Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report

Despite the ever-increasing interest in applying deep learning (DL) models to medical imaging, the typical scarcity and imbalance of medical datasets can severely impact the performance of DL models. The generation of synthetic data that might be freely shared without compromising patient privacy is a well-known technique for addressing these difficulties. Inpainting algorithms are a subset of DL generative models that can alter one or more regions of an input image while matching its surrounding context and, in certain cases, non-imaging input conditions. Although the majority of inpainting techniques for medical imaging data use generative adversarial networks (GANs), the performance of these algorithms is frequently suboptimal due to their limited output variety, a problem that is already well-known for GANs. Denoising diffusion probabilistic models (DDPMs) are a recently introduced family of generative networks that can generate results of comparable quality to GANs, but with diverse outputs. In this paper, we describe a DDPM to execute multiple inpainting tasks on 2D axial slices of brain MRI with various sequences, and present proof-of-concept examples of its performance in a variety of evaluation scenarios. Our model and a public online interface to try our tool are available at: https://github.com/Mayo-Radiology-Informatics-Lab/MBTIComment: 17 pages, 7 figure

Deep-learning for automated detection of MSU deposits on DECT: evaluating impact on efficiency and reader confidence

IntroductionDual-energy CT (DECT) is a non-invasive way to determine the presence of monosodium urate (MSU) crystals in the workup of gout. Color-coding distinguishes MSU from calcium following material decomposition and post-processing. Manually identifying these foci (most commonly labeled green) is tedious, and an automated detection system could streamline the process. This study aims to evaluate the impact of a deep-learning (DL) algorithm developed for detecting green pixelations on DECT on reader time, accuracy, and confidence.MethodsWe collected a sample of positive and negative DECTs, reviewed twice—once with and once without the DL tool—with a 2-week washout period. An attending musculoskeletal radiologist and a fellow separately reviewed the cases, simulating clinical workflow. Metrics such as time taken, confidence in diagnosis, and the tool's helpfulness were recorded and statistically analyzed.ResultsWe included thirty DECTs from different patients. The DL tool significantly reduced the reading time for the trainee radiologist (p = 0.02), but not for the attending radiologist (p = 0.15). Diagnostic confidence remained unchanged for both (p = 0.45). However, the DL model identified tiny MSU deposits that led to a change in diagnosis in two cases for the in-training radiologist and one case for the attending radiologist. In 3/3 of these cases, the diagnosis was correct when using DL.ConclusionsThe implementation of the developed DL model slightly reduced reading time for our less experienced reader and led to improved diagnostic accuracy. There was no statistically significant difference in diagnostic confidence when studies were interpreted without and with the DL model

Table_1_The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis.DOCX

BackgroundMirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients.MethodsWe included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual.ResultsWe included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect.DiscussionThis finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism.Systematic review registrationPROSPERO identifier: CRD42021236453.</p

Table_2_The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis.DOCX

BackgroundMirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients.MethodsWe included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual.ResultsWe included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect.DiscussionThis finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism.Systematic review registrationPROSPERO identifier: CRD42021236453.</p

Data_Sheet_1_The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis.PDF

BackgroundMirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients.MethodsWe included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual.ResultsWe included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect.DiscussionThis finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism.Systematic review registrationPROSPERO identifier: CRD42021236453.</p

Data_Sheet_3_The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis.pdf

BackgroundMirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients.MethodsWe included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual.ResultsWe included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect.DiscussionThis finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism.Systematic review registrationPROSPERO identifier: CRD42021236453.</p

Table_3_The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis.DOCX

BackgroundMirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients.MethodsWe included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual.ResultsWe included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect.DiscussionThis finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism.Systematic review registrationPROSPERO identifier: CRD42021236453.</p

Data_Sheet_2_The mirror mechanism in schizophrenia: A systematic review and qualitative meta-analysis.pdf

BackgroundMirror neuron system (MNS) consists of visuomotor neurons that are responsible for the mirror neuron activity (MNA), meaning that each time an individual observes another individual performing an action, these neurons encode that action, and are activated in the observer's cortical motor system. Previous studies report its malfunction in autism, opening doors to investigate the underlying pathophysiology of the disorder in a more elaborate way and coming up with new rehabilitation methods. The study of MNA function in schizophrenia patients has not been as frequent and conclusive as in autism. In this research, we aimed to evaluate the functional integrity of MNA and the microstructural integrity of MNS in schizophrenia patients.MethodsWe included case-control studies that have evaluated MNA in schizophrenia patients compared to healthy controls using a variety of objective assessment tools. In August 2022, we searched Embase, PubMed, and Web of Science for eligible studies. We used an adapted version of the NIH Quality Assessment of Case-Control Studies tool to assess the quality of the included studies. Evidence was analyzed using vote counting methods of the direction of the effect and was tested statistically using the Sign test. Certainty of evidence was assessed using CERQual.ResultsWe included 32 studies for the analysis. Statistical tests revealed decreased MNA (p = 0.002) in schizophrenia patients. The certainty of the evidence was judged to be moderate. Investigations of heterogeneity revealed a possible relationship between the age and the positive symptoms of participants in the included studies and the direction of the observed effect.DiscussionThis finding contributes to gaining a better understanding of the underlying pathophysiology of the disorder by revealing its possible relation to some of the symptoms in schizophrenia patients, while also highlighting a new commonality with autism.Systematic review registrationPROSPERO identifier: CRD42021236453.</p

Development of a deep learning model for the automated detection of green pixels indicative of gout on dual energy CT scan

Background: Dual-energy CT (DECT) is a non-invasive way to determine the presence of monosodium urate (MSU) crystals in the workup of gout. Color-coding distinguishes MSU from calcium following material decomposition and post-processing. Most software labels MSU as green and calcium as blue. There are limitations in the current image processing methods of segmenting green-encoded pixels. Additionally, identifying green foci is tedious, and automated detection would improve workflow. This study aimed to determine the optimal deep learning (DL) algorithm for segmenting green-encoded pixels of MSU crystals on DECTs. Methods: DECT images of positive and negative gout cases were retrospectively collected. The dataset was split into train (N = 28) and held-out test (N = 30) sets. To perform cross-validation, the train set was split into seven folds. The images were presented to two musculoskeletal radiologists, who independently identified green-encoded voxels. Two 3D Unet-based DL models, Segresnet and SwinUNETR, were trained, and the Dice similarity coefficient (DSC), sensitivity, and specificity were reported as the segmentation metrics. Results: Segresnet showed superior performance, achieving a DSC of 0.9999 for the background pixels, 0.7868 for the green pixels, and an average DSC of 0.8934 for both types of pixels, respectively. According to the post-processed results, the Segresnet reached voxel-level sensitivity and specificity of 98.72 % and 99.98 %, respectively. Conclusion: In this study, we compared two DL-based segmentation approaches for detecting MSU deposits in a DECT dataset. The Segresnet resulted in superior performance metrics. The developed algorithm provides a potential fast, consistent, highly sensitive and specific computer-aided diagnosis tool. Ultimately, such an algorithm could be used by radiologists to streamline DECT workflow and improve accuracy in the detection of gout