Effect of latent space distribution on the segmentation of images with multiple annotations

We propose the Generalized Probabilistic U-Net, which extends the Probabilistic U-Net by allowing more general forms of the Gaussian distribution as the latent space distribution that can better approximate the uncertainty in the reference segmentations. We study the effect the choice of latent space distribution has on capturing the variation in the reference segmentations for lung tumors and white matter hyperintensities in the brain. We show that the choice of distribution affects the sample diversity of the predictions and their overlap with respect to the reference segmentations. We have made our implementation available at https://github.com/ishaanb92/GeneralizedProbabilisticUNetComment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:005. arXiv admin note: text overlap with arXiv:2207.1287

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis

With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of eXplainable Artificial Intelligence (XAI) used in deep learning-based medical image analysis. A framework of XAI criteria is introduced to classify deep learning-based medical image analysis methods. Papers on XAI techniques in medical image analysis are then surveyed and categorized according to the framework and according to anatomical location. The paper concludes with an outlook of future opportunities for XAI in medical image analysis.Comment: Submitted for publication. Comments welcome by email to first autho

Hippocampal T2 hyperintensities on 7Tesla MRI

AbstractHippocampal focal T2 hyperintensities (HT2Hs), also referred to as hippocampal sulcal cavities, are a common finding on Magnetic Resonance (MR) images. There is uncertainty about their etiology and clinical significance. In this study we aimed to describe these HT2Hs in more detail using high resolution 7Tesla MR imaging, addressing 1) the MR signal characteristics of HT2Hs, 2) their occurrence frequency, 3) their location within the hippocampus, and 4) their relation with age. We also performed an explorative post-mortem study to examine the histology of HT2Hs.Fifty-eight persons without a history of invalidating neurological or psychiatric disease (mean age 64±8years; range 43–78years), recruited through their general practitioners, were included in this study. They all underwent 7Tesla MRI, including a T1, T2, and FLAIR image. MR signal characteristics of the HT2Hs were assessed on these images by two raters. Also, the location and number of the HT2Hs were assessed. In addition, four formalin-fixed brain slices from two subjects were scanned overnight. HT2Hs identified in these slices were subjected to histopathological analysis.HT2Hs were present in 97% of the subjects (median number per person 10; range 0–20). All HT2Hs detected on the T2 sequence were hypointense on T1 weighted images. Of all HT2Hs, 94% was hypointense and 6% hyperintense on FLAIR. FLAIR hypointense HT2Hs were all located in the vestigial sulcus of the hippocampus, FLAIR hyperintense HT2Hs in the hippocampal sulcus or the gray matter. Post-mortem MRI and histopathological analysis suggested that the hypointense HT2Hs on FLAIR were cavities filled with cerebrospinal fluid. A hyperintense HT2H on FLAIR proved to be a microinfarct upon microscopy.In conclusion, hippocampal T2Hs are extremely common and unrelated to age. They can be divided into two types (hypo- and hyperintense on FLAIR), probably with different etiology

Temporal Dynamics of Cortical Microinfarcts in Cerebral Small Vessel Disease

Question: What are the cumulative incidence and temporal dynamics of acute cortical microinfarcts? Findings In this cohort study of 54 participants with cerebral small vessel disease who were recruited to undergo 10 monthly 3-T magnetic resonance imaging (MRI) scans, including high-resolution diffusion-weighted imaging, 21 acute cortical microinfarcts were observed in 7 of 54 participants (13%). All acute cortical microinfarcts disappeared on follow-up MRI. Meaning We show that incident acute cortical microinfarcts never evolved into chronically MRI-detectable lesions and suggest that these acute microinfarcts underlie part of the submillimeter cortical microinfarcts visible only on neuropathology, thereby providing a source for the high microinfarct burden encountered on neuropathology. Importance Neuropathology studies show a high prevalence of cortical microinfarcts (CMIs) in aging individuals, especially in patients with cerebrovascular disease and dementia. However, most, are invisible on T1- and T2-weighted magnetic resonance imaging (MRI), raising the question of how to explain this mismatch. Studies on small acute infarcts, detected on diffusion-weighted imaging (DWI), suggest that infarcts are largest in their acute phase and reduce in size thereafter. Therefore, we hypothesized that a subset of the CMI that are invisible on MRI can be detected on MRI in their acute phase. However, to our knowledge, a serial imaging study investigating the temporal dynamics of acute CMI (A-CMI) is lacking. Objective: To determine the prevalence of chronic CMI (C-CMI) and the cumulative incidence and temporal dynamics of A-CMI in individuals with cerebral small vessel disease (SVD). Design, Setting, Participants and Exposures The RUN DMC-Intense study is a single-center hospital-based prospective cohort study on SVD performed between March 2016 and November 2017 and comprising 10 monthly 3-T MRI scans, including high-resolution DWI, 3-dimensional T1, 3-dimensional fluid-attenuated inversion recovery, and T2. One hundred six individuals from the previous longitudinal RUN DMC study were recruited based on the presence of progression of white matter hyperintensities on MRI between 2006 and 2015 and exclusion of causes of cerebral ischemia other than SVD. Fifty-four individuals (50.9%) participated. The median total follow-up duration was 39.5 weeks (interquartile range, 37.8-40.3). Statistical data analysis was performed between May and October 2019. Main Outcomes and Measures: We determined the prevalence of C-CMI using the baseline T1, fluid-attenuated inversion recovery, and T2 scans. Monthly high-resolution DWI scans (n = 472) were screened to determine the cumulative incidence of A-CMI. The temporal dynamics of A-CMI were determined based on the MRI scans collected during the first follow-up visit after A-CMI onset and the last available follow-up visit. Results The median age of the cohort at baseline MRI was 69 years (interquartile range, 66-74 years) and 34 participants (63%) were men. The prevalence of C-CMI was 35% (95% CI, 0.24-0.49). Monthly DWI detected 21 A-CMI in 7 of 54 participants, resulting in a cumulative incidence of 13% (95% CI, 0.06-0.24). All A-CMI disappeared on follow-up MRI. Conclusions and Relevance: Acute CMI never evolved into chronically MRI-detectable lesions. We suggest that these A-CMI underlie part of the submillimeter C-CMI encountered on neuropathological examination and thereby provide a source for the high CMI burden on neuropathology. This cohort study examines the prevalence of chronic cortical microinfarcts and the cumulative incidence and temporal dynamics of acute cortical microinfarcts in Finnish individuals with cerebral small vessel disease

The Impact of Strategic White Matter Hyperintensity Lesion Location on Language

Objective: The impact of white matter hyperintensities (WMH) on language possibly depends on lesion location through disturbance of strategic white matter tracts. We examined the impact of WMH location on language in elderly Asians. Design: Cross-sectional. Setting: Population-based. Participants: Eight-hundred nineteen residents of Singapore, ages (≥65 years). Measurements: Clinical, cognitive and 3T magnetic resonance imaging assessments were performed on all participants. Language was assessed using the Modified Boston Naming Test (MBNT) and Verbal Fluency (VF). Hypothesis-free region-of-interest-based (ROI) analyses based on major white matter tracts were used to determine the association between WMH location and language. Conditional dependencies between the regional WMH volumes and language were examined using Bayesian-network analysis. Results: ROI-based analyses showed that WMH located within the anterior thalamic radiation (mean difference: −0.12, 95% confidence interval [CI]: −0.22; −0.02, p = 0.019) and uncinate fasciculus (mean difference: −0.09, 95% CI: −0.18; −0.01, p = 0.022) in the left hemisphere were significantly associated with worse VF but did not survive multiple testing. Conversely, WMH volume in the left cingulum of cingulate gyrus was significantly associated with MBNT performance (mean difference: −0.09, 95% CI: −0.17; −0.02, p = 0.016). Bayesian-network analyses confirmed the left cingulum of cingulate gyrus as a direct determinant of MBNT performance. Conclusion: Our findings identify the left cingulum of cingulate gyrus as a strategic white matter tract for MBNT, suggesting that language – is sensitive to subcortical ischemic damage. Future studies on the role of sporadic ischemic lesions and vascular cognitive impairment should not only focus on total WMH volume but should also take WMH lesion location into account when addressing language