Pub Date : 2024-09-06DOI: 10.1101/2024.09.04.24313026
Su Hwan Kim, Severin Schramm, Lisa C. Adams, Rickmer Braren, Keno K. Bressem, Matthias Keicher, Claus Zimmer, Dennis M. Hedderich, Benedikt Wiestler
Background Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages in continuity of access, independence from commercial update cycles, and potentially lower costs.
{"title":"Performance of Open-Source LLMs in Challenging Radiological Cases – A Benchmark Study on 4,049 Eurorad Case Reports","authors":"Su Hwan Kim, Severin Schramm, Lisa C. Adams, Rickmer Braren, Keno K. Bressem, Matthias Keicher, Claus Zimmer, Dennis M. Hedderich, Benedikt Wiestler","doi":"10.1101/2024.09.04.24313026","DOIUrl":"https://doi.org/10.1101/2024.09.04.24313026","url":null,"abstract":"<strong>Background</strong> Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages in continuity of access, independence from commercial update cycles, and potentially lower costs.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1101/2024.09.04.24313070
Chad A. Arledge, Alan H. Zhao, Umit Topaloglu, Dawen Zhao
Dynamic contrast enhanced (DCE) MRI is a non-invasive imaging technique that has become a quantitative standard for assessing tumor microvascular permeability. Through the application of a pharmacokinetic (PK) model to a series of T1-weighed MR images acquired after an injection of a contrast agent, several vascular permeability parameters can be quantitatively estimated. These parameters, including Ktrans, a measure of capillary permeability, have been widely implemented for assessing tumor vascular function as well as tumor therapeutic response. However, conventional PK modeling for translation of DCE MRI to PK vascular permeability parameter maps is complex and time-consuming for dynamic scans with thousands of pixels per image. In recent years, image-to-image conditional generative adversarial network (cGAN) is emerging as a robust approach in computer vision for complex cross-domain translation tasks. Through a sophisticated adversarial training process between two neural networks, image-to-image cGANs learn to effectively translate images from one domain to another, producing images that are indistinguishable from those in the target domain. In the present study, we have developed a novel image-to-image cGAN approach for mapping DCE MRI data to PK vascular permeability parameter maps. The DCE-to-PK cGAN not only generates high-quality parameter maps that closely resemble the ground truth, but also significantly reduces computation time over 1000-fold. The utility of the cGAN approach to map vascular permeability is validated using open-source breast cancer patient DCE MRI data provided by The Cancer Imaging Archive (TCIA). This data collection includes images and pathological analyses of breast cancer patients acquired before and after the first cycle of neoadjuvant chemotherapy (NACT). Importantly, in good agreement with previous studies leveraging this dataset, the percentage change of vascular permeability Ktrans derived from the DCE-to-PK cGAN enables early prediction of responders to NACT.
{"title":"Dynamic Contrast Enhanced MRI Mapping of Vascular Permeability for Evaluation of Breast Cancer Neoadjuvant Chemotherapy Response Using Image-to-Image Conditional Generative Adversarial Networks","authors":"Chad A. Arledge, Alan H. Zhao, Umit Topaloglu, Dawen Zhao","doi":"10.1101/2024.09.04.24313070","DOIUrl":"https://doi.org/10.1101/2024.09.04.24313070","url":null,"abstract":"Dynamic contrast enhanced (DCE) MRI is a non-invasive imaging technique that has become a quantitative standard for assessing tumor microvascular permeability. Through the application of a pharmacokinetic (PK) model to a series of T1-weighed MR images acquired after an injection of a contrast agent, several vascular permeability parameters can be quantitatively estimated. These parameters, including K<sub>trans</sub>, a measure of capillary permeability, have been widely implemented for assessing tumor vascular function as well as tumor therapeutic response. However, conventional PK modeling for translation of DCE MRI to PK vascular permeability parameter maps is complex and time-consuming for dynamic scans with thousands of pixels per image. In recent years, image-to-image conditional generative adversarial network (cGAN) is emerging as a robust approach in computer vision for complex cross-domain translation tasks. Through a sophisticated adversarial training process between two neural networks, image-to-image cGANs learn to effectively translate images from one domain to another, producing images that are indistinguishable from those in the target domain. In the present study, we have developed a novel image-to-image cGAN approach for mapping DCE MRI data to PK vascular permeability parameter maps. The DCE-to-PK cGAN not only generates high-quality parameter maps that closely resemble the ground truth, but also significantly reduces computation time over 1000-fold. The utility of the cGAN approach to map vascular permeability is validated using open-source breast cancer patient DCE MRI data provided by The Cancer Imaging Archive (TCIA). This data collection includes images and pathological analyses of breast cancer patients acquired before and after the first cycle of neoadjuvant chemotherapy (NACT). Importantly, in good agreement with previous studies leveraging this dataset, the percentage change of vascular permeability K<sub>trans</sub> derived from the DCE-to-PK cGAN enables early prediction of responders to NACT.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1101/2024.09.04.24313077
Fanhua Guo, Chenyang Zhao, Qinyang Shou, Ning Jin, Kay Jann, Xingfeng Shao, Danny JJ Wang
Arterial pulsation is crucial for promoting fluid circulation and for influencing neuronal activity. Previous studies assessed the pulsatility index based on blood flow velocity pulsatility in relatively large cerebral arteries of human. Here, we introduce a novel method to quantify the volumetric pulsatility of cerebral microvasculature across cortical layers and in white matter (WM), using high-resolution 4D vascular space occupancy (VASO) MRI with simultaneous recording of pulse signals at 7T. Microvascular volumetric pulsatility index (mvPI) and cerebral blood volume (CBV) changes across cardiac cycles are assessed through retrospective sorting of VASO signals into cardiac phases and estimating mean CBV in resting state (CBV0) by arterial spin labeling (ASL) MRI at 7T. Using data from 11 young (28.4±5.8 years) and 7 older (61.3±6.2 years) healthy participants, we investigated the aging effect on mvPI and compared microvascular pulsatility with large arterial pulsatility assessed by 4D-flow MRI. We observed the highest mvPI in the cerebrospinal fluid (CSF) on the cortical surface (0.19±0.06), which decreased towards the cortical layers as well as in larger arteries. In the deep WM, a significantly increased mvPI (p = 0.029) was observed in the older participants compared to younger ones. Additionally, mvPI in deep WM is significantly associated with the velocity pulsatility index (vePI) of large arteries (r = 0.5997, p = 0.0181). We further performed test-retest scans, non-parametric reliability test and simulations to demonstrate the reproducibility and accuracy of our method. To the best of our knowledge, our method offers the first in vivo measurement of microvascular volumetric pulsatility in human brain which has implications for cerebral microvascular health and its relationship research with glymphatic system, aging and neurodegenerative diseases.
{"title":"Assessing Cerebral Microvascular Volumetric Pulsatility with High-Resolution 4D CBV MRI at 7T","authors":"Fanhua Guo, Chenyang Zhao, Qinyang Shou, Ning Jin, Kay Jann, Xingfeng Shao, Danny JJ Wang","doi":"10.1101/2024.09.04.24313077","DOIUrl":"https://doi.org/10.1101/2024.09.04.24313077","url":null,"abstract":"Arterial pulsation is crucial for promoting fluid circulation and for influencing neuronal activity. Previous studies assessed the pulsatility index based on blood flow velocity pulsatility in relatively large cerebral arteries of human. Here, we introduce a novel method to quantify the volumetric pulsatility of cerebral microvasculature across cortical layers and in white matter (WM), using high-resolution 4D vascular space occupancy (VASO) MRI with simultaneous recording of pulse signals at 7T. Microvascular volumetric pulsatility index (mvPI) and cerebral blood volume (CBV) changes across cardiac cycles are assessed through retrospective sorting of VASO signals into cardiac phases and estimating mean CBV in resting state (CBV0) by arterial spin labeling (ASL) MRI at 7T. Using data from 11 young (28.4±5.8 years) and 7 older (61.3±6.2 years) healthy participants, we investigated the aging effect on mvPI and compared microvascular pulsatility with large arterial pulsatility assessed by 4D-flow MRI. We observed the highest mvPI in the cerebrospinal fluid (CSF) on the cortical surface (0.19±0.06), which decreased towards the cortical layers as well as in larger arteries. In the deep WM, a significantly increased mvPI (p = 0.029) was observed in the older participants compared to younger ones. Additionally, mvPI in deep WM is significantly associated with the velocity pulsatility index (vePI) of large arteries (r = 0.5997, p = 0.0181). We further performed test-retest scans, non-parametric reliability test and simulations to demonstrate the reproducibility and accuracy of our method. To the best of our knowledge, our method offers the first in vivo measurement of microvascular volumetric pulsatility in human brain which has implications for cerebral microvascular health and its relationship research with glymphatic system, aging and neurodegenerative diseases.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"2018 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.1101/2024.09.03.24313024
V Jain, E Hojo, G McKillop, A Oniscu, Y Le, J Chen, R Ehman, N Roberts, HOD Critchley
Introduction Adenomyosis is an under-recognised condition in which definitive diagnosis is only possible via histology after hysterectomy, an unacceptable option for those wishing to preserve fertility. Recent cellular/molecular studies indicate adenomyotic lesions may be fibrotic leading to increased uterine tissue stiffness. 3D Magnetic Resonance Elastography (MRE) is a novel imaging technique that allows in vivo measurement of tissue stiffness (via elastograms). 3D MRE has not been reported to study adenomyosis. The feasibility study aimed to utilise a novel 3D MRE protocol to measure global uterine stiffness and to investigate its potential application for non-invasive in vivo diagnosis of adenomyosis.
{"title":"Feasibility study of the application of Magnetic Resonance Elastography (MRE) to diagnose adenomyosis","authors":"V Jain, E Hojo, G McKillop, A Oniscu, Y Le, J Chen, R Ehman, N Roberts, HOD Critchley","doi":"10.1101/2024.09.03.24313024","DOIUrl":"https://doi.org/10.1101/2024.09.03.24313024","url":null,"abstract":"<strong>Introduction</strong> Adenomyosis is an under-recognised condition in which definitive diagnosis is only possible via histology after hysterectomy, an unacceptable option for those wishing to preserve fertility. Recent cellular/molecular studies indicate adenomyotic lesions may be fibrotic leading to increased uterine tissue stiffness. 3D Magnetic Resonance Elastography (MRE) is a novel imaging technique that allows in vivo measurement of tissue stiffness (via elastograms). 3D MRE has not been reported to study adenomyosis. The feasibility study aimed to utilise a novel 3D MRE protocol to measure global uterine stiffness and to investigate its potential application for non-invasive in vivo diagnosis of adenomyosis.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"311 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-04DOI: 10.1101/2024.09.03.24312925
Louise Denis, Elena Meseguer, Augustin Gaudemer, Georges Jaklh, Sylvain Bodard, Georges Chabouh, Dominique Hervé, Eric Vicaut, Pierre Amarenco, Olivier Couture
Background Deep brain structures are supplied by perforating arteries, these arteries are too thin to be observed with non-invasive and widely available clinical imaging methods. In Moya Moya disease, main arteries in the base of the brain progressively narrowed, and perforating arteries grow densely and tortuously to compensate the lack of blood supply in deep brain structures.
{"title":"Transcranial Ultrasound Localization Microscopy in Moya Moya patients using a clinical ultrasound system","authors":"Louise Denis, Elena Meseguer, Augustin Gaudemer, Georges Jaklh, Sylvain Bodard, Georges Chabouh, Dominique Hervé, Eric Vicaut, Pierre Amarenco, Olivier Couture","doi":"10.1101/2024.09.03.24312925","DOIUrl":"https://doi.org/10.1101/2024.09.03.24312925","url":null,"abstract":"<strong>Background</strong> Deep brain structures are supplied by perforating arteries, these arteries are too thin to be observed with non-invasive and widely available clinical imaging methods. In Moya Moya disease, main arteries in the base of the brain progressively narrowed, and perforating arteries grow densely and tortuously to compensate the lack of blood supply in deep brain structures.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"117 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background Large Language Models (LLMs) show promise in medical diagnosis, but their performance varies with prompting. Recent studies suggest that modifying prompts may enhance diagnostic capabilities.
{"title":"Structured Clinical Reasoning Prompt Enhances LLM’s Diagnostic Capabilities in Diagnosis Please Quiz Cases","authors":"Yuki Sonoda, Ryo Kurokawa, Akifumi Hagiwara, Yusuke Asari, Takahiro Fukushima, Jun Kanzawa, Wataru Gonoi, Osamu Abe","doi":"10.1101/2024.09.01.24312894","DOIUrl":"https://doi.org/10.1101/2024.09.01.24312894","url":null,"abstract":"<strong>Background</strong> Large Language Models (LLMs) show promise in medical diagnosis, but their performance varies with prompting. Recent studies suggest that modifying prompts may enhance diagnostic capabilities.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1101/2024.08.31.24312184
Steven Squires, Grey Kuling, D. Gareth Evans, Anne L. Martel, Susan M. Astley
Purpose Mammographic density is associated with the risk of developing breast cancer and can be predicted using deep learning methods. Model uncertainty estimates are not produced by standard regression approaches but would be valuable for clinical and research purposes. Our objective is to produce deep learning models with in-built uncertainty estimates without degrading predictive performance.
{"title":"Model uncertainty estimates for deep learning mammographic density prediction using ordinal and classification approaches","authors":"Steven Squires, Grey Kuling, D. Gareth Evans, Anne L. Martel, Susan M. Astley","doi":"10.1101/2024.08.31.24312184","DOIUrl":"https://doi.org/10.1101/2024.08.31.24312184","url":null,"abstract":"<strong>Purpose</strong> Mammographic density is associated with the risk of developing breast cancer and can be predicted using deep learning methods. Model uncertainty estimates are not produced by standard regression approaches but would be valuable for clinical and research purposes. Our objective is to produce deep learning models with in-built uncertainty estimates without degrading predictive performance.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-31DOI: 10.1101/2024.08.30.24312867
Kevin J. Chung, Abhijit J. Chaudhari, Lorenzo Nardo, Terry Jones, Moon S. Chen, Ramsey D. Badawi, Simon R. Cherry, Guobao Wang
Quantitative total-body PET imaging of blood flow can be performed with freely diffusible flow radiotracers such as 15O-water and 11C-butanol, but their short half-lives necessitate close access to a cyclotron. Past efforts to measure blood flow with the widely available radiotracer 18F-fluorodeoxyglucose (FDG) were limited to tissues with high 18F-FDG extraction fraction. In this study, we developed an early-dynamic 18F-FDG PET method with high temporal resolution kinetic modeling to assess total-body blood flow based on deriving the vascular transit time of 18F-FDG and conducted a pilot comparison study against a 11C-butanol reference.
{"title":"Quantitative Total-Body Imaging of Blood Flow with High Temporal Resolution Early Dynamic 18F-Fluorodeoxyglucose PET Kinetic Modeling","authors":"Kevin J. Chung, Abhijit J. Chaudhari, Lorenzo Nardo, Terry Jones, Moon S. Chen, Ramsey D. Badawi, Simon R. Cherry, Guobao Wang","doi":"10.1101/2024.08.30.24312867","DOIUrl":"https://doi.org/10.1101/2024.08.30.24312867","url":null,"abstract":"Quantitative total-body PET imaging of blood flow can be performed with freely diffusible flow radiotracers such as <sup>15</sup>O-water and <sup>11</sup>C-butanol, but their short half-lives necessitate close access to a cyclotron. Past efforts to measure blood flow with the widely available radiotracer <sup>18</sup>F-fluorodeoxyglucose (FDG) were limited to tissues with high <sup>18</sup>F-FDG extraction fraction. In this study, we developed an early-dynamic <sup>18</sup>F-FDG PET method with high temporal resolution kinetic modeling to assess total-body blood flow based on deriving the vascular transit time of <sup>18</sup>F-FDG and conducted a pilot comparison study against a <sup>11</sup>C-butanol reference.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-31DOI: 10.1101/2024.08.30.24312851
Yunkun Zhao, Aditya A Bhosale, Xiaoliang Zhang
Background Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities.
{"title":"Coupled stack-up volume RF coils for low-field open MR imaging","authors":"Yunkun Zhao, Aditya A Bhosale, Xiaoliang Zhang","doi":"10.1101/2024.08.30.24312851","DOIUrl":"https://doi.org/10.1101/2024.08.30.24312851","url":null,"abstract":"<strong>Background</strong> Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-30DOI: 10.1101/2024.08.29.24312709
Hassan Sial, Francesc Carandell, Sara Ajanovic, Javier Jiménez, Rita Quesada, Fabião Santos, W. Chris Buck, Muhammad Sidat, UNITED Study Consortium, Quique Bassat, Beatrice Jobst, Paula Petrone
Background Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar punctures (LP), to obtain and analyze cerebrospinal fluid (CSF). Despite being standard practice, LPs are invasive, pose risks for the patient and often yield negative results, either because of the contamination with red blood cells derived from the puncture itself, or due to the disease’s relatively low incidence due to the protocolized requirement to do LPs to discard a life-threatening infection in spite its relatively low incidence. Furthermore, in low-income settings, where the incidence is the highest, LPs and CSF exams are rarely feasible, and suspected meningitis cases are generally treated empirically. There’s a growing need for non-invasive, accurate diagnostic methods.
{"title":"Novel AI-Driven Infant Meningitis Screening from High Resolution Ultrasound Imaging","authors":"Hassan Sial, Francesc Carandell, Sara Ajanovic, Javier Jiménez, Rita Quesada, Fabião Santos, W. Chris Buck, Muhammad Sidat, UNITED Study Consortium, Quique Bassat, Beatrice Jobst, Paula Petrone","doi":"10.1101/2024.08.29.24312709","DOIUrl":"https://doi.org/10.1101/2024.08.29.24312709","url":null,"abstract":"<strong>Background</strong> Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar punctures (LP), to obtain and analyze cerebrospinal fluid (CSF). Despite being standard practice, LPs are invasive, pose risks for the patient and often yield negative results, either because of the contamination with red blood cells derived from the puncture itself, or due to the disease’s relatively low incidence due to the protocolized requirement to do LPs to discard a life-threatening infection in spite its relatively low incidence. Furthermore, in low-income settings, where the incidence is the highest, LPs and CSF exams are rarely feasible, and suspected meningitis cases are generally treated empirically. There’s a growing need for non-invasive, accurate diagnostic methods.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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