a tool to distinguish between malignant and benign skin tumours.

Methods: Near infrared and skin impedance spectra were collected in vivo on 50 naevi or suspect melanomas prior to excision. Received data was analysed with multivariate techniques and the results were compared to histopathology analyses of the tumours. A total of 12 cutaneous malignant melanomas, 19 dysplastic naevi and 19 benign naevi were included in the study.

Results: The observed sensitivity and specificity of the proposed method were 83% and 95%, respectively, for malignant melanoma.

Conclusions: The results indicate that the combination of near infrared and skin impedance spectroscopy is a promising tool for non-invasive diagnosis of suspect cutaneous malignant melanomas. 

BACKGROUND: Venous blood sampling is a common procedure in health care. It is strictly regulated by national and international guidelines. Deviations from guidelines due to human mistakes can cause patient harm. Validated questionnaires for health care personnel can be used to assess preventable "near misses"--i.e. potential errors and nonconformities during venous blood sampling practices that could transform into adverse events. However, no validated questionnaire that assesses nonconformities in venous blood sampling has previously been presented. The aim was to test a recently developed questionnaire in self reported venous blood sampling practices for validity and reliability.

FINDINGS: We developed a questionnaire to assess deviations from best practices during venous blood sampling. The questionnaire contained questions about patient identification, test request management, test tube labeling, test tube handling, information search procedures and frequencies of error reporting. For content validity, the questionnaire was confirmed by experts on questionnaires and venous blood sampling. For reliability, test-retest statistics were used on the questionnaire answered twice. The final venous blood sampling questionnaire included 19 questions out of which 9 had in total 34 underlying items. It was found to have content validity. The test-retest analysis demonstrated that the items were generally stable. In total, 82% of the items fulfilled the reliability acceptance criteria.

CONCLUSIONS: The questionnaire could be used for assessment of "near miss" practices that could jeopardize patient safety and gives several benefits instead of assessing rare adverse events only. The higher frequencies of "near miss" practices allows for quantitative analysis of the effect of corrective interventions and to benchmark preanalytical quality not only at the laboratory/hospital level but also at the health care unit/hospital ward.

The tactile resonance method (TRM) and Raman spectroscopy (RS) are promising for tissue characterization in vivo. Our goal is to combine these techniques into one instrument, to use TRM for swift scanning, and RS for increasing the diagnostic power. The aim of this study was to determine the classification accuracy, using support vector machines, for measurements on porcine tissue and also produce preliminary data on human prostate tissue. This was done by developing a new experimental set-up combining micro-scale TRMscanning haptic microscopy (SHM)for assessing stiffness on a micro-scale, with fibre optic RS measurements for assessing biochemical content. We compared the accuracy using SHM alone versus SHM combined with RS, for different degrees of tissue homogeneity. The cross-validation classification accuracy for healthy porcine tissue types using SHM alone was 6581%, and when RS was added it increased to 8187%. The accuracy for healthy and cancerous human tissue was 6770% when only SHM was used, and increased to 7277% for the combined measurements. This shows that the potential for swift and accurate classification of healthy and cancerous prostate tissue is high. This is promising for developing a tool for probing the surgical margins during prostate cancer surgery. 

Tissue characterization is fundamental for identification of pathological conditions. Raman spectroscopy (RS) and tactile resonance measurement (TRM) are two promising techniques that measure biochemical content and stiffness, respectively. They have potential to complement the golden standard-–histological analysis. By combining RS and TRM, complementary information about tissue content can be obtained and specific drawbacks can be avoided. The aim of this study was to develop a multivariate approach to compare RS and TRM information. The approach was evaluated on measurements at the same points on porcine abdominal tissue. The measurement points were divided into five groups by multivariate analysis of the RS data. A regression analysis was performed and receiver operating characteristic (ROC) curves were used to compare the RS and TRM data. TRM identified one group efficiently (area under ROC curve 0.99). The RS data showed that the proportion of saturated fat was high in this group. The regression analysis showed that stiffness was mainly determined by the amount of fat and its composition. We concluded that RS provided additional, important information for tissue identification that was not provided by TRM alone. The results are promising for development of a method combining RS and TRM for intraoperative tissue characterization.

Prostate cancer is the most common form of cancer and is the third leading cause of cancer-related death in European men. There is a need for new methods that can accurately localize and diagnose prostate cancer. In this study a new approach is presented: a combination of resonance sensor technology and Raman spectroscopy. Both methods have shown promising results for prostate cancer detection in vitro. The aim of this study was to evaluate the combined information from measurements with a Raman fiberoptic probe and a resonance sensor system. Pork belly tissue was used as a model system. A three-dimensional translation table was equipped with an in-house developed software, allowing measurements to be performed at the same point using two separate instruments. The Raman data was analyzed using principal component analysis and hierarchical clustering analysis. The spectra were divided into 5 distinct groups. The mean stiffness of each group was calculated from the resonance sensor measurements. One of the groups differed significantly (p < 0.05) from the others. A regression analysis, with the stiffness parameter as response variable and the principal component scores of the Raman data as the predictor variables, explained 67% of the total variability. The use of a smaller resonance sensor tip would probably increase the degree of correlation. In conclusion, Raman spectroscopy provides additional discriminatory power to the resonance sensor.

The bacterial cell wall is critical for the determination of cell shape during growth and division, and maintains the mechanical integrity of cells in the face of turgor pressures several atmospheres in magnitude. Across the diverse shapes and sizes of the bacterial kingdom, the cell wall is composed of peptidoglycan, a macromolecular network of sugar strands crosslinked by short peptides. Peptidoglycan's central importance to bacterial physiology underlies its use as an antibiotic target and has motivated genetic, structural, and cell biological studies of how it is robustly assembled during growth and division. Nonetheless, extensive investigations are still required to fully characterize the key enzymatic activities in peptidoglycan synthesis and the chemical composition of bacterial cell walls. High Performance Liquid Chromatography (HPLC) is a powerful analytical method for quantifying differences in the chemical composition of the walls of bacteria grown under a variety of environmental and genetic conditions, but its throughput is often limited. Here, we present a straightforward procedure for the isolation and preparation of bacterial cell walls for biological analyses of peptidoglycan via HPLC and Ultra Performance Liquid Chromatography (UPLC), an extension of HPLC that utilizes pumps to deliver ultra-high pressures of up to 15,000 psi, compared with 6,000 psi for HPLC. In combination with the preparation of bacterial cell walls presented here, the low-volume sample injectors, detectors with high sampling rates, smaller sample volumes, and shorter run times of UPLC will enable high resolution and throughput for novel discoveries of peptidoglycan composition and fundamental bacterial cell biology in most biological laboratories with access to an ultracentrifuge and UPLC.

Glaucoma is an eye disease that, in its most common form, is characterised by high intra-ocular pressure (IOP), reduced visual field and optic nerve damage. For diagnostic purposes and for follow-up after treatment, it is important to have simple and reliable methods for measuring IOP. Recently, an applanation resonator sensor (ARS) for measuring IOP was introduced and evaluated using an in vitro pig-eye model. In the present study, the first clinical evaluation of the same probe has been carried out, with experiments in vivo on human eyes. There was a low but significant correlation between IOP(ARS) and the IOP measured with a Goldmann applanation tonometer (r = 0.40, p = 0.001, n = 72). However, off-centre positioning of the sensor against the cornea caused a non-negligible source of error. The sensor probe was redesigned to have a spherical, instead of flat, contact surface against the eye and was evaluated in the in vitro model. The new probe showed reduced sensitivity to off-centre positioning, with a decrease in relative deviation from 89% to 11% (1 mm radius). For normalised data, linear regression between IOP(ARS) and direct IOP measurement in the vitreous chamber showed a correlation of r = 0.97 (p < 0.001, n = 108) and a standard deviation for the residuals of SD < or = 2.18 mm Hg (n = 108). It was concluded that a spherical contact surface should be preferred and that further development towards a clinical instrument should focus on probe design and signal analysis.

Portable motion systems based on inertial motion sensors are promising methods, with the advantage compared to optoelectronic cameras of not being confined to a laboratory setting. A challenge is to develop relevant outcome measures for clinical use. The aim of this study was to characterize elbow and shoulder motion during functional tasks, using portable motion sensors and a modified Exposure Variation Analysis (EVA) and evaluate system accuracy with optoelectronic cameras. Ten healthy volunteers and one participant with sequel after stroke performed standardised functional arm tasks. Motion was registered simultaneously with a custom developed motion sensor system, including gyroscopes and accelerometers, and an optoelectronic camera system. The EVA was applied on elbow and shoulder joints, and angular and angular velocity EVA plots was calculated. The EVA showed characteristic patterns for each arm task in the healthy controls and a distinct difference between the affected and unaffected arm in the participant with sequel after stroke. The accuracy of the portable system was high with a systematic error ranging between -1.2 degrees and 2.0 degrees. The error was direction specific due to a drift component along the gravity vector. Portable motion sensor systems have high potential as clinical tools for evaluation of arm function. EVA effectively illustrates joint angle and joint angle velocity patterns that may capture deficiencies in arm function and movement quality. Next step will be to manage system drift by including magnetometers, to further develop clinically relevant outcome variables and apply this for relevant patient groups.

Detektion av spårgaser i utandningsluften har stor potential för icke-invasiv medicinsk diagnostik och fysiologisk övervakning. Realtid andningsgasanalys av enskilda andningscykler underlättar datatolkningen och kan förbättra det diagnostiska värdet av andningstester, eftersom utandningsprofiler bär spatiotemporal information om biomarkörens ursprung och gasutbyte i andningssystemet. Denna avhandling presenterar och granskar en ny analysmetod, där utandningsprofiler simuleras med hjälp av en matematisk modell för gasutbytet, och anpassas till uppmätta expirogram för att bestämma luftvägs- och alveolära bidrag och diffusionsförmågor. Metoden demonstreras på utandad kolmonoxid (eCO), en potentiell biomarkör för oxidativ stress och respiratoriska sjukdomar. Avhandlingen omfattar huvudsakligen (1) konstruktionen av en kompakt optisk sensor baserat på mid-infraröd diodlaserabsorptionsspektroskopi (TDLAS) vid 4.7 μm för selektiv och precis realtidsmätning av CO i utandnings- och omgivningsluften (detektionsgräns 9 ± 5 ppb vid 0.1 s), (2) design av ett avancerat system för online provtagning, (3) adaption av en matematisk lungmodell med axiell diffusion (TMAD) för simulation av CO gasutbytet, och (4) tillämpningen av utökad eCO analys i kliniska studier för att fastställa baslinjen för eCO parametrarna i friska icke-rökare, och för att studera effekten av exponering för CO och trärök. Det visas att modellen väl beskriver gasutbytet under systemiskt CO utsläpp för olika andningsmönster, och att det inte finns någon skillnad mellan eCO parametrarna från utandning via mun och näsa. Utandningsprofilerna och eCO parametrarna ändras beroende på utandningsflödet, men för ett visst andningsmönstret ligger parametrarna i ett smalt område. Koncentrationen av CO i luftvägarna ligger nära och korrelerar med CO i omgivningsluften, vilket indikerar att CO produktionen i luftvägarna är försumbart hos den friska befolkningen. Den alveolär diffusionsförmågan är oberoende av endogen CO, även efter exponering för förhöjd exogen CO, och kan möjligtvis användas för att diagnosticera en nedsatt diffusionsförmåga. Jämfört med exponering för CO observeras ingen tydlig ytterligare effekt av exponering för trärökpartiklar. Att åtskilja endogena och exogena eCO källor förbli en utmaning.

The influence of breath sampling on exhaled carbon monoxide (eCO) and related pulmonary gas exchange parameters is investigated in a study with 32 healthy non-smokers. Mid-infrared tunable diode laser absorption spectroscopy and well-controlled online sampling is used to precisely measure mouth- and nose-exhaled CO expirograms at exhalation flow rates (EFRs) of 250, 120 and 60 ml s⁻¹, and for 10 s of breath-holding followed by exhalation at 120 ml s⁻¹. A trumpet model with axial diffusion is employed to fit simulated exhalation profiles to the experimental expirograms, which provides equilibrium airway and alveolar CO concentrations and the average lung diffusing capacity in addition to end-tidal concentrations. For all breathing maneuvers, excellent agreement is found between mouth- and nose-exhaled end-tidal CO (ETCO), and the individual values for ETCO and alveolar diffusing capacity are consistent across maneuvers. The eCO parameters clearly show a dependence on EFR, where the lung diffusing capacity increases with EFR, while ETCO slightly decreases. End-tidal CO is largely independent of ambient air CO and alveolar diffusing capacity. While airway CO is slightly higher than, and correlates strongly with, ambient air CO, and there is a weak correlation with ETCO, the results point to negligible endogenous airway CO production in healthy subjects. An EFR of around 120 ml s⁻¹ can be recommended for clinical eCO measurements. The employed method provides means to measure variations in endogenous CO, which can improve the interpretation of exhaled CO concentrations and the diagnostic value of eCO tests in clinical studies.

Clinical trial registration number: 2017/306-31

We present a compact sensor for carbon monoxide (CO) in air and exhaled breath based on a room temperature interband cascade laser (ICL) operating at 4.69 µm, a low-volume circular multipass cell and wavelength modulation absorption spectroscopy. A fringe-limited (1σ) sensitivity of 6.5 × 10⁻⁸ cm⁻¹Hz^-1/2 and a detection limit of 9 ± 5 ppbv at 0.07 s acquisition time are achieved, which constitutes a 25-fold improvement compared to direct absorption spectroscopy. Integration over 10 s increases the precision to 0.6 ppbv. The setup also allows measuring the stable isotope ¹³CO in breath. We demonstrate quantification of indoor air CO and real-time detection of CO expirograms from healthy non-smokers and a healthy smoker before and after smoking. Isotope ratio analysis indicates depletion of ¹³CO in breath compared to natural abundance.

Real-time breath gas analysis is a promising, non-invasive tool in medical diagnostics, and well-suited to investigate the physiology of carbon monoxide (CO), a potential biomarker for oxidative stress and respiratory diseases. A sensor for precise, breath-cycle resolved, simultaneous detection of exhaled CO (eCO) and carbon dioxide (eCO₂) was developed based on a continuous wave, external-cavity quantum cascade laser (EC-QCL), a low-volume multi-pass cell and wavelength modulation spectroscopy. The system achieves a noise-equivalent (1σ) sensitivity of 8.5 × 10⁻⁸ cm⁻¹ Hz^−1/2 and (2σ) detection limits of 9 ± 2 ppbv and 650 ± 7 ppmv at 0.14 s spectrum acquisition time for CO and CO₂, respectively. Integration over 15 s yields a precision of 0.6 ppbv for CO. The fact that the eCO₂ expirograms measured by capnography and laser spectroscopy have essentially identical shape confirms true real-time detection. It is found that the individual eCO exhalation profiles from healthy non-smokers have a slightly different shape than the eCO₂ profiles and exhibit a clear dependence on exhalation flow rate and breath-holding time. Detection of indoor air CO and broadband breath profiling across the 93 cm⁻¹ mode-hop-free tuning range of the EC-QCL are also demonstrated.

Video conferencing is a very effective tool to use for e-learning. Most of the available video conferencing systems suffer a main drawback represented by the lack of eye contact between participants. In this paper we present a new scheme for building eye contact in e-learning sessions. The scheme assumes a video conferencing session with “one teacher many students” arrangement. In our system, eye contact is achieved without the need for any gaze estimation technique. Instead, we “generate the gaze” by allowing the user communicate his visual attention to the system through head-eye coordination. To enable real time and precise headeye coordination, a head motion tracking technique is required. Unlike traditional head tracking systems, our procedure suggests mounting the camera on the user’s head rather than in front of it. This configuration achieves much better resolution and thus leads to better tracking results. Promising results obtained from both demo and real time experiments demonstrate the effectiveness and efficiency of the proposed scheme. Although this paper concentrates on elearning, the proposed concept can be easily extended to the world of interaction with social robotics, in which introducing eye contact between humans and robots would be of great advantage.

Detection and analysis of volatile compounds in exhaled breath represents an attractive tool for monitoring the metabolic status of a patient and disease diagnosis, since it is non-invasive and fast. Numerous studies have already demonstrated the benefit of breath analysis in clinical settings/applications and encouraged multidisciplinary research to reveal new insights regarding the origins, pathways, and pathophysiological roles of breath components. Many breath analysis methods are currently available to help explore these directions, ranging from mass spectrometry to laser-based spectroscopy and sensor arrays. This review presents an update of the current status of optical methods, using near and mid-infrared sources, for clinical breath gas analysis over the last decade and describes recent technological developments and their applications. The review includes: tunable diode laser absorption spectroscopy, cavity ring-down spectroscopy, integrated cavity output spectroscopy, cavity-enhanced absorption spectroscopy, photoacoustic spectroscopy, quartz-enhanced photoacoustic spectroscopy, and optical frequency comb spectroscopy. A SWOT analysis (strengths, weaknesses, opportunities, and threats) is presented that describes the laser-based techniques within the clinical framework of breath research and their appealing features for clinical use.

Background: Abnormalities in homocysteine metabolism have been suggested as risk factors for stroke. The aim of this prospective study was to examine whether total plasma homocysteine concentration (tHcy) and its main genetic determinant, methylene tetrahydrofolate reductase (MTHFR) polymorphisms, were associated with first ischemic or hemorrhagic stroke.

Methods: This was a nested case-referent study of 321 ischemic and 60 hemorrhagic stroke cases, defined by WHO MONICA criteria and each matched with two event-free referents for sex, age, cohort, recruitment date and geographical area. All subjects were from the population-based Northern Sweden Health and Disease Study cohorts. Odds ratios were determined by conditional logistic regression.

Results: The mean follow-up time was 4.2 years. Both tHcy and MTHFR were independent predictors of hemorrhagic stroke in multivariate models including body mass index, hypertension and, for MTHFR, tHcy [OR for the highest vs. lowest tHcy quartile 8.13 (95% CI 1.83-36.1), p(trend)=0.002; OR for MTHFR 677TT vs. 677CC genotype 3.62 (95% CI 0.77-17.0), p(trend)=0.040]. Haplotype analyses confirmed that the MTHFR 677T-1298A haplotype was positively associated with hemorrhagic stroke [OR 1.81 (95% CI 1.09-3.00), p=0.022], whereas the MTHFR 677C-1298C haplotype was not significantly related to either hemorrhagic or ischemic stroke. Neither tHcy nor the MTHFR polymorphisms were significant predictors of ischemic stroke.

Conclusion: Both elevated plasma homocysteine levels and the MTHFR 677T allele are indicators of increased risk of hemorrhagic stroke in the northern Swedish population.

Motion analysis using inertial measurement units (IMU) has emerged as an alternative to optical motion capture. However, the validity and reliability of upper limb measurements varies significantly between studies. The objective of this study was to determine how sensor placement affects kinematic output in the assessment of motion of the arm, shoulder, and scapula. IMUs were placed proximally/distally on arms, and medially/laterally on the scapula, in a group of eleven healthy participants, while performing nine different motion tasks. Linear regressions and mixed models analysed how these different sensor placements affected the estimated joint motion by establishing the linear relationship between sensors placed on the same body segment. The placement of sensors affected the measured kinematic output considerably, most prominent affect was seen for sensor placement on scapula during flexion and abduction, and on forearm during pronation/supination. The slope of the linear regression lines was 2.5 during flexion, 2.7 during abduction, and 1.8 for forearm pronation/supination. The results of this study suggest that the forearm sensor should be placed on the dorsal side of the forearm, at the distal end; the upper arm sensor should be placed laterally, on the distal part of the arm; and the sensor on the scapula should be placed cranially, along the spine of scapula.

A piezoelectric transducer in a feedback circuit operating in a resonance state is the basis of a resonance sensor. Upon contact with a soft object a change in the resonance frequency reflects the acoustic impedance. Together with force measurement it is possible to obtain the elastic stiffness of the object. The aim of this study was to evaluate the concept of a hand-held resonance sensor for tissue stiffness measurement. A time derivative analysis of the force and the frequency change showed that a stiffness-sensitive parameter was independent of the impression speed. Soft tissue phantoms of gelatin were used in an experimental validation of the theory. A force indentation method was used as a reference method for assessing the gelatin's elastic stiffness. Results from the hand-held measurements showed that the stiffness parameter accurately measured the elastic stiffness of the gelatin (R² = 0.94, p < 0.05). The stiffness parameter was weakly (on average R² = 0.15) and non-significantly (p > 0.05, 14 out of 17) dependent on an impression speed parameter. On average, a small amount of the total variance was explained by the impression speed. In conclusion, soft tissue stiffness can be objectively measured with free-hand measurement with a resonance sensor. This study contributes a theoretical analysis and an experimental demonstration of the concept of a hand-held resonance sensor for stiffness measurements.

Prostate cancer is the most common type of cancer among men. Standard methods for detecting and diagnosing prostate cancer are not sensitive enough. Radical prostatectomy is a procedure where the prostate is removed as a treatment for prostate cancer. Objectively measured prostate stiffness could be a clinical marker for prostate cancer and this could be accomplished with a stiffness sensitive resonance sensor. A future handheld pen-like resonance sensor instrument could be a valuable clinical tool for locating cancer during radical prostatectomy surgery and thus aid in the diagnosis and treatment. The aim of this study was to evaluate the concept of a handheld resonance sensor for stiffness measurements on a soft tissue phantom. For a handheld resonance sensor set-up the impression depth and speed of the sensor tip into the tissue are unknown. A theoretical model was derived to show that a stiffness sensitive parameter can be obtained independent of the impression depth and the impression speed. The theoretical result was verified on a soft tissue phantom made of gelatin with a silicon tumor inclusion. These results were promising for further studies and development of a handheld instrument towards faster diagnosis of prostate cancer.

Prostate cancer is the most common type of cancer in men in Europe and the USA. Some prostate tumours are regarded as stiffer than the surrounding normal tissue, and therefore it is of interest to be able to reliably measure prostate tissue stiffness. The methods presently used to detect prostate cancer are inexact, and new techniques are needed. In this licentiate thesis resonance sensor technology, with its ability to measure tissue stiffness, was applied to normal and cancerous prostate tissue.

A piezoelectric transducer element in a feedback system can be set to vibrate at its resonance frequency. When the sensor element contacts an object a change in the resonance frequency is observed, and this feature has been utilized in sensor systems to describe physical properties of different objects. For medical applications it has been used to measure stiffness variations due to various pathophysiological conditions.

An impression-controlled resonance sensor system was used to quantify stiffness in human prostate tissue in vitro using a combination of frequency change and force measurements. Measurements on prostate tissue showed statistically significant (p < 0.001) and reproducible differences between normal healthy tissue and tumour tissue when using a multivariate parameter analysis. Measured stiffness varied in both the normal tissue and tumour tissue group. One source of variation was assumed to be related to differences in tissue composition. Other sources of error could be uneven surfaces, different levels of dehydration of the prostates, and actual differences between patients.

The prostate specimens were also subjected to morphometric measurements, and the sensor parameter was compared with the morphology of the tissue with linear regression. In the probe impression interval 0.5–1.7 mm, the maximum coefficient of determination was R2 ≥ 0.60 (p < 0.05, n = 75). An increase in the proportion of prostate stones (corpora amylacea), stroma, or cancer in relation to healthy glandular tissue increased the measured stiffness. Cancer and stroma had the greatest effect on the measured stiffness. The deeper the sensor was pressed, the greater, i.e., deeper, volume it sensed.

It is concluded that prostate cancer increases the measured stiffness as compared with healthy glandular tissue, but areas with predominantly stroma or many stones could be more difficult to differentiate from cancer. Furthermore, the results of this study indicated that the resonance sensor could be used to detect stiffness variations in human prostate tissue in vitro, and especially due to prostate cancer. This is promising for the development of a future diagnostic tool for prostate cancer.

Prostate cancer is the most frequent type of cancer in men in Europe and the USA. The methods presently used to detect and diagnose prostate cancer are inexact, and new techniques are needed. Prostate tumours can be regarded as harder than the surrounding normal healthy glandular tissue, and therefore it is of interest to be able to reliably measure prostate tissue stiffness. In this dissertation the approach was to evaluate tactile resonance sensor technology and its ability to measure mechanical properties and to detect cancer in human prostate tissue.

The tactile resonance sensor is based on a piezoelectric transducer element vibrating at its resonance frequency through a feedback circuit. A change in the resonance frequency is observed when the sensor contacts an object. This feature has been utilized to measure tissue stiffness variations due to various pathophysiological conditions.

An impression-controlled tactile resonance sensor system was first used to quantify stiffness and evaluate performance on silicone. Then the sensor system was used on fresh human prostate tissue in vitro to measure stiffness using a combination of frequency change and force measurements. Significant differences in measured stiffness between malignant and healthy normal tissue were found, but there were large variations within the groups.

Some of the variability was explained by prostate tissue histology using a tissue stiffness model. The tissue content was quantified at four depths in the tissue specimens with a microscope-image-based morphometrical method involving a circular grid. Numerical weights were assigned to the tissue data from the four depths, and the weighted tissue proportions were related to the measured stiffness through a linear model which was solved with a least-squares method. An increase in the proportion of prostate stones, stroma, or cancer in relation to healthy glandular tissue increased the measured stiffness. Stroma and cancer had the greatest effect and accounted for 90 % of the measured stiffness (45% and 45%, respectively).

The deeper the sensor was pressed, the greater, i.e., deeper, volume it sensed. A sensing depth was extrapolated from the numerical weights for the measurements performed at different impression depths. Horizontal surface tissue variations were studied by altering the circular grid size relative to the contact area between the sensor tip and the tissue. The results indicated that the sensing area was greater than the contact area. The sensor registered spatial tissue variations.

Tissue density-related variations, as measured by the frequency change, were weakly significant or non-significant. The measured force registered elastic-related tissue variations, to which stroma and cancer were the most important variables.

A theoretical material-dependent linear relation was found between frequency change and force from theoretical models of frequency change and force. Tactile resonance sensor measurements on prostate tissue verified this at small impression depths. From this model, a physical interpretation was given to the parameters used to describe stiffness.

These results indicate that tactile resonance sensor technology is promising for assessing soft tissue mechanical properties and especially for prostate tissue stiffness measurement with the goal of detecting prostate cancer. However, further studies and development of the sensor design must be performed to determine the full potential of the method and its diagnostic power. Preferably, measurements of tissue mechanical properties should be used in combination with other methods, such as optical methods, to increase the diagnostic power.

Prostate cancer is the most common type of cancer among men worldwide. Mechanical properties of prostate tissue are promising for distinguishing prostate cancer from healthy prostate tissue. The aim was to investigate the indentation loading response of a resonance sensor for discriminating prostate cancer tissue from normal tissue. Indentation measurements were done on prostate tissue specimens ex vivo from 10 patients from radical prostatectomy. The measurement areas were analysed using standard histological methods. The stiffness parameter was linearly dependent on the loading force (average R²= 0.90) and an increased loading force caused a greater stiffness contrast of prostate cancer vs normal tissue. The accuracy of the stiffness contrast was assessed by the ROC curve with the area under the curve being 0.941 for a loading force of 12.8 mN. The results are promising for the development of a resonance sensor instrument for detecting prostate cancer.

Prostate cancer is the most common cancer among men and the methods used to detect and diagnose prostate cancer are not sufficiently accurate. Radical prostatectomy is a surgical treatment of prostate cancer where the whole prostate is removed from the patient. Prostate tissue stiffness can be measured with a stiffness sensitive resonance sensor. The aim of this study was to measure the stiffness on the anterior and posterior side of fresh human prostate tissue in vitro and compare these two groups with each other and relate the findings with the prostate tissue histology.  In a prostate tissue slice with mostly normal healthy tissue, the anterior side was significantly harder (p-value < 0.05) as expected. In a prostate tissue slice with areas of cancer tumors, no difference was found between the anterior and posterior sides. However, large stiffness variations were found within groups with measurements points on cancer tissue (coefficient of variation, CV = 42 and 85%), as opposed to groups without cancer tissue (CV = 27 and 28%).  The large stiffness variations could be used as a sign for the presence of cancer. The results are promising for the development of an instrument and method for faster diagnosis on radical prostatectomy samples.

Tactile sensors based on piezoelectric resonance have been adopted for medical applications. The sensor consists of an oscillating piezoelectric sensor–circuit system, and a change in resonance frequency is observed when the sensor tip contacts a measured object such as tissue. The frequency change at a constant applied force or mass load is used as a stiffness-sensitive parameter in many applications. Differential relations between force and frequency have also been used for monitoring intraocular pressure and stiffness variations in prostate tissue in vitro. The aim of this study was to relate the frequency change (Δf), measured force (F) and the material properties, density and elasticity to an explanatory model for the resonance sensor measurement principle and thereby to give explanatory models for the stiffness parameters used previously. Simulations of theoretical equations were performed to investigate the relation between frequency change and contact impedance. Measurements with a resonance sensor system on prostate tissue in vitro were used for experimental validation of the theory. Tissue content was quantified with a microscopic-based morphometrical method. Simulation results showed that the frequency change was dependent upon density (ρ) and contact area (S) according to Δf ∝ ρS^3/2. The experiments followed the simulated theory at small impression depths. The measured contact force followed a theoretical model with the dependence of the elastic modulus (E) and contact area, F ∝ ES^3/2. Measured density variations related to histological variations were statistically weak or non-significant. Elastic variations were statistically significant with contributions from stroma and cancer relative to normal glandular tissue. The theoretical models of frequency change and force were related through the contact area, and a material-dependent explanatory model was found as Δf ∝ ρE⁻¹F. It explains the measurement principle and the previously established stiffness parameters from the material properties point of view.

Prostate cancer is the most common form of cancer in men in Europe and in the USA. Some prostate tumours are stiffer than the surrounding normal tissue, and it could therefore be of interest to measure prostate tissue stiffness. Resonance sensor technology based on piezoelectric resonance detects variations in tissue stiffness due to a change in the resonance frequency. An impression-controlled resonance sensor system was used to detect stiffness in silicone rubber and in human prostate tissue in vitro using two parameters, both combinations of frequency change and force. Variations in silicone rubber stiffness due to the mixing ratio of the two components could be detected (p<0.05) using both parameters. Measurements on prostate tissue showed that there existed a statistically significant (MANOVA test, p<0.001) reproducible difference between tumour tissue (n=13) and normal healthy tissue (n=98) when studying a multivariate parameter set. Both the tumour tissue and normal tissue groups had variations within them, which were assumed to be related to differences in tissue composition. Other sources of error could be uneven surfaces and different levels of dehydration for the prostates. Our results indicated that the resonance sensor could be used to detect stiffness variations in silicone and in human prostate tissue in vitro. This is promising for the development of a future diagnostic tool for prostate cancer.

Prostate cancer is the most common type of cancer in men in Europe and the US. The methods to detect prostate cancer are still precarious and new techniques are needed. A piezoelectric transducer element in a feedback system is set to vibrate with its resonance frequency. When the sensor element contacts an object a change in the resonance frequency is observed, and this feature has been utilized in sensor systems to describe physical properties of different objects. For medical applications it has been used to measure stiffness variations due to various patho-physiological conditions. In this study the sensor's ability to measure the stiffness of prostate tissue, from two excised prostatectomy specimens in vitro, was analysed. The specimens were also subjected to morphometric measurements, and the sensor parameter was compared with the morphology of the tissue with linear regression. In the probe impression interval 0.5-1.7 mm, the maximum R(2) > or = 0.60 (p < 0.05, n = 75). An increase in the proportion of prostate stones (corpora amylacea), stroma, or cancer in relation to healthy glandular tissue increased the measured stiffness. Cancer and stroma had the greatest effect on the measured stiffness. The deeper the sensor was pressed, the greater, i.e., deeper, volume it sensed. Tissue sections deeper in the tissue were assigned a lower mathematical weighting than sections closer to the sensor probe. It is concluded that cancer increases the measured stiffness as compared with healthy glandular tissue, but areas with predominantly stroma or many stones could be more difficult to differ from cancer.

Purpose: The aim of this study was to investigate the filtration efficacy of a 38-µm 1-layer screen filter based on Doppler registrations and video recordings of gaseous microbubbles (GME) observed in a microscope.

Methods: The relative filtration efficacy (RFE) was calculated from 20 (n = 20) sequential bursts of air introduced into the Plasmodex® primed test circuit.

Results: The main findings indicate that the RFE decreased (p = 0.00), with increasing flow rates (100-300 mL/min) through the filter screen. This reaction was most accentuated for GME below the size of 100 µm, where counts of GME paradoxically increased after filtration, indicating GME fragmentation. For GME sized between 100-250 µm, the RFE was constantly >60%, independently of the flow rate level. The video recording documenting the GME interactions with the screen filter confirmed the experimental findings.

Conslusions: The 38-µm 1-layer screen filter investigated in this experimental setup was unable to trap gaseous microbubbles effectively, especially for GME below 100 µm in size and in conjunction with high flow rates.

Denna avhandling berör frågan: är det möjligt, med en piezoelektrisk sensor/vibrator, att detektera ett hårt objekt inneslutet i en fantom av silikongummi? Frågan närmades utan begränsningar och uppgiften delades upp i tre tydliga delar: karaktäriseringen av den piezoelektriska sensorn/vibratorn (paper I), skapa en modell av det viskoelastiska uppförandet hos ett vävnadsliknande material (fantom) som står i kontakt med sensorn-/vibratorn (paper II) och att detektera förekomsten av ett hårt objekt inneslutet i fantomen (paper III). En finit element modell (FEM) skapades för att beräkna vibrationerna hos sensorn/vibratorn och fantomen. För att minimera beräkningstiden och maximera modellens förmåga att återge vibrationer på ett korrekt sätt, så skapades ett tvådimensionellt modellsystem bestående av en cylindrisk piezoelektrisk sensor/vibrator i kontakt med en cylindrisk fantom av silikongummi. Sensorn/vibratorn skickar radiella elastiska vågor in i fantomen. Den piezoelektriska sensorn/vibratorn karakteriserades med hjälp av en procedur som anpassar parametervärden med hjälp av övertoner. Proceduren möjliggör en justering av parametervärdena så att uppmätta och beräknade impedansspektra överensstämmer. En 'fractional derivative' modell av de viskoelastiska egenskaperna hos silikongummit skapades. De hyperelastiska egenskaperna vid första radiella resonansen blev kompenserade med hjälp av en sigmoidformad funktion. Den komplexa viskoelastiska modulen bestämdes för höga frekvenser med hjälp av transitioner hos stående Lambvågor i fantomen. Närvaron av ett hårt ringformat objekt i fantomen detekterades med hjälp av förändringar i mönstret hos de stående Lambvågorna. Justeringen av de piezoelektriska parametrarna hos elementet PZT5A1 gav som mest en skillnad på 0.54% mellan uppmätta och beräknade impedansspektra. Medelvärdet hos tre prov av silikongummit Silgel 612 av den komplexa elastiska modulen uppmättes till (0.97 + 0.009i) GPa  vid 100 kHz och (0.97 + 0.005i) GPa vid 250 kHz. Närvaron av ett hårt objekt, gjort av polyaramid (PA6GPE), detekterades i fantomen med hjälp av multifrekvensiella fotavtryck.

To gain an understanding of the high-frequency elastic properties of silicone rubber, a finite element model of a cylindrical piezoelectric element, in contact with a silicone rubber disk, was constructed. The frequency dependent elastic modulus of the silicone rubber was modeled by a four parameter fractional derivative viscoelastic model in the 100 kHz to 250 kHz frequency range. The calculations were carried out in the range of the first radial resonance frequency of the sensor. At the resonance, the hyperelastic effect of the silicone rubber was modeled by a hyperelastic compensating function. The calculated response was matched to the measured response by using the transitional peaks in the impedance spectrum that originates from the switching of standing Lamb wave modes in the silicone rubber. To validate the results, the impedance responses of three 5 mm thick silicone rubber disks, with different radial lengths, were measured. The calculated and measured transitional frequencies have been compared in detail. The comparison showed very good agreement, with average relative differences of 0.7 %, 0.6 %, and 0.7 % for the silicone rubber samples with radial lengths of 38.0 mm, 21.4 mm, and 11.0 mm, respectively. The average, complex, elastic modulus of the samples were: (0.97 + 0.009i) GPa at 100 kHz and (0.97 + 0.005i) GPa at 250 kHz.

The presence of an inclusion in a cylindrical silicone rubber disk is determined using FEM, standing Lamb waves, and an algorithm using multiple frequency footprints. Radial elastic waves are emitted into the disk by a cylindrical piezoelectric sensor placed in the center of the disk. The visco-elastic properties of the silicone rubber disk is modeled by a fractional derivative model and the hyperelastic effect at the radial resonance frequency was compensated for. Using the finite element model, the Lamb wave transition frequencies in the impedance frequency response of the sensor was calculated for a specified position of the inclusion. The set of frequencies was named the footprint for that position. The position of the inclusion was varied between 0.05 to 0.95, with a step of 0.01, of the radial length of the silicone rubber disk. For each position, a footprint was calculated. The footprints,s, with corresponding positions, were stored in a database. A positioning algorithm was developed that could match an unknown footprint to a footprint in the database. A self-test of the algorithm showed that the correct position was found for 94% of the tested positions. The results of the positioning algorithm was that the presence of the inclusions were detected, and that the positions of the inclusions at 0.38 and 0.63 were estimated by the positioning algorithm as: 0.45 and 0.74, with relative errors +18% and +17% respectively. The positions are given as the ratio of the radius of the inclusion to the silicone rubber disk radius.

Background: Idiopathic intracranial hypertension (IIH) is a rare disease of unknown aetiology related possibly to disturbed cerebrospinal fluid (CSF) dynamics and characterised by elevated intracranial pressure (ICP) causing optic nerve atrophy if not timely treated. We studied CSF dynamics of the IIH patients based on the available literature and our well-defined cohort.

Method: A literature review was performed from PubMed between 1980 and 2020 in compliance with the PRISMA guideline. Our study includes 59 patients with clinical, demographical, neuro-ophthalmological, radiological, outcome data, and lumbar CSF pressure measurements for suspicion of IIH; 39 patients had verified IIH while 20 patients did not according to Friedman’s criteria, hence referred to as symptomatic controls.

Results: The literature review yielded 19 suitable studies; 452 IIH patients and 264 controls had undergone intraventricular or lumbar CSF pressure measurements. In our study, the mean CSF pressure, pulse amplitudes, power of respiratory waves (RESP), and the pressure constant (P0) were higher in IIH than symptomatic controls (p < 0.01). The mean CSF pressure was higher in IIH patients with psychiatric comorbidity than without (p < 0.05). In IIH patients without acetazolamide treatment, the RAP index and power of slow waves were also higher (p < 0.05). IIH patients with excess CSF around the optic nerves had lower relative pulse pressure coefficient (RPPC) and RESP than those without (p < 0.05).

Conclusions: Our literature review revealed increased CSF pressure, resistance to CSF outflow and sagittal sinus pressure (SSP) as key findings in IIH. Our study confirmed significantly higher lumbar CSF pressure and increased CSF pressure waves and RAP index in IIH when excluding patients with acetazolamide treatment. In overall, the findings reflect decreased craniospinal compliance and potentially depleted cerebral autoregulation resulting from the increased CSF pressure in IIH. The increased slow waves in patients without acetazolamide may indicate issues in autoregulation, while increased P0 could reflect the increased SSP.

Background: Amyloid transthyretin (ATTR) cardiomyopathy is caused by the deposition of misfolded proteins, known as amyloid fibrils, in the myocardium. Quantitative Single Photon Emission Computed Tomography (QSPECT) utilizing 99mTc-DPD scintigraphy has the potential to assess ATTR-suspected cardiac amyloidosis (CA). This method could offer improved risk stratification and therapy response monitoring compared to the established Perugini score system. The primary objective of this study is to evaluate the feasibility of employing a quantitative approach and correlating various parameters with LVMI (left ventricular mass index).

Method: Initially, planar and volumetric sensitivity measurements were conducted, followed by verification of accuracy measurements. Several torso phantom acquisitions were then performed to evaluate the accuracy and repeatability in terms of recovery coefficient (RC) and repeatability deviation (RD). This served as the foundation for the subsequent in vivo quantification. In this retrospective study, 10 patients underwent 99mTc-DPD scintigraphy, including SPECT/CT of the thorax and echocardiography examinations, as part of a clinical routine for suspected CA. The myocardial SUVmax was determined using a semi-automatic segmentation of the entire heart, excluding the descending and ascending aortas. The bone uptake was also quantified using the SUVmean parameter within the automatically delineated volume of all bones. This enabled the determination of the normalized uptake value nSUVmax, (SUVmax to SUVmean bone). Moreover, an attempt was made to apply an automatic segmentation of the myocardium based on 26% and 36% thresholds, which were developed from the torso phantom acquisitions. This approach allowed for the utilization of the injected dose (ID).

Results: The planar calibration factor (CF) exceeded the volumetric cross-calibration factor (CCF) by 3.4%. The anthropomorphic phantom exhibited an underestimation of approximately 50% in the myocardium and around 21% in the kidneys. The average RD in the myocardium and kidneys was 2.3% and 1.6%, respectively. A significant quantitative separation was observed between the ATTR and control groups, comprising 6 and 4 patients, respectively (p<0.01 for SUVmax and nSUVmax, and p<0.02 for SUVmean bone). Correlation analysis revealed a weak positive correlation between SUVmax and LVMI; however, the correlation was not statistically significant (ρ = 0.31, p = 0.39). The ID in the 26% and 36% threshold-based segmented myocardium showed a relatively lower negative correlation with LVMI; although this was observed in the small ATTR cohort and was not statistically significant. The latter outcome resulted from the automatic-delineation method, which was unable to segment grade 0 and 1 patients.

Conclusion: This study suggests that both CFs can be used in QSPECT. The phantom measurements indicate good repeatability and a significant quantitative underestimation, primarily due to the partial volume effect (PVE). Size and shape-specific PVE corrections, encompassing various activity concentrations of myocardium-to-blood pool ratios, are essential in QSPECT of the myocardium. Moreover, quantitative SPECT/CT utilizing 99mTc-DPD scintigraphy can effectively distinguish between patients with grade 0/1 and those with grade 2/3. This approach has the potential to enhance diagnostic accuracy and improve risk stratification.

BACKGROUND: Adipose tissue cells produce cathepsins L and S, which have proatherogenic effects. Obesity is strongly linked to atherogenesis, cardiovascular morbidity, and mortality. OBJECTIVE: The aim of the present study was to see if life style interventions/weight reduction could decrease cathepsin L and S levels in blood plasma. METHOD: Study subjects (n=31) were recruited to a life style intervention program aiming at increased physical activity, more healthy eating habits, and weight reduction for most of the participants. Blood samples were collected at inclusion and after 4 and 8 weeks. RESULTS: Cathepsin L was significantly reduced at 4 weeks (p<0.0001) and 8 weeks (p=0.0004). A similar reduction was also seen for cathepsin S at 4 weeks (p=0.03) and 8 weeks (p=0.008). No significant change in fractalkine values was observed at 4 weeks (p=0.58), but a significant increase was apparent at 8 weeks (p=0.0002). CONCLUSION: The intervention program resulted in significant reductions of cathepsin L and S levels in plasma after 4 and 8 weeks of intervention.

Tracercenter på Norrlands Universitetssjukhus producerar radiotracers. För att mäta aktiviteten hos de radioaktiva isotoperna används idag en jonkammare tillsammans med mjukvara byggt på Windows XP. Målet med det här examensarbetet är att bygga ny mjukvara som är kompatibelt med Windows 10. Mjukvaran ska tillhandahålla kalibreringsmöjligheter för isotoperna F-18, C-11 och Cs-137 samt kunna överföra uppmätt värde till datahanteringssystemet PETra.Med användandet av kodspråket Python och biblioteket TkInter har ett användargränsnitt och bakomliggande funktionskod utvecklats. Mjukvaran kommunicerar med både jonkammare och PETra seriellt via COM-Port. Linjäritetstester har gjorts för jonkammaren som påvisat god linjäritet. Detta resultat bekräftar mjukvarans tillförlitlighet med en liten felmarginal. Ytterligare tester behövs för att fastställa magnituden av felmarginalen.

Prostate cancer surgery risks erectile problems and incontinence for the patient. An instrument for guiding surgeons to avoid nerve bundle damage and ensure complete cancer removal is desirable. We present a tactile resonance sensor made of PZT ceramics, mounted in a 3D motorized translation stage for scanning and measuring tissue stiffness for detecting cancer in human prostate. The sensor may be used during surgery for guidance, scanning the prostate surface for the presence of cancer, indicating migration of cancer cells into surrounding tissue. Ten fresh prostates, obtained from patients undergoing prostate cancer surgery, were cut into 0.5 cm thick slices. Each slice was measured for tissue stiffness at about 25 different sites and compared to histology for validation cancer prediction by stiffness. The statistical analysis was based on a total of 148 sites with non-cancer and 40 sites with cancer. Using a generalized linear mixed model (GLMM), the stiffness data predicted cancer with an area under the curve of 0.74, after correcting for overfitting using bootstrap validation. Mean prostate stiffness on the logarithmic scale (p = 0.015) and standardized Z-scores (p = 0.025) were both significant predictors of cancer. This study concludes that stiffness measured by the tactile resonance sensor is a significant predictor of prostate cancer with potential for future development towards a clinical instrument for surgical guidance.

Prostate cancer (PCa) is the most common cancer form for men in Europe. A sensor system combining Raman spectroscopy and stiffness sensing with a resonance sensor has recently been developed by us for prostate cancer detection. In this study the sensor system has been used for measurements on two slices of fresh human prostate tissue. The stiffness sensor could detect locations slices with significantly different stiffness contrasts (p < 0.05). Raman spectroscopic measurements could be performed with the dual-modality probe for tissue classification. The findings are important for the continued development of a combination probe for prostate cancer detection.

Prostate cancer is the most common cancer for men in the western world. The most prevalent curative treatment is radical prostatectomy. However, prostate surgery can give unwanted side effects and there is a need for an instrument that can provide decision support to the surgeon during surgery on the presence of cancer cells in the surgical margin. A dual modality probe, combining Raman spectroscopy and tactile resonance technology, has been used for detecting cancer in fresh human prostate tissue. The tactile resonance modality measures the tissue stiffness and Raman spectroscopy depicts the molecular content in tissue, both related to cancer. After ethical approval, the study investigated the potential of the dual-modality probe by testing its ability to differentiate between normal and cancerous prostate tissue ex vivo. It also investigated the minimal amount of measurement points needed to securely detect cancer on the surface of prostate tissue. Measurements on three prostate tissue slices show that the tactile resonance modality measuring stiffness was able to detect differences between normal and cancerous tissue on a significant level of 90%, but the sample size was too low to draw any firm conclusions. It was also suggested from the study results that the high wavenumber region in the Raman spectrum can give valuable information about cancer in prostate tissue. A number of 24 measurement points were enough for detecting cancer in prostate slices in this study. It can be suggested from this study that combining these two sensor modalities is promising for accurate detection of prostate cancer that is needed during prostate surgery, but more measurements including more prostates must be performed before the full value of the study result can be established.