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Objective: Idiopathic normal pressure hydrocephalus (INPH) is a treatable neurological condition, yet predicting which patients will benefit from a cerebrospinal fluid shunt remains challenging. Structural brain MRI is a core part of the diagnostic workup, but traditional radiological measures show limited predictive accuracy. This study aimed to assess whether deep learning and radiomics-based machine learning approaches can provide clinically useful predictions of shunt outcome based on preoperative MRI.

Methods: We investigated 149 shunted INPH patients with available preoperative T1-weighted, T2-weighted, and FLAIR images. Patients were classified as responders (n = 113) or non-responders (n = 36) based on postoperative gait speed improvement. For INPH, this is a large sample with typical outcome distribution. Three artificial intelligence approaches were tested: a late-fusion ensemble of multiple 3D convolutional neural networks; a multimodal intermediate fusion model; and radiomics-based machine learning models trained on features extracted from whole-brain masks. Models were assessed using 10-fold cross-validation. The best performing model on the validation set was selected from each approach. Performance metrics included the area under the receiving operating characteristic curve (AUROC), sensitivity, and specificity.

Results: Performance was considered poor in all models, and none reached an area under the receiving operating characteristic curve above 70%. Of the three methodologies, the best performance was achieved with a radiomics-based model (Linear Discriminant Analysis classifier on T1-weighted images) which achieved an AUROC of 63.7%. In a reduced subset of clearly separated responders and non-responders (n = 72), the best model (late fusion ensemble of 5 convolutional neural networks) reached an AUROC of 69.2%.

Conclusions: Despite the use of advanced artificial intelligence techniques, structural MRI alone were insufficient for reliably predicting gait outcome after surgery in idiopathic normal pressure hydrocephalus. To capture the complexity of the condition and enable clinically meaningful predictions, our findings indicate the need for research investigating multimodal input and using large multi-center datasets.

According to glymphatic system theory, cerebrospinal fluid (CSF) perfuses the brain’s interstitial space to support waste clearance, but the magnitude of this flow and the outflow pathway of interstitial fluid (ISF) in humans remain uncertain. To achieve flow quantification, we applied a compartment-model approach applied in conjunction with serial quantitative MRI data acquired after intrathecal gadolinium administration. Using the method, we estimated CSF-to-ISF inflow to 45 ± 20 mL/h, in patients with suspected idiopathic normal pressure hydrocephalus. Tissue-specific contributions were 34 ± 14 mL/h in cortical gray matter, 11±6 mL/h in white matter, and 0.4 ± 0.3 mL/h in subcortical gray matter, suggesting that CSF perfusion occurs primarily in superficial regions near the subarachnoid space. A lack of correlation between inflow and total craniospinal system outflow (r = 0.03, P = 0.91) suggested that ISF recirculates back into CSF rather than exiting the craniospinal system via a separate route. Independent experiments in healthy older individuals using intravenous gadolinium administration supported ISF-to-CSF recirculation, where contrast material that presumably crossed the blood–brain barrier subsequently appeared in the subarachnoid space, allowing ISF-to-CSF flow quantification. These findings provide a quantitative framework for studying brain clearance in humans and support subarachnoid space recirculation as an important efflux route.

Purpose: The aim was to estimate T1 relaxivity of gadobutrol and gadoteric acid in cerebrospinal fluid (CSF) at 3T, to support research on CSF-flow and the glymphatic system in humans utilizing T1 mapping after intrathecal injection.

Methods: Using a phantom, relaxivity was estimated for gadobutrol and gadoteric acid in lumbar CSF and an isotonic solution. All samples were scanned simultaneously using the variable flip angle method with B1 correction, repeated six times on one 3T scanner, and once on a second 3T scanner. Difference in relaxivity between CSF and the isotonic solution were evaluated from the repeated measurements.

Results: There was a significant difference in relaxivity between CSF and the isotonic solution for both gadobutrol and gadoteric acid. The relaxivity for gadobutrol for the respective scanners was estimated to 3.02 ± 0.09 vs. 3.63 L mmol⁻¹ s⁻¹ in CSF and 2.35 ± 0.05 vs. 2.74 L mmol⁻¹ s⁻¹ in isotonic solution. For gadoteric acid, corresponding results were 2.47 ± 0.02 vs. 2.91 L mmol⁻¹ s⁻¹ in CSF and 2.37 ± 0.03 vs. 2.8 L mmol⁻¹ s⁻¹ in isotonic solution. Between the scanners, there was a high correlation (R2 0.998) but an 18% scaling difference in the T1 relaxation rates and corresponding relaxivities.

Conclusions: The relaxivity was higher in CSF than in the isotonic solution, particularly for gadobutrol. Systematic differences in relaxivity between scanners may potentially be corrected using a scaling factor derived from the T1 time of baseline CSF. For CSF studies using T1 mapping with a gadolinium-based contrast agent, we recommend using a CSF-specific relaxivity constant.

Background and purpose: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is a radiological biomarker for idiopathic normal pressure hydrocephalus (iNPH). DESH is a subjective measure, based on visual assessments, which may limit its reliability. The aim of this study was to develop and validate a method for the objective quantification of DESH.

Materials and methods: By using a semiautomatic quantitative method, we calculated quantitative DESH (qDESH), defined as a ratio between CSF volumes at high convexities and Sylvian fissures. The analysis was based on three-dimensional T1-weighted images from 35 subjects with iNPH (mean age 74 yrs; 10 females) and 45 controls (mean age 72 yrs; 13 females). The interrater agreement for qDESH was evaluated by the intraclass correlation coefficient, and qDESH was compared with visual assessments performed by two neuroradiologists.

Results: All subjects with iNPH and 13% of the controls visually scored DESH positive. The median qDESH was 2.48 (5th to 95th percentile 0.88 to 5.42) for iNPH and 0.63 (5th to 95th percentile 0.37 to 1.73) for the controls. The area under the receiver operating characteristic curve for qDESH was 0.95 (95% confidence interval 0.90–1) in separating iNPH patients from controls. The interrater agreement for qDESH was 0.99 (95% CI 0.986–0.994, p < 0.001).

Conclusion: Unlike visual DESH, qDESH generates a continuous variable, enabling reproducible quantification of DESH severity. With this method we can objectively investigate the diagnostic accuracy and prognostic assessment of DESH in iNPH.

Background: Hereditary transthyretin amyloid (ATTRv) is a systemic amyloidosis with mainly neurological and cardiac symptoms. The aim of this study was to evaluate the outcome of [¹⁸F]Flutemetamol PET/CT-scan of the heart in long-term survivors with ATTRV30M amyloidosis.

Methods: Twenty-one patients with ATTRV30M amyloidosis and predominantly neurological symptoms, mainly negative on cardiac ^99mtechnetium-3,3-diphosphono-1,2-propanodicarboxylic acid (DPD)-scintigraphy, were examined with a dynamic [¹⁸F]Flutemetamol PET/CT-scan. Five patients suffering from Alzheimer’s disease and one healthy individual served as controls. Volumes of interests were drawn over the intraventricular septum, lateral wall of the left ventricle and free wall of the right ventricle. Clinical records were reviewed for data from previous completed DPD-scintigraphy of the heart and echocardiography.

Results: Patients with ATTRv amyloidosis had a higher cardiac uptake than the control-group in all analysed regions of the heart and could be identified with high accuracy (sensitivity 88%, specificity 100%) in static image acquisition at 30 or 60 min. We found no correlation between cardiac [¹⁸F]Flutemetamol uptake and clinical variables.

Conclusion: In this small study of selected patients, cardiac [¹⁸F]Flutemetamol PET/CT could differentiate between healthy individuals and patients with ATTRV30M. [¹⁸F]Flutemetamol PET/CT imaging of amyloidosis in patients with a negative DPD-scintigraphy has a potential as a diagnostic method.