Umeå University's logo

umu.sePublications
Change search
Link to record
Permanent link

Direct link
Brynolfsson, Patrik
Publications (10 of 22) Show all publications
Holmlund, W., Simkó, A., Söderkvist, K., Palásti, P., Tótin, S., Kalmár, K., . . . Nyholm, T. (2024). ProstateZones: segmentations of the prostatic zones and urethra for the PROSTATEx dataset. Scientific Data, 11(1), Article ID 1097.
Open this publication in new window or tab >>ProstateZones: segmentations of the prostatic zones and urethra for the PROSTATEx dataset
Show others...
2024 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 11, no 1, article id 1097Article in journal (Refereed) Published
Abstract [en]

Manual segmentations are considered the gold standard for ground truth in machine learning applications. Such tasks are tedious and time-consuming, albeit necessary to train reliable models. In this work, we present a dataset with expert segmentations of the prostatic zones and urethra for 200 randomly selected patients from the PROSTATEx dataset. Notably, independent duplicate segmentations were performed for 40 patients, providing inter-reader variability data. This results in a total of 240 segmentations. This dataset can be used to train machine learning models or serve as an external test set for evaluating models trained on private data, thereby addressing a current gap in the field. The delineated structures and terminology adhere to the latest Prostate Imaging Reporting and Data Systems v2.1 guidelines, ensuring consistency.

Place, publisher, year, edition, pages
Springer Nature, 2024
National Category
Radiology, Nuclear Medicine and Medical Imaging Computer Sciences
Identifiers
urn:nbn:se:umu:diva-230979 (URN)10.1038/s41597-024-03945-2 (DOI)001331330300004 ()39379407 (PubMedID)2-s2.0-85205955286 (Scopus ID)
Available from: 2024-10-29 Created: 2024-10-29 Last updated: 2024-10-29Bibliographically approved
Wang, J., Garpebring, A., Brynolfsson, P. & Yu, J. (2021). Contrast Agent Quantification by Using Spatial Information in Dynamic Contrast Enhanced MRI. Frontiers in Signal Processing, 1, Article ID 727387.
Open this publication in new window or tab >>Contrast Agent Quantification by Using Spatial Information in Dynamic Contrast Enhanced MRI
2021 (English)In: Frontiers in Signal Processing, E-ISSN 2673-8198, Vol. 1, p. 12article id 727387Article in journal (Refereed) Published
Abstract [en]

The purpose of this work is to investigate spatial statistical modelling approaches to improve contrast agent quantification in dynamic contrast enhanced MRI, by utilising the spatial dependence among image voxels. Bayesian hierarchical models (BHMs), such as Besag model and Leroux model, were studied using simulated MRI data. The models were built on smaller images where spatial dependence can be incorporated, and then extended to larger images using the maximum a posteriori (MAP) method. Notable improvements on contrast agent concentration estimation were obtained for both smaller and larger images. For smaller images: the BHMs provided substantial improved estimates in terms of the root mean squared error (rMSE), compared to the estimates from the existing method for a noise level equivalent of a 12-channel head coil at 3T. Moreover, Leroux model outperformed Besag models with two different dependence structures. Specifically, the Besag models increased the estimation precision by 27% around the peak of the dynamic curve, while the Leroux model improved the estimation by 40% at the peak, compared with the existing estimation method. For larger images: the proposed MAP estimators showed clear improvements on rMSE for vessels, tumor rim and white matter.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2021. p. 12
Keywords
Contrast agent quantication, BHM, Besag, Leroux, INLA, MAP
National Category
Probability Theory and Statistics Medical Imaging
Research subject
Mathematical Statistics; Radiology
Identifiers
urn:nbn:se:umu:diva-141525 (URN)10.3389/frsip.2021.727387 (DOI)001093041400001 ()2-s2.0-85212500211 (Scopus ID)
Funder
Swedish Research Council, 2013-5342
Note

Originally included in thesis in manuscript form.

Available from: 2017-11-07 Created: 2017-11-07 Last updated: 2025-02-09Bibliographically approved
Grill, F., Johansson, J., Axelsson, J., Brynolfsson, P., Nyberg, L. & Rieckmann, A. (2021). Dissecting Motor and Cognitive Component Processes of a Finger-Tapping Task With Hybrid Dopamine Positron Emission Tomography and Functional Magnetic Resonance Imaging. Frontiers in Human Neuroscience, 15, Article ID 733091.
Open this publication in new window or tab >>Dissecting Motor and Cognitive Component Processes of a Finger-Tapping Task With Hybrid Dopamine Positron Emission Tomography and Functional Magnetic Resonance Imaging
Show others...
2021 (English)In: Frontiers in Human Neuroscience, E-ISSN 1662-5161, Vol. 15, article id 733091Article in journal (Refereed) Published
Abstract [en]

Striatal dopamine is involved in facilitation of motor action as well as various cognitive and emotional functions. Positron emission tomography (PET) is the primary imaging method used to investigate dopamine function in humans. Previous PET studies have shown striatal dopamine release during simple finger tapping in both the putamen and the caudate. It is likely that dopamine release in the putamen is related to motor processes while dopamine release in the caudate could signal sustained cognitive component processes of the task, but the poor temporal resolution of PET has hindered firm conclusions. In this study we simultaneously collected [11C]Raclopride PET and functional Magnetic Resonance Imaging (fMRI) data while participants performed finger tapping, with fMRI being able to isolate activations related to individual tapping events. The results revealed fMRI-PET overlap in the bilateral putamen, which is consistent with a motor component process. Selective PET responses in the caudate, ventral striatum, and right posterior putamen, were also observed but did not overlap with fMRI responses to tapping events, suggesting that these reflect non-motor component processes of finger tapping. Our findings suggest an interplay between motor and non-motor-related dopamine release during simple finger tapping and illustrate the potential of hybrid PET-fMRI in revealing distinct component processes of cognitive functions.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2021
Keywords
finger tapping, PET, fMRI, dopamine, cognitive component, striatum
National Category
Neurosciences
Identifiers
urn:nbn:se:umu:diva-194737 (URN)10.3389/fnhum.2021.733091 (DOI)000741902700001 ()34912200 (PubMedID)2-s2.0-85121204052 (Scopus ID)
Funder
Swedish Research Council, 2015-03080Knut and Alice Wallenberg Foundation, 2015.0277
Available from: 2022-05-16 Created: 2022-05-16 Last updated: 2024-01-17Bibliographically approved
Rutegård, M., Båtsman, M., Blomqvist, L., Rutegård, M., Axelsson, J., Ljuslinder, I., . . . Riklund, K. (2020). Rectal cancer: a methodological approach to matching PET/MRI to histopathology. Cancer Imaging, 20(1), Article ID 80.
Open this publication in new window or tab >>Rectal cancer: a methodological approach to matching PET/MRI to histopathology
Show others...
2020 (English)In: Cancer Imaging, ISSN 1740-5025, E-ISSN 1470-7330, Vol. 20, no 1, article id 80Article in journal (Refereed) Published
Abstract [en]

Purpose: To enable the evaluation of locoregional disease in the on-going RECTOPET (REctal Cancer Trial on PET/MRI/CT) study; a methodology to match mesorectal imaging findings to histopathology is presented, along with initial observations.

Methods: FDG-PET/MRI examinations were performed in twenty-four consecutively included patients with rectal adenocarcinoma. In nine patients, of whom five received neoadjuvant treatment, a postoperative MRI of the surgical specimen was performed. The pathological cut-out was performed according to clinical routine with the addition of photo documentation of each slice of the surgical specimen, meticulously marking the location, size, and type of pathology of each mesorectal finding. This allowed matching individual nodal structures from preoperative MRI, via the specimen MRI, to histopathology.

Results: Preoperative MRI identified 197 mesorectal nodal structures, of which 92 (47%) could be anatomically matched to histopathology. Of the matched nodal structures identified in both MRI and histopathology, 25% were found to be malignant. These malignant structures consisted of lymph nodes (43%), tumour deposits (48%), and extramural venous invasion (9%). One hundred eleven nodal structures (55%) could not be matched anatomically. Of these, 97 (87%) were benign lymph nodes, and 14 (13%) were malignant nodal structures. Five were malignant lymph nodes, and nine were tumour deposits, all of which had a short axis diameter < 5 mm.

Conclusions: We designed a method able to anatomically match and study the characteristics of individual mesorectal nodal structures, enabling further research on the impact of each imaging modality. Initial observations suggest that small malignant nodal structures assessed as lymph nodes in MRI often comprise other forms of mesorectal tumour spread.

Trial registration: Clinical Trials Identifier: NCT03846882.

Place, publisher, year, edition, pages
BioMed Central (BMC), 2020
Keywords
Rectal neoplasms, EMVI, Staging, Lymph nodes, Tumour deposits
National Category
Cancer and Oncology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:umu:diva-176783 (URN)10.1186/s40644-020-00347-6 (DOI)000583174400001 ()33129352 (PubMedID)2-s2.0-85094683721 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationCancerforskningsfonden i Norrland
Available from: 2020-11-26 Created: 2020-11-26 Last updated: 2025-04-09Bibliographically approved
Löfstedt, T., Brynolfsson, P., Nyholm, T. & Garpebring, A. (2019). Gray-level invariant Haralick texture features. PLOS ONE, 14(2), Article ID e0212110.
Open this publication in new window or tab >>Gray-level invariant Haralick texture features
2019 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 14, no 2, article id e0212110Article in journal (Refereed) Published
Abstract [en]

Haralick texture features are common texture descriptors in image analysis. To compute the Haralick features, the image gray-levels are reduced, a process called quantization. The resulting features depend heavily on the quantization step, so Haralick features are not reproducible unless the same quantization is performed. The aim of this work was to develop Haralick features that are invariant to the number of quantization gray-levels. By redefining the gray-level co-occurrence matrix (GLCM) as a discretized probability density function, it becomes asymptotically invariant to the quantization. The invariant and original features were compared using logistic regression classification to separate two classes based on the texture features. Classifiers trained on the invariant features showed higher accuracies, and had similar performance when training and test images had very different quantizations. In conclusion, using the invariant Haralick features, an image pattern will give the same texture feature values independent of image quantization.

Place, publisher, year, edition, pages
Public Library of Science, 2019
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:umu:diva-134995 (URN)10.1371/journal.pone.0212110 (DOI)000459709100037 ()30794577 (PubMedID)2-s2.0-85062005861 (Scopus ID)
Note

Originally included in thesis in manuscript form

Available from: 2017-05-15 Created: 2017-05-15 Last updated: 2024-07-02Bibliographically approved
Rutegård, M., Båtsman, M., Axelsson, J., Brynolfsson, P., Brännström, F., Rutegård, J., . . . Riklund, K. (2019). PET/MRI and PET/CT hybrid imaging of rectal cancer - description and initial observations from the RECTOPET (REctal Cancer trial on PET/MRI/CT) study. Cancer Imaging, 19, Article ID 52.
Open this publication in new window or tab >>PET/MRI and PET/CT hybrid imaging of rectal cancer - description and initial observations from the RECTOPET (REctal Cancer trial on PET/MRI/CT) study
Show others...
2019 (English)In: Cancer Imaging, ISSN 1740-5025, E-ISSN 1470-7330, Vol. 19, article id 52Article in journal (Refereed) Published
Abstract [en]

PurposeThe role of hybrid imaging using F-18-fluoro-2-deoxy-D-glucose positron-emission tomography (FDG-PET), computed tomography (CT) and magnetic resonance imaging (MRI) to improve preoperative evaluation of rectal cancer is largely unknown. To investigate this, the RECTOPET (REctal Cancer Trial on PET/MRI/CT) study has been launched with the aim to assess staging and restaging of primary rectal cancer. This report presents the study workflow and the initial experiences of the impact of PET/CT on staging and management of the first patients included in the RECTOPET study.MethodsThis prospective cohort study, initiated in September 2016, is actively recruiting patients from Region Vasterbotten in Sweden. This pilot study includes patients recruited and followed up until December 2017. All patients had a biopsy-verified rectal adenocarcinoma and underwent a minimum of one preoperative FDG-PET/CT and FDG-PET/MRI examination. These patients were referred to the colorectal cancer multidisciplinary team meeting at Umea University Hospital. All available data were evaluated when making management recommendations. The clinical course was noted and changes consequent to PET imaging were described; surgical specimens underwent dedicated MRI for anatomical matching between imaging and histopathology.ResultsTwenty-four patients have so far been included in the study. Four patients were deemed unresectable, while 19 patients underwent or were scheduled for surgery; one patient was enrolled in a watch-and-wait programme after restaging. Consequent to taking part in the study, two patients were upstaged to M1 disease: one patient was diagnosed with a solitary hepatic metastasis detected using PET/CT and underwent metastasectomy prior to rectal cancer surgery, while one patient with a small, but metabolically active, lung nodulus experienced no change of management. PET/MRI did not contribute to any recorded change in patient management.ConclusionsThe RECTOPET study investigating the role of PET/CT and PET/MRI for preoperative staging of primary rectal cancer patients will provide novel data that clarify the value of adding hybrid to conventional imaging, and the role of PET/CT versus PET/MRI.Trial registrationNCT03846882.

Place, publisher, year, edition, pages
BMC, 2019
Keywords
Rectal neoplasm, Rectal tumour, Staging, Lymph nodes, Tumour deposits, PET, CT, FDG-PET, CT, PET
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-161991 (URN)10.1186/s40644-019-0237-1 (DOI)000477054900002 ()31337428 (PubMedID)2-s2.0-85069762976 (Scopus ID)
Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2025-04-09Bibliographically approved
Skorpil, M., Ryden, H., Berglund, J., Brynolfsson, P., Brosjö, O. & Tsagozis, R. (2019). Soft-tissue fat tumours: differentiating malignant from benign using proton density fat fraction quantification MRI. Clinical Radiology, 74(7), 534-538
Open this publication in new window or tab >>Soft-tissue fat tumours: differentiating malignant from benign using proton density fat fraction quantification MRI
Show others...
2019 (English)In: Clinical Radiology, ISSN 0009-9260, E-ISSN 1365-229X, Vol. 74, no 7, p. 534-538Article in journal (Refereed) Published
Abstract [en]

Aim: To evaluate if quantifying proton density fat fraction (PDFF) would be useful in separating lipoma, atypical lipomatous tumour (ALT) and liposarcoma in the extremities and trunk. In addition, differentiating ALT versus non-classical lipomas using magnetic resonance imaging (MRI)-based fatty acidcomposition (FAC) and three-dimensional (3D) texture analysis was tested.

Material and methods: This prospective study (undertaken between 2014–2017; comprising 20 women, 21 men) was approved by the Regional Ethical Review Board and informed consent was obtained from all participants. For PDFF and FAC 3D spoiled gradient multi-echo images were acquired. PDFF was analysed in 16 lipomas (25–76 years), 14 ALTs (42–78 years) and 11 myxoid liposarcomas (31–68 years). The difference of mean PDFF was tested with one-way analysis of variance. A support vector machine algorithm was used to find the separating mean PDFF values.

Results: Mean PDFF for lipomas was 90% (range 76–98%), for ALT 83% (range 62–91%), and for liposarcoma 4% (range 0–21%). The difference of mean PDFF for liposarcomas versus ALT and lipoma was significant (p=0.0001, for both), and for ALT versus lipoma (p=0.021). The optimal threshold for separating liposarcoma from ALT and lipoma was 41.5%, and for ALT and lipoma 85%. Texture analysis could not separate ALT and non-classical lipomas, while the difference for FAC unsaturation degree was significant (p=0.013).

Conclusion: Measuring PDFF is a promising complement to standard MRI, to separate liposarcomas from ALT and lipomas. Lipomas that are not solely composed of fat cannot confidently be separated from ALT using PDFF, FAC, or texture analysis.

Place, publisher, year, edition, pages
Saunders Elsevier, 2019
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-160276 (URN)10.1016/j.crad.2019.01.011 (DOI)000469026600007 ()31000331 (PubMedID)2-s2.0-85064161077 (Scopus ID)
Available from: 2019-06-17 Created: 2019-06-17 Last updated: 2023-03-24Bibliographically approved
Garpebring, A., Brynolfsson, P., Kuess, P., Georg, D., Helbich, T. H., Nyholm, T. & Löfstedt, T. (2018). Density Estimation of Grey-Level Co-Occurrence Matrices for Image Texture Analysis. Physics in Medicine and Biology, 63(19), 9-15, Article ID 195017.
Open this publication in new window or tab >>Density Estimation of Grey-Level Co-Occurrence Matrices for Image Texture Analysis
Show others...
2018 (English)In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 63, no 19, p. 9-15, article id 195017Article in journal (Refereed) Published
Abstract [en]

The Haralick texture features are common in the image analysis literature, partly because of their simplicity and because their values can be interpreted. It was recently observed that the Haralick texture features are very sensitive to the size of the GLCM that was used to compute them, which led to a new formulation that is invariant to the GLCM size. However, these new features still depend on the sample size used to compute the GLCM, i.e. the size of the input image region-of-interest (ROI).

The purpose of this work was to investigate the performance of density estimation methods for approximating the GLCM and subsequently the corresponding invariant features.

Three density estimation methods were evaluated, namely a piece-wise constant distribution, the Parzen-windows method, and the Gaussian mixture model. The methods were evaluated on 29 different image textures and 20 invariant Haralick texture features as well as a wide range of different ROI sizes.

The results indicate that there are two types of features: those that have a clear minimum error for a particular GLCM size for each ROI size, and those whose error decreases monotonically with increased GLCM size. For the first type of features, the Gaussian mixture model gave the smallest errors, and in particular for small ROI sizes (less than about 20×20).

In conclusion, the Gaussian mixture model is the preferred method for the first type of features (in particular for small ROIs). For the second type of features, simply using a large GLCM size is preferred.

Place, publisher, year, edition, pages
Institute of Physics and Engineering in Medicine, 2018
Keywords
Haralick features, invariant features, GLCM, density estimation, texture analysis, image analysis
National Category
Computer graphics and computer vision Other Mathematics
Identifiers
urn:nbn:se:umu:diva-152488 (URN)10.1088/1361-6560/aad8ec (DOI)000446205200005 ()30088815 (PubMedID)2-s2.0-85054100030 (Scopus ID)
Funder
Västerbotten County CouncilVINNOVA
Available from: 2018-10-08 Created: 2018-10-08 Last updated: 2025-02-01Bibliographically approved
Brynolfsson, P., Löfstedt, T., Asklund, T., Nyholm, T. & Garpebring, A. (2018). Gray-level invariant Haralick texture features. Paper presented at 37th Meeting of the European-Society-for-Radiotherapy-and-Oncology (ESTRO), APR 20-24, 2018, Barcelona, SPAIN. Radiotherapy and Oncology, 127, S279-S280
Open this publication in new window or tab >>Gray-level invariant Haralick texture features
Show others...
2018 (English)In: Radiotherapy and Oncology, ISSN 0167-8140, E-ISSN 1879-0887, Vol. 127, p. S279-S280Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:umu:diva-150493 (URN)10.1016/S0167-8140(18)30837-5 (DOI)000437723401139 ()
Conference
37th Meeting of the European-Society-for-Radiotherapy-and-Oncology (ESTRO), APR 20-24, 2018, Barcelona, SPAIN
Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2024-07-02Bibliographically approved
Brynolfsson, P., Axelsson, J., Holmberg, A., Jonsson, J., Goldhaber, D., Jian, Y., . . . Nyholm, T. (2018). Technical note: adapting a GE SIGNA PET/MR scanner for radiotherapy. Medical physics (Lancaster), 45(8), 3546-3550
Open this publication in new window or tab >>Technical note: adapting a GE SIGNA PET/MR scanner for radiotherapy
Show others...
2018 (English)In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 45, no 8, p. 3546-3550Article in journal (Refereed) Published
Abstract [en]

Purpose: Simultaneous collection of PET and MR data for radiotherapy purposes are useful for, for example, target definition and dose escalations. However, a prerequisite for using PET/MR in the radiotherapy workflow is the ability to image the patient in treatment position. The aim of this work was to adapt a GE SIGNA PET/MR scanner to image patients for radiotherapy treatment planning and evaluate the impact on signal-to-noise (SNR) of the MR images, and the accuracy of the PET attenuation correction. Method: A flat tabletop and a coil holder were developed to image patients in the treatment position, avoid patient contour deformation, and facilitate attenuation correction of flex coils. Attenuation corrections for the developed hardware and an anterior array flex coil were also measured and implemented to the PET/MR system to minimize PET quantitation errors. The reduction of SNR in the MR images due to the added distance between the coils and the patient was evaluated using a large homogenous saline-doped water phantom, and the activity quantitation errors in PET imaging were evaluated with and without the developed attenuation corrections. Result: We showed that the activity quantitation errors in PET imaging were within ±5% when correcting for attenuation of the flat tabletop, coil holder, and flex coil. The SNR of the MRI images were reduced to 74% using the tabletop, and 66% using the tabletop and coil holders. Conclusion: We present a tabletop and coil holder for an anterior array coil to be used with a GE SIGNA PET/MR scanner, for scanning patients in the radiotherapy work flow. Implementing attenuation correction of the added hardware from the radiotherapy setup leads to acceptable PET image quantitation. The drop in SNR in MR images may require adjustment of the imaging protocols.

Place, publisher, year, edition, pages
Wiley-Blackwell Publishing Inc., 2018
Keywords
MRI, PET, PET, MR, quality assurance, radiotherapy
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:umu:diva-151405 (URN)10.1002/mp.13032 (DOI)000441292000009 ()29862522 (PubMedID)2-s2.0-85051438748 (Scopus ID)
Funder
Vinnova
Available from: 2018-09-03 Created: 2018-09-03 Last updated: 2024-07-02Bibliographically approved
Organisations

Search in DiVA

Show all publications