Pub Date : 2024-08-01DOI: 10.1101/2024.07.30.24311094
Amanda Craine, Anderson Scott, Dhruvi Desai, Seth Kligerman, Eric D. Adler, Nick Kim, Laith Alshawabkeh, Francisco J Contijoch
Background: Regional myocardial work (MW) is not measured in the right ventricle (RV) due to a lack of high spatial resolution regional strain (RS) estimates throughout the ventricle. We present a cineCT-based approach to evaluate regional RV performance and demonstrate its ability to phenotype three complex populations: end-stage LV failure (HF), chronic thromboembolic pulmonary hypertension (CTEPH), and repaired tetralogy of Fallot (rTOF). Methods: 49 patients (19 HF, 11 CTEPH, 19 rTOF) underwent cineCT and right heart catheterization (RHC). RS was estimated from full-cycle ECG-gated cineCT and combined with RHC pressure waveforms to create regional pressure-strain loops; endocardial MW was measured as the loop area. Detailed, 3D mapping of RS and MW enabled spatial visualization of strain and work strength, and phenotyping of patients. Results: HF patients demonstrated more overall impaired strain and work compared to the CTEPH and rTOF cohorts. For example, the HF patients had more akinetic areas (median: 9%) than CTEPH (median: <1%, p=0.02) and rTOF (median: 1%, p<0.01) and performed more low work (median: 69%) than the rTOF cohort (median: 38%, p<0.01). The CTEPH cohort had more impairment in the septal wall; <1% of the free wall and 16% of the septal wall performed negative work. The rTOF cohort demonstrated a wide distribution of strain and work, ranging from hypokinetic to hyperkinetic strain and low to medium-high work. Impaired strain (-0.15<=RS) and negative work were strongly-to-very strongly correlated with RVEF (R=-0.89, p<0.01; R=-0.70, p<0.01 respectively), while impaired work (MW<=5 mmHg) was moderately correlated with RVEF (R=-0.53, p<0.01). Conclusions: Regional RV MW maps can be derived from clinical CT and RHC studies and can provide patient-specific phenotyping of RV function in complex heart disease patients.
{"title":"3D Regional Evaluation of Right Ventricular Myocardial Work from cineCT","authors":"Amanda Craine, Anderson Scott, Dhruvi Desai, Seth Kligerman, Eric D. Adler, Nick Kim, Laith Alshawabkeh, Francisco J Contijoch","doi":"10.1101/2024.07.30.24311094","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311094","url":null,"abstract":"Background: Regional myocardial work (MW) is not measured in the right ventricle (RV) due to a lack of high spatial resolution regional strain (RS) estimates throughout the ventricle. We present a cineCT-based approach to evaluate regional RV performance and demonstrate its ability to phenotype three complex populations: end-stage LV failure (HF), chronic thromboembolic pulmonary hypertension (CTEPH), and repaired tetralogy of Fallot (rTOF). Methods: 49 patients (19 HF, 11 CTEPH, 19 rTOF) underwent cineCT and right heart catheterization (RHC). RS was estimated from full-cycle ECG-gated cineCT and combined with RHC pressure waveforms to create regional pressure-strain loops; endocardial MW was measured as the loop area. Detailed, 3D mapping of RS and MW enabled spatial visualization of strain and work strength, and phenotyping of patients. Results: HF patients demonstrated more overall impaired strain and work compared to the CTEPH and rTOF cohorts. For example, the HF patients had more akinetic areas (median: 9%) than CTEPH (median: <1%, p=0.02) and rTOF (median: 1%, p<0.01) and performed more low work (median: 69%) than the rTOF cohort (median: 38%, p<0.01). The CTEPH cohort had more impairment in the septal wall; <1% of the free wall and 16% of the septal wall performed negative work. The rTOF cohort demonstrated a wide distribution of strain and work, ranging from hypokinetic to hyperkinetic strain and low to medium-high work. Impaired strain (-0.15<=RS) and negative work were strongly-to-very strongly correlated with RVEF (R=-0.89, p<0.01; R=-0.70, p<0.01 respectively), while impaired work (MW<=5 mmHg) was moderately correlated with RVEF (R=-0.53, p<0.01). Conclusions: Regional RV MW maps can be derived from clinical CT and RHC studies and can provide patient-specific phenotyping of RV function in complex heart disease patients.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868492","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 : 2024-08-01DOI: 10.1101/2024.07.30.24311224
Jirong Yi, Anna M Michalowska, Aakash Shanbhag, Robert Miller, Jolien Geers, Wenhao Zhang, Aditya Killekar, Nipun Manral, Mark Lemley, Mikolaj Buchwald, Jacek Kwiecinski, Jianhang Zhou, Paul Kavanagh, Joanna Liang, Valerie Builoff, Terrence Ruddy, Andrew J. Einstein, Attila Feher, Edward J Miller, Albert Sinusas, Daniel Berman, Damini Dey, Piotr Slomka
Background: Computed tomography attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only utilized for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-based approach to obtain volumetric measurements of chest body composition from CTAC scans and evaluate these measures for all-cause mortality (ACM) risk stratification. Methods: We applied AI-based segmentation and image-processing techniques on CTAC scans from a large international image-based registry (four sites), to define chest rib cage and multiple tissues. Volumetric measures of bone, skeletal muscle (SM), subcutaneous, intramuscular (IMAT), visceral (VAT), and epicardial (EAT) adipose tissues were quantified between automatically-identified T5 and T11 vertebrae. The independent prognostic value of volumetric attenuation, and indexed volumes were evaluated for predicting ACM, adjusting for established risk factors and 18 other body compositions measures via Cox regression models and Kaplan-Meier curves. Findings: End-to-end processing time was <2 minutes/scan with no user interaction. Of 9918 patients studied, 5451(55%) were male. During median 2.5 years follow-up, 610 (6.2%) patients died. High VAT, EAT and IMAT attenuation were associated with increased ACM risk (adjusted hazard ratio (HR) [95% confidence interval] for VAT: 2.39 [1.92, 2.96], p<0.0001; EAT: 1.55 [1.26, 1.90], p<0.0001; IMAT: 1.30 [1.06, 1.60], p=0.0124). Patients with high bone attenuation were at lower risk of death as compared to subjects with lower bone attenuation (adjusted HR 0.77 [0.62, 0.95], p=0.0159). Likewise, high SM volume index was associated with a lower risk of death (adjusted HR 0.56 [0.44, 0.71], p<0.0001). Interpretations: CTAC scans obtained routinely during cardiac perfusion imaging contain important volumetric body composition biomarkers which can be automatically measured and offer important additional prognostic value.
{"title":"AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans enhances mortality prediction: multicenter study","authors":"Jirong Yi, Anna M Michalowska, Aakash Shanbhag, Robert Miller, Jolien Geers, Wenhao Zhang, Aditya Killekar, Nipun Manral, Mark Lemley, Mikolaj Buchwald, Jacek Kwiecinski, Jianhang Zhou, Paul Kavanagh, Joanna Liang, Valerie Builoff, Terrence Ruddy, Andrew J. Einstein, Attila Feher, Edward J Miller, Albert Sinusas, Daniel Berman, Damini Dey, Piotr Slomka","doi":"10.1101/2024.07.30.24311224","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311224","url":null,"abstract":"Background: Computed tomography attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only utilized for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-based approach to obtain volumetric measurements of chest body composition from CTAC scans and evaluate these measures for all-cause mortality (ACM) risk stratification. Methods: We applied AI-based segmentation and image-processing techniques on CTAC scans from a large international image-based registry (four sites), to define chest rib cage and multiple tissues. Volumetric measures of bone, skeletal muscle (SM), subcutaneous, intramuscular (IMAT), visceral (VAT), and epicardial (EAT) adipose tissues were quantified between automatically-identified T5 and T11 vertebrae. The independent prognostic value of volumetric attenuation, and indexed volumes were evaluated for predicting ACM, adjusting for established risk factors and 18 other body compositions measures via Cox regression models and Kaplan-Meier curves.\u0000Findings: End-to-end processing time was <2 minutes/scan with no user interaction. Of 9918 patients studied, 5451(55%) were male. During median 2.5 years follow-up, 610 (6.2%) patients died. High VAT, EAT and IMAT attenuation were associated with increased ACM risk (adjusted hazard ratio (HR) [95% confidence interval] for VAT: 2.39 [1.92, 2.96], p<0.0001; EAT: 1.55 [1.26, 1.90], p<0.0001; IMAT: 1.30 [1.06, 1.60], p=0.0124). Patients with high bone attenuation were at lower risk of death as compared to subjects with lower bone attenuation (adjusted HR 0.77 [0.62, 0.95], p=0.0159). Likewise, high SM volume index was associated with a lower risk of death (adjusted HR 0.56 [0.44, 0.71], p<0.0001).\u0000Interpretations: CTAC scans obtained routinely during cardiac perfusion imaging contain important volumetric body composition biomarkers which can be automatically measured and offer important additional prognostic value.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868493","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 : 2024-07-27DOI: 10.1101/2024.07.26.24311027
Kevin J. Chung, Yasser G. Abdelhafez, Benjamin A. Spencer, Terry Jones, Quyen Tran, Lorenzo Nardo, Moon S. Chen, Souvik Sarkar, Valentina Medici, Victoria Lyo, Ramsey D. Badawi, Simon R. Cherry, Guobao Wang
Blood-brain barrier (BBB) disruption is involved in the pathogenesis and progression of many neurological and systemic diseases. Non-invasive assessment of BBB permeability in humans has mainly been performed with dynamic contrast-enhanced magnetic resonance imaging, evaluating the BBB as a structural barrier. Here, we developed a novel non-invasive positron emission tomography (PET) method in humans to measure the BBB permeability of molecular radiotracers that cross the BBB through different transport mechanisms. Our method uses high-temporal resolution dynamic imaging and kinetic modeling to jointly estimate cerebral blood flow and tracer-specific BBB transport rate from a single dynamic PET scan and measure the molecular permeability-surface area (PS) product of the radiotracer. We show our method can resolve BBB PS across three PET radiotracers with greatly differing permeabilities, measure reductions in BBB PS of 18F-fluorodeoxyglucose (FDG) in healthy aging, and demonstrate a possible brain-body association between decreased FDG BBB PS in patients with metabolic dysfunction-associated steatotic liver inflammation. Our method opens new directions to efficiently study the molecular permeability of the human BBB in vivo using the large catalogue of available molecular PET tracers.
{"title":"Quantitative PET imaging and modeling of molecular blood-brain barrier permeability","authors":"Kevin J. Chung, Yasser G. Abdelhafez, Benjamin A. Spencer, Terry Jones, Quyen Tran, Lorenzo Nardo, Moon S. Chen, Souvik Sarkar, Valentina Medici, Victoria Lyo, Ramsey D. Badawi, Simon R. Cherry, Guobao Wang","doi":"10.1101/2024.07.26.24311027","DOIUrl":"https://doi.org/10.1101/2024.07.26.24311027","url":null,"abstract":"Blood-brain barrier (BBB) disruption is involved in the pathogenesis and progression of many neurological and systemic diseases. Non-invasive assessment of BBB permeability in humans has mainly been performed with dynamic contrast-enhanced magnetic resonance imaging, evaluating the BBB as a structural barrier. Here, we developed a novel non-invasive positron emission tomography (PET) method in humans to measure the BBB permeability of molecular radiotracers that cross the BBB through different transport mechanisms. Our method uses high-temporal resolution dynamic imaging and kinetic modeling to jointly estimate cerebral blood flow and tracer-specific BBB transport rate from a single dynamic PET scan and measure the molecular permeability-surface area (PS) product of the radiotracer. We show our method can resolve BBB PS across three PET radiotracers with greatly differing permeabilities, measure reductions in BBB PS of <sup>18</sup>F-fluorodeoxyglucose (FDG) in healthy aging, and demonstrate a possible brain-body association between decreased FDG BBB PS in patients with metabolic dysfunction-associated steatotic liver inflammation. Our method opens new directions to efficiently study the molecular permeability of the human BBB in vivo using the large catalogue of available molecular PET tracers.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141773041","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 : 2024-07-24DOI: 10.1101/2024.07.24.24310920
Josef Lorenz Rumberger, Winna Lim, Benjamin Wildfeuer, Elisa Birgit Sodemann, Augustin Lecler, Simon Stemplinger, Ahi-Sema Issever, Ali Sepahdari, Soenke Langner, Dagmar Kainmueller, Bernd Hamm, Katharina Erg-Eigner
Background: Diagnoses of eye and orbit pathologies by radiological imaging is challenging due to their low prevalence and the relative high number of possible pathologies and variability in presentation, thus requiring substantial domain-specific experience. Purpose: This study investigates whether a content-based image retrieval (CBIR) tool paired with a curated database of orbital MRI cases with verified diagnoses can enhance diagnostic accuracy and reduce reading time for radiologists across different experience levels. Material and Methods: We tested these two hypotheses in a multi-reader, multi-case study, with 36 readers and 48 retrospective eye and orbit MRI cases. We asked each reader to diagnose eight orbital MRI cases, four while having only status quo reference tools available (e.g. Radiopaedia.org, StatDx, etc.), and four while having a CBIR reference tool additionally available. Then, we analyzed and compared the results with linear mixed effects models, controlling for the cases and participants. Results: Overall, we found a strong positive effect on diagnostic accuracy when using the CBIR tool only as compared to using status quo tools only (status quo only 55.88%, CBIR only 70.59%, 26.32% relative improvement, p=.03, odds ratio=2.07), and an even stronger effect when using the CBIR tool in conjunction with status quo tools (status quo only 55.88%, CBIR + status quo 83.33%, 49% relative improvement, p=.02, odds ratio=3.65). Reading time in seconds (s) decreased when using only the CBIR tool (status quo only 334s, CBIR only 236s, 29% decrease, p<.001), but increased when used in conjunction with status quo tools (status quo only 334s, CBIR + status quo 396s, 19% increase, p<.001). Conclusion: We found significant positive effects on diagnostic accuracy and mixed effects on reading times when using the CBIR reference tool, indicating the potential benefits when using CBIR reference tools in diagnosing eye and orbit mass lesions by radiological imaging.
{"title":"Content-based image retrieval assists radiologists in diagnosing eye and orbital mass lesions in MRI","authors":"Josef Lorenz Rumberger, Winna Lim, Benjamin Wildfeuer, Elisa Birgit Sodemann, Augustin Lecler, Simon Stemplinger, Ahi-Sema Issever, Ali Sepahdari, Soenke Langner, Dagmar Kainmueller, Bernd Hamm, Katharina Erg-Eigner","doi":"10.1101/2024.07.24.24310920","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310920","url":null,"abstract":"Background:\u0000Diagnoses of eye and orbit pathologies by radiological imaging is challenging due to their low prevalence and the relative high number of possible pathologies and variability in presentation, thus requiring substantial domain-specific experience.\u0000Purpose:\u0000This study investigates whether a content-based image retrieval (CBIR) tool paired with a curated database of orbital MRI cases with verified diagnoses can enhance diagnostic accuracy and reduce reading time for radiologists across different experience levels.\u0000Material and Methods:\u0000We tested these two hypotheses in a multi-reader, multi-case study, with 36 readers and 48 retrospective eye and orbit MRI cases. We asked each reader to diagnose eight orbital MRI cases, four while having only status quo reference tools available (e.g. Radiopaedia.org, StatDx, etc.), and four while having a CBIR reference tool additionally available. Then, we analyzed and compared the results with linear mixed effects models, controlling for the cases and participants.\u0000Results:\u0000Overall, we found a strong positive effect on diagnostic accuracy when using the CBIR tool only as compared to using status quo tools only (status quo only 55.88%, CBIR only 70.59%, 26.32% relative improvement, p=.03, odds ratio=2.07), and an even stronger effect when using the CBIR tool in conjunction with status quo tools (status quo only 55.88%, CBIR + status quo 83.33%, 49% relative improvement, p=.02, odds ratio=3.65). Reading time in seconds (s) decreased when using only the CBIR tool (status quo only 334s, CBIR only 236s, 29% decrease, p<.001), but increased when used in conjunction with status quo tools (status quo only 334s, CBIR + status quo 396s, 19% increase, p<.001). Conclusion:\u0000We found significant positive effects on diagnostic accuracy and mixed effects on reading times when using the CBIR reference tool, indicating the potential benefits when using CBIR reference tools in diagnosing eye and orbit mass lesions by radiological imaging.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141773042","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 : 2024-07-24DOI: 10.1101/2024.07.23.24310903
Nicholas A White, Aart J van der Molen, Ronald WAL Limpens, Jacinta Maas, Koen EA van der Bogt, Tim Horeman, Joris I. Rotmans
Background: Central venous catheters (CVCs) provide direct access to the central circulatory system, commonly used in hemodialysis and intensive care units for drug administration. Although uncertified for the procedure, CVCs are sometimes used for power injection of contrast medium (CM) during CT scans to avoid peripheral intravenous catheter placement. Previous studies suggest this practice is safe, but incidents have been reported. This study aims to measure intraluminal pressure during CM injection through CVCs and assess its impact on the luminal surface to guide responsible clinical use. Methods: Strain gauges were applied to the exterior walls of four samples from three different types of unused CVCs. These gauges measured material deformation due to intraluminal pressure during CM injections at rates of 4.5 mL/s and 8 mL/s, each performed five times. Strain data were calibrated against known pressures in a static system. The CVCs were then either pressurized until bursting or subjected to microscopic analysis of their luminal surfaces. Results: Intraluminal pressures measured (97-545 kPa or 14-79 PSI) were below the burst pressure (779-1248 Kpa or 113-181 PSI) in all instances. Strain regression analysis shows a statistically significant (p<0.05) trend over 10 injections in almost all CVCs tested, indicating material fatigue. Surface microscopy revealed surface micro-cracks from repeated injections, suggesting material damage. Conclusions: The intraluminal pressures from power injections of CM are sufficiently low to prevent CVC bursting. While incidental use for CM injection appears safe, repeated use may cause material damage?
{"title":"Intraluminal pressure in central venous hemodialysis catheters during power injection of contrast media","authors":"Nicholas A White, Aart J van der Molen, Ronald WAL Limpens, Jacinta Maas, Koen EA van der Bogt, Tim Horeman, Joris I. Rotmans","doi":"10.1101/2024.07.23.24310903","DOIUrl":"https://doi.org/10.1101/2024.07.23.24310903","url":null,"abstract":"Background:\u0000Central venous catheters (CVCs) provide direct access to the central circulatory system, commonly used in hemodialysis and intensive care units for drug administration. Although uncertified for the procedure, CVCs are sometimes used for power injection of contrast medium (CM) during CT scans to avoid peripheral intravenous catheter placement. Previous studies suggest this practice is safe, but incidents have been reported. This study aims to measure intraluminal pressure during CM injection through CVCs and assess its impact on the luminal surface to guide responsible clinical use.\u0000Methods:\u0000Strain gauges were applied to the exterior walls of four samples from three different types of unused CVCs. These gauges measured material deformation due to intraluminal pressure during CM injections at rates of 4.5 mL/s and 8 mL/s, each performed five times. Strain data were calibrated against known pressures in a static system. The CVCs were then either pressurized until bursting or subjected to microscopic analysis of their luminal surfaces.\u0000Results:\u0000Intraluminal pressures measured (97-545 kPa or 14-79 PSI) were below the burst pressure (779-1248 Kpa or 113-181 PSI) in all instances. Strain regression analysis shows a statistically significant (p<0.05) trend over 10 injections in almost all CVCs tested, indicating material fatigue. Surface microscopy revealed surface micro-cracks from repeated injections, suggesting material damage.\u0000Conclusions:\u0000The intraluminal pressures from power injections of CM are sufficiently low to prevent CVC bursting. While incidental use for CM injection appears safe, repeated use may cause material damage?","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141773043","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 : 2024-07-22DOI: 10.1101/2024.07.21.24310778
Alfredo Lucas, Marc Jaskir, Nishant Sinha, Akash Ranjan Pattnaik, Sofia Mouchtaris, Mariam Josyula, Nina Petillo, Rebecca Roth, Gulce N. Dikecligil, Leonardo Bonilha, Jay Gottfried, Ezequiel Gleichgerrcht, Sandhitsu Das, Joel M. Stein, James J. Gugger, Kathryn A. Davis
Background: The piriform cortex has been implicated in the initiation, spread and termination of epileptic seizures. This understanding has extended to surgical management of epilepsy, where it has been shown that resection or ablation of the piriform cortex can result in better outcomes. How and why the piriform cortex may play such a crucial role in seizure networks is not well understood. To answer these questions, we investigated the functional and structural connectivity of the piriform cortex in both healthy controls and temporal lobe epilepsy (TLE) patients. Methods: We studied a retrospective cohort of 55 drug-resistant unilateral TLE patients and 26 healthy controls who received structural and functional neuroimaging. Using seed-to-voxel connectivity we compared the normative whole-brain connectivity of the piriform to that of the hippocampus, a region commonly involved in epilepsy, to understand the differential contribution of the piriform to the epileptogenic network. We subsequently measured the inter-piriform coupling (IPC) to quantify similarities in the inter-hemispheric cortical functional connectivity profile between the two piriform cortices. We related differences in IPC in TLE back to aberrations in normative piriform connectivity, whole brain functional properties, and structural connectivity. Results: We find that relative to the hippocampus, the piriform is functionally connected to the anterior insula and the rest of the salience ventral attention network (SAN). We also find that low IPC is a sensitive metric of poor surgical outcome (sensitivity: 85.71%, 95% CI: [19.12%, 99.64%]); and differences in IPC within TLE were related to disconnectivity and hyperconnectivity to the anterior insula and the SAN. More globally, we find that low IPC is associated with whole-brain functional and structural segregation, marked by decreased functional small-worldness and fractional anisotropy. Conclusions: Our study presents novel insights into the functional and structural neural network alterations associated with this structure, laying the foundation for future work to carefully consider its connectivity during the presurgical management of epilepsy.
背景：梨状皮质与癫痫发作的诱发、扩散和终止有关。这种认识已延伸到癫痫的外科治疗中，有研究表明，切除或消融梨状皮层可获得更好的疗效。人们对梨状皮层如何以及为何在癫痫发作网络中发挥如此关键的作用还不甚了解。为了回答这些问题，我们研究了健康对照组和颞叶癫痫（TLE）患者梨状皮层的功能和结构连接性。研究方法我们对 55 名单侧耐药性 TLE 患者和 26 名健康对照者进行了回顾性队列研究，他们都接受了结构和功能神经影像学检查。通过种子到象素的连接性，我们比较了梨状体与海马（癫痫常见区域）的正常全脑连接性，以了解梨状体对致痫网络的不同贡献。我们随后测量了梨状皮层间的耦合（IPC），以量化两个梨状皮层之间大脑半球间皮层功能连接的相似性。我们将 TLE 中 IPC 的差异与正常梨状连接、全脑功能特性和结构连接的异常联系起来。结果：我们发现，相对于海马，梨状皮层与前脑岛和突出腹侧注意网络（SAN）的其他部分有功能连接。我们还发现，低 IPC 是手术效果不佳的敏感指标（敏感度：85.71%，95% CI：[19.12%, 99.64%]）；TLE 中 IPC 的差异与与前脑岛和 SAN 的断开连接和超连接有关。更全面地说，我们发现低 IPC 与全脑功能和结构分隔有关，其特征是功能小世界性和分数各向异性降低。结论：我们的研究对与该结构相关的功能和结构神经网络改变提出了新的见解，为今后在癫痫手术前管理中仔细考虑其连接性奠定了基础。
{"title":"Connectivity of the Piriform Cortex and its Implications in Temporal Lobe Epilepsy","authors":"Alfredo Lucas, Marc Jaskir, Nishant Sinha, Akash Ranjan Pattnaik, Sofia Mouchtaris, Mariam Josyula, Nina Petillo, Rebecca Roth, Gulce N. Dikecligil, Leonardo Bonilha, Jay Gottfried, Ezequiel Gleichgerrcht, Sandhitsu Das, Joel M. Stein, James J. Gugger, Kathryn A. Davis","doi":"10.1101/2024.07.21.24310778","DOIUrl":"https://doi.org/10.1101/2024.07.21.24310778","url":null,"abstract":"<strong>Background:</strong> The piriform cortex has been implicated in the initiation, spread and termination of epileptic seizures. This understanding has extended to surgical management of epilepsy, where it has been shown that resection or ablation of the piriform cortex can result in better outcomes. How and why the piriform cortex may play such a crucial role in seizure networks is not well understood. To answer these questions, we investigated the functional and structural connectivity of the piriform cortex in both healthy controls and temporal lobe epilepsy (TLE) patients. <strong>Methods:</strong> We studied a retrospective cohort of 55 drug-resistant unilateral TLE patients and 26 healthy controls who received structural and functional neuroimaging. Using seed-to-voxel connectivity we compared the normative whole-brain connectivity of the piriform to that of the hippocampus, a region commonly involved in epilepsy, to understand the differential contribution of the piriform to the epileptogenic network. We subsequently measured the inter-piriform coupling (IPC) to quantify similarities in the inter-hemispheric cortical functional connectivity profile between the two piriform cortices. We related differences in IPC in TLE back to aberrations in normative piriform connectivity, whole brain functional properties, and structural connectivity. <strong>Results:</strong> We find that relative to the hippocampus, the piriform is functionally connected to the anterior insula and the rest of the salience ventral attention network (SAN). We also find that low IPC is a sensitive metric of poor surgical outcome (sensitivity: 85.71%, 95% CI: [19.12%, 99.64%]); and differences in IPC within TLE were related to disconnectivity and hyperconnectivity to the anterior insula and the SAN. More globally, we find that low IPC is associated with whole-brain functional and structural segregation, marked by decreased functional small-worldness and fractional anisotropy. <strong>Conclusions:</strong> Our study presents novel insights into the functional and structural neural network alterations associated with this structure, laying the foundation for future work to carefully consider its connectivity during the presurgical management of epilepsy.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141773044","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 : 2024-07-21DOI: 10.1101/2024.07.20.24310708
Ruta Virsinskaite, James T. Brown, Tushar Kotecha, Darren Bower, Jennifer A. Steeden, Javier Montalt-Tordera, Olivier Jaubert, Marianna Fontana, J. Gerry Coghlan, Daniel S. Knight, Vivek Muthurangu
Introduction The value of exercise cardiovascular magnetic resonance (CMR) has been shown in many clinical scenarios. We have developed a MR-compatible exercise apparatus and aim to validate it against the reference standard MR-conventional ergometer. Methods The novel device consisted of two half-pipes fixed to a wooden base, with participants wearing knee-length socks with a 0.5kg weight in each sock. Increased workload was achieved by increasing the rate of alternating leg flexion and extension in time with a bleep sound of increasing frequency. Twenty subjects (10 healthy volunteers, 10 patients with pulmonary hypertension) performed two CMR-augmented cardiopulmonary exercise tests (CMR-CPET) using the novel exercise apparatus and a conventional ergometer in a randomised order. Results Comparing peak metrics elicited on both exercise devices, there was a moderate correlation in peak oxygen consumption (VO2, r=0.86, P<0.001), cardiac output (CO, r=0.66, P=0.002), stroke volume (SV, r=0.75, P<0.001), peak heart rate (HR, r=0.65, P=0.002) and peak arteriovenous oxygen content gradient (△avO2, r=0.71, P<0.001). However, all metrics (except peak SV) were significantly lower from the novel device. Both devices were able to elicit statistically significant differences in VO2, HR and RVEF between patients and healthy subjects (P≤0.036). Conclusions We have created a simple, easy to use and affordable exercise apparatus for CMR environment. This may encourage greater dissemination of exercise CMR in clinical and research practice. Keywords: exercise CMR device, pulmonary hypertension, systemic sclerosis
{"title":"Validation of a novel, low-cost, portable MRI-compatible exercise device in healthy volunteers and patients with pulmonary hypertension","authors":"Ruta Virsinskaite, James T. Brown, Tushar Kotecha, Darren Bower, Jennifer A. Steeden, Javier Montalt-Tordera, Olivier Jaubert, Marianna Fontana, J. Gerry Coghlan, Daniel S. Knight, Vivek Muthurangu","doi":"10.1101/2024.07.20.24310708","DOIUrl":"https://doi.org/10.1101/2024.07.20.24310708","url":null,"abstract":"Introduction The value of exercise cardiovascular magnetic resonance (CMR) has been shown in many clinical scenarios. We have developed a MR-compatible exercise apparatus and aim to validate it against the reference standard MR-conventional ergometer. Methods The novel device consisted of two half-pipes fixed to a wooden base, with participants wearing knee-length socks with a 0.5kg weight in each sock. Increased workload was achieved by increasing the rate of alternating leg flexion and extension in time with a bleep sound of increasing frequency.\u0000Twenty subjects (10 healthy volunteers, 10 patients with pulmonary hypertension) performed two CMR-augmented cardiopulmonary exercise tests (CMR-CPET) using the novel exercise apparatus and a conventional ergometer in a randomised order. Results\u0000Comparing peak metrics elicited on both exercise devices, there was a moderate correlation in peak oxygen consumption (VO2, r=0.86, P<0.001), cardiac output (CO, r=0.66, P=0.002), stroke volume (SV, r=0.75, P<0.001), peak heart rate (HR, r=0.65, P=0.002) and peak arteriovenous oxygen content gradient (△avO2, r=0.71, P<0.001). However, all metrics (except peak SV) were significantly lower from the novel device. Both devices were able to elicit statistically significant differences in VO2, HR and RVEF between patients and healthy subjects (P≤0.036). Conclusions\u0000We have created a simple, easy to use and affordable exercise apparatus for CMR environment. This may encourage greater dissemination of exercise CMR in clinical and research practice. Keywords: exercise CMR device, pulmonary hypertension, systemic sclerosis","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745465","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 : 2024-07-21DOI: 10.1101/2024.07.21.24310760
Gazal Mahameed, Dana Brin, Eli Konen, Girish Nadkarni, Eyal Klang
Background: As MRI use grows in medical diagnostics, applying NLP techniques could improve management of related text data. This review aims to explore how NLP can augment radiological evaluations in MRI. Methods: We conducted a PubMed search for studies that applied NLP in the clinical analysis of MRI, including publications up to January 4, 2024. The quality and potential bias of the included studies were assessed using the QUADAS-2 tool. Results: Twenty-six studies published between April 2010 and January 2024, covering more than 160k MRI reports were analyzed. Most of these studies demonstrated low to no risk of bias of the NLP. Neurology was the most frequently studied specialty, with twelve studies, followed by musculoskeletal (MSK) and body imaging. Applications of NLP included staging, quantification, and disease diagnosis. Notably, NLP showed high precision in tumor staging classification and structuring of free-text reports. Conclusion: NLP shows promise in enhancing the utility of MRI. However, there is a need for prospective studies to further validate NLP algorithms in real-time clinical and operational scenarios and across various radiology specialties, which could lead to broader applications in healthcare.
{"title":"Systematic review of natural language processing (NLP) applications in magnetic resonance imaging (MRI)","authors":"Gazal Mahameed, Dana Brin, Eli Konen, Girish Nadkarni, Eyal Klang","doi":"10.1101/2024.07.21.24310760","DOIUrl":"https://doi.org/10.1101/2024.07.21.24310760","url":null,"abstract":"Background: As MRI use grows in medical diagnostics, applying NLP techniques could improve management of related text data. This review aims to explore how NLP can augment radiological evaluations in MRI.\u0000Methods: We conducted a PubMed search for studies that applied NLP in the clinical analysis of MRI, including publications up to January 4, 2024. The quality and potential bias of the included studies were assessed using the QUADAS-2 tool.\u0000Results: Twenty-six studies published between April 2010 and January 2024, covering more than 160k MRI reports were analyzed. Most of these studies demonstrated low to no risk of bias of the NLP. Neurology was the most frequently studied specialty, with twelve studies, followed by musculoskeletal (MSK) and body imaging. Applications of NLP included staging, quantification, and disease diagnosis. Notably, NLP showed high precision in tumor staging classification and structuring of free-text reports.\u0000Conclusion: NLP shows promise in enhancing the utility of MRI. However, there is a need for prospective studies to further validate NLP algorithms in real-time clinical and operational scenarios and across various radiology specialties, which could lead to broader applications in healthcare.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737125","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 : 2024-07-19DOI: 10.1101/2024.07.17.24310314
June-Goo Lee, Tae Joon Jun, Gyujun Jeong, Hongmin Oh, Sijoon Kim, Heejun Kang, Jung Bok Lee, Hyun Jung Koo, Jong Eun Lee, Joon-Won Kang, Yura Ahn, Sang Min Lee, Joon Beom Seo, Seong Ho Park, Min Soo Cho, Jung-Min Ahn, Duk-Woo Park, Joon Bum Kim, Cherry Kim, Young Joo Suh, Iksung Cho, Marly van Assen, Carlo N De Cecco, Eun Ju Chun, Young-Hak Kim, Dong Hyun Yang
OBJECTIVE The analysis of cardiovascular borders (CVBs) on chest X-rays (CXRs) has traditionally relied on subjective assessment, and the cardiothoracic (CT) ratio, its sole quantitative marker, does not reflect great vessel changes and lacks established normal ranges. This study aimed to develop a deep learning-based method for quantifying CVBs on CXRs and to explore its clinical utility. DESIGN Diagnostic/prognostic study SETTING Pre-validated deep learning for quantification and z-score standardization of CVBs: the superior vena cava/ascending aorta (SVC/AO), right atrium (RA), aortic arch, pulmonary artery, left atrial appendage (LAA), left ventricle (LV), descending aorta, and carinal angle. PARTICIPANTS A total of 96,129 normal CXRs from 4 sites were used to establish age- and sex-specific normal ranges of CVBs. The clinical utility of the z-score analysis was tested using 44,567 diseased CXRs from 3 sites. MAIN OUTCOMES MEASURES The area under the curve (AUC) for detecting disease, differences in z-scores for classifying subtypes, and hazard ratio (HR) for predicting 5-year risk of death or myocardial infarction. RESULTS: A total of 44,567 patients with disease (9964 valve disease; 32,900 coronary artery disease; 1299 congenital heart disease; 294 aortic aneurysm; 110 mediastinal mass) were analyzed. For distinguishing valve disease from normal controls, the AUC for the CT ratio was 0.79 (95% CI, 0.78-0.80), while the combination of RA and LV had an AUC of 0.82 (95% CI, 0.82-0.83). Between mitral and aortic stenosis, z-scores of CVBs were significantly different in LAA (1.54 vs. 0.33, p<0.001), carinal angle (1.10 vs. 0.67, p<0.001), and SVC/AO (0.63 vs. 1.02, p<0.001), reflecting distinct disease pathophysiology (dilatation of LA vs. AO). CT ratio was independently associated with a 5-year risk of death or myocardial infarction in the coronary artery disease group (z-score ≥2, adjusted HR 3.73 [95% CI, 2.09-6.64], reference z-score <-1). CONCLUSIONS Fully automated, deep learning-derived z-score analysis of CXR showed potential in detecting, classifying, and stratifying the risk of cardiovascular abnormalities. Further research is needed to determine the most beneficial clinical scenarios for this method.
目的：胸部 X 光片（CXR）上心血管边界（CVB）的分析历来依赖于主观评估，而心胸（CT）比值是其唯一的定量标记，它不能反映大血管的变化，也缺乏既定的正常范围。本研究旨在开发一种基于深度学习的方法，用于量化 CXR 上的 CVB，并探索其临床实用性。设计诊断/预后研究设定 对上腔静脉/升主动脉 (SVC/AO)、右心房 (RA)、主动脉弓、肺动脉、左心房附壁 (LAA)、左心室 (LV)、降主动脉和心尖角等 CVB 的量化和 Z 值标准化进行预先验证的深度学习。参试者 共使用了来自 4 个地点的 96,129 张正常 CXR 照片来确定不同年龄和性别的 CVB 正常范围。使用来自 3 个地点的 44,567 张病变 CXR 照片测试了 z 值分析的临床实用性。主要结果测量：检测疾病的曲线下面积（AUC）、划分亚型的 z 值差异以及预测 5 年死亡或心肌梗死风险的危险比（HR）。结果：共分析了 44567 名疾病患者（9964 名瓣膜病患者；32900 名冠心病患者；1299 名先天性心脏病患者；294 名主动脉瘤患者；110 名纵隔肿块患者）。在区分瓣膜疾病和正常对照组时，CT 比值的 AUC 为 0.79（95% CI，0.78-0.80），而 RA 和 LV 组合的 AUC 为 0.82（95% CI，0.82-0.83）。在二尖瓣狭窄和主动脉瓣狭窄之间，LAA（1.54 vs. 0.33，p<0.001）、心尖角（1.10 vs. 0.67，p<0.001）和 SVC/AO （0.63 vs. 1.02，p<0.001）的 CVBs z 值有显著差异，反映了不同的疾病病理生理学（LA 的扩张 vs. AO）。在冠心病组中，CT 比值与 5 年死亡或心肌梗死风险独立相关（z-score ≥2，调整 HR 3.73 [95% CI, 2.09-6.64]，参考 z-score<-1）。要确定这种方法最有益的临床应用场景，还需要进一步的研究。
{"title":"Automated, standardized, quantitative analysis of cardiovascular borders on chest X-rays using deep learning for assessing cardiovascular disease","authors":"June-Goo Lee, Tae Joon Jun, Gyujun Jeong, Hongmin Oh, Sijoon Kim, Heejun Kang, Jung Bok Lee, Hyun Jung Koo, Jong Eun Lee, Joon-Won Kang, Yura Ahn, Sang Min Lee, Joon Beom Seo, Seong Ho Park, Min Soo Cho, Jung-Min Ahn, Duk-Woo Park, Joon Bum Kim, Cherry Kim, Young Joo Suh, Iksung Cho, Marly van Assen, Carlo N De Cecco, Eun Ju Chun, Young-Hak Kim, Dong Hyun Yang","doi":"10.1101/2024.07.17.24310314","DOIUrl":"https://doi.org/10.1101/2024.07.17.24310314","url":null,"abstract":"OBJECTIVE\u0000The analysis of cardiovascular borders (CVBs) on chest X-rays (CXRs) has traditionally relied on subjective assessment, and the cardiothoracic (CT) ratio, its sole quantitative marker, does not reflect great vessel changes and lacks established normal ranges. This study aimed to develop a deep learning-based method for quantifying CVBs on CXRs and to explore its clinical utility. DESIGN\u0000Diagnostic/prognostic study\u0000SETTING Pre-validated deep learning for quantification and z-score standardization of CVBs: the superior vena cava/ascending aorta (SVC/AO), right atrium (RA), aortic arch, pulmonary artery, left atrial appendage (LAA), left ventricle (LV), descending aorta, and carinal angle.\u0000PARTICIPANTS A total of 96,129 normal CXRs from 4 sites were used to establish age- and sex-specific normal ranges of CVBs. The clinical utility of the z-score analysis was tested using 44,567 diseased CXRs from 3 sites. MAIN OUTCOMES MEASURES The area under the curve (AUC) for detecting disease, differences in z-scores for classifying subtypes, and hazard ratio (HR) for predicting 5-year risk of death or myocardial infarction. RESULTS: A total of 44,567 patients with disease (9964 valve disease; 32,900 coronary artery disease; 1299 congenital heart disease; 294 aortic aneurysm; 110 mediastinal mass) were analyzed. For distinguishing valve disease from normal controls, the AUC for the CT ratio was 0.79 (95% CI, 0.78-0.80), while the combination of RA and LV had an AUC of 0.82 (95% CI, 0.82-0.83). Between mitral and aortic stenosis, z-scores of CVBs were significantly different in LAA (1.54 vs. 0.33, p<0.001), carinal angle (1.10 vs. 0.67, p<0.001), and SVC/AO (0.63 vs. 1.02, p<0.001), reflecting distinct disease pathophysiology (dilatation of LA vs. AO). CT ratio was independently associated with a 5-year risk of death or myocardial infarction in the coronary artery disease group (z-score ≥2, adjusted HR 3.73 [95% CI, 2.09-6.64], reference z-score <-1).\u0000CONCLUSIONS Fully automated, deep learning-derived z-score analysis of CXR showed potential in detecting, classifying, and stratifying the risk of cardiovascular abnormalities. Further research is needed to determine the most beneficial clinical scenarios for this method.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737156","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 : 2024-07-05DOI: 10.1101/2024.07.04.24309964
Caryn Geady, Hemangini Patel, Jacob Peoples, Amber Simpson, Benjamin Haibe-Kains
Background Radiomics traditionally focuses on analyzing a single lesion within a patient to extract tumor characteristics, yet this process may overlook inter-lesion heterogeneity, particularly in the multi-metastatic setting. There is currently no established method for combining radiomic features in such settings, leading to diverse approaches with varying strengths and limitations. Our quantitative review aims to illuminate these methodologies, assess their replicability, and guide future research toward establishing best practices, offering insights into the challenges of multi-lesion radiomic analysis across diverse datasets. Methods We conducted a comprehensive literature search to identify methods for integrating data from multiple lesions in radiomic analyses. We replicated these methods using either the author's code or by reconstructing them based on the information provided in the papers. Subsequently, we applied these identified methods to three distinct datasets, each depicting a different metastatic scenario. Results We compared ten mathematical methods for combining radiomic features across three distinct datasets, encompassing a total of 16,850 lesions in 3,930 patients. Performance of these methods was evaluated using the Cox proportional hazards model and benchmarked against univariable analysis of total tumor volume. We observed variable performance in methods across datasets. However, no single method consistently outperformed others across all datasets. Notably, while some methods surpassed total tumor volume analysis in certain datasets, others did not. Averaging methods showed higher median performance in patients with colorectal liver metastases, and in soft tissue sarcoma, concatenation of radiomic features from different lesions exhibited the highest median performance among tested methods. Conclusions Radiomic features can be effectively selected or combined to estimate patient-level outcomes in multi-metastatic patients, though the approach varies by metastatic setting. Our study fills a critical gap in radiomics research by examining the challenges of radiomic-based analysis in this setting. Through a comprehensive review and rigorous testing of different methods across diverse datasets representing unique metastatic scenarios, we provide valuable insights into effective radiomic analysis strategies.
{"title":"Radiomic-Based Approaches in the Multi-metastatic Setting: a Quantitative Review","authors":"Caryn Geady, Hemangini Patel, Jacob Peoples, Amber Simpson, Benjamin Haibe-Kains","doi":"10.1101/2024.07.04.24309964","DOIUrl":"https://doi.org/10.1101/2024.07.04.24309964","url":null,"abstract":"Background\u0000Radiomics traditionally focuses on analyzing a single lesion within a patient to extract tumor characteristics, yet this process may overlook inter-lesion heterogeneity, particularly in the multi-metastatic setting. There is currently no established method for combining radiomic features in such settings, leading to diverse approaches with varying strengths and limitations. Our quantitative review aims to illuminate these methodologies, assess their replicability, and guide future research toward establishing best practices, offering insights into the challenges of multi-lesion radiomic analysis across diverse datasets.\u0000Methods\u0000We conducted a comprehensive literature search to identify methods for integrating data from multiple lesions in radiomic analyses. We replicated these methods using either the author's code or by reconstructing them based on the information provided in the papers. Subsequently, we applied these identified methods to three distinct datasets, each depicting a different metastatic scenario.\u0000Results\u0000We compared ten mathematical methods for combining radiomic features across three distinct datasets, encompassing a total of 16,850 lesions in 3,930 patients. Performance of these methods was evaluated using the Cox proportional hazards model and benchmarked against univariable analysis of total tumor volume. We observed variable performance in methods across datasets. However, no single method consistently outperformed others across all datasets. Notably, while some methods surpassed total tumor volume analysis in certain datasets, others did not. Averaging methods showed higher median performance in patients with colorectal liver metastases, and in soft tissue sarcoma, concatenation of radiomic features from different lesions exhibited the highest median performance among tested methods. Conclusions\u0000Radiomic features can be effectively selected or combined to estimate patient-level outcomes in multi-metastatic patients, though the approach varies by metastatic setting. Our study fills a critical gap in radiomics research by examining the challenges of radiomic-based analysis in this setting. Through a comprehensive review and rigorous testing of different methods across diverse datasets representing unique metastatic scenarios, we provide valuable insights into effective radiomic analysis strategies.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568922","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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