Pub Date : 2025-05-01DOI: 10.1016/j.diii.2024.11.006
Clément Marcelin , Amandine Crombé , Eva Jambon , Grégoire Robert , Franck Bladou , Pierre Bour , Thibaut Faller , Valéry Ozenne , Nicolas Grenier , Bruno Quesson
Purpose
The primary purpose of this study was to evaluate the accuracy of an MR-thermometry sequence for monitoring prostate temperature. The secondary purposes were to analyze clinical and technical factors that may affect accuracy and testing the method in a realistic setting, with MR-guided Laser ablation on an ex vivo muscle sample.
Materials and methods
An ex vivo muscle sample was subjected to Laser ablation while using a two-dimensional multislice segmented echo planar imaging sequence for MR thermometry. The MR thermometry measurements were compared with invasive sensor temperature readings to assess accuracy. Subsequently, 56 men with a median age of 70 years (age range: 53–84 years) who underwent prostate MRI examinations at 1.5- (n = 27) or 3 T (n = 24) were prospectively included. For each patient, the proportion of 'noisy voxels' (i.e., those with a temporal standard deviation of temperature [SD(T)] > 2 °C) in the prostate was calculated. The impact of clinical and technical factors on the proportion of noisy voxels was also examined.
Results
MR-thermometry showed excellent correlation with invasive sensors during MR-guided Laser ablation on the ex vivo muscle sample. The median proportion of noisy voxels per patient in the entire cohort was 1 % (Q1, 0.2; Q3, 4.9; range: 0–90.4). No significant differences in median proportion of noisy voxels were observed between examinations performed at 1.5 T and those at 3 T (P = 0.89 before and after adjustment). No clinical or technical factors significantly influenced the proportion of noisy voxels.
Conclusion
Two-dimensional real time multislice MR-thermometry is feasible and accurate for monitoring prostate temperature in patients.
目的:本研究的主要目的是评估核磁共振测温序列监测前列腺温度的准确性。次要目的是分析可能影响准确性的临床和技术因素,并在现实环境中对离体肌肉样本进行核磁共振引导激光消融测试。材料和方法:利用二维多层分割回波平面成像序列对离体肌肉样本进行激光消融,进行磁共振测温。将磁共振测温测量结果与侵入式传感器温度读数进行比较,以评估准确性。随后,56名中位年龄为70岁(年龄范围:53-84岁)的男性在1.5 T (n = 27)或3 T (n = 24)时接受了前列腺MRI检查。对于每个患者,计算前列腺中“噪声体素”(即温度[SD(T)]的时间标准偏差[SD(T)] >2°C)的比例。临床和技术因素对噪声体素比例的影响也进行了研究。结果:核磁共振温度测量与有创传感器在核磁共振引导下对离体肌肉样本进行激光消融时表现出良好的相关性。在整个队列中,每个患者的噪声体素的中位数比例为1% (Q1, 0.2;第三,4.9;范围:0 - 90.4)。在1.5 T和3 T时进行的检查中,噪声体素的中位数比例无显著差异(调整前后P = 0.89)。没有临床或技术因素显著影响噪声体素的比例。结论:二维实时多层磁共振测温法监测前列腺温度是可行且准确的。
{"title":"Real-time multislice MR-thermometry of the prostate: Assessment of feasibility, accuracy and sources of biases in patients","authors":"Clément Marcelin , Amandine Crombé , Eva Jambon , Grégoire Robert , Franck Bladou , Pierre Bour , Thibaut Faller , Valéry Ozenne , Nicolas Grenier , Bruno Quesson","doi":"10.1016/j.diii.2024.11.006","DOIUrl":"10.1016/j.diii.2024.11.006","url":null,"abstract":"<div><h3>Purpose</h3><div>The primary purpose of this study was to evaluate the accuracy of an MR-thermometry sequence for monitoring prostate temperature. The secondary purposes were to analyze clinical and technical factors that may affect accuracy and testing the method in a realistic setting, with MR-guided Laser ablation on an <em>ex vivo</em> muscle sample.</div></div><div><h3>Materials and methods</h3><div>An <em>ex vivo</em> muscle sample was subjected to Laser ablation while using a two-dimensional multislice segmented echo planar imaging sequence for MR thermometry. The MR thermometry measurements were compared with invasive sensor temperature readings to assess accuracy. Subsequently, 56 men with a median age of 70 years (age range: 53–84 years) who underwent prostate MRI examinations at 1.5- (<em>n</em> = 27) or 3 T (<em>n</em> = 24) were prospectively included. For each patient, the proportion of 'noisy voxels' (i.e., those with a temporal standard deviation of temperature [SD(T)] > 2 °C) in the prostate was calculated. The impact of clinical and technical factors on the proportion of noisy voxels was also examined.</div></div><div><h3>Results</h3><div>MR-thermometry showed excellent correlation with invasive sensors during MR-guided Laser ablation on the <em>ex vivo</em> muscle sample. The median proportion of noisy voxels per patient in the entire cohort was 1 % (Q1, 0.2; Q3, 4.9; range: 0–90.4). No significant differences in median proportion of noisy voxels were observed between examinations performed at 1.5 T and those at 3 T (<em>P</em> = 0.89 before and after adjustment). No clinical or technical factors significantly influenced the proportion of noisy voxels.</div></div><div><h3>Conclusion</h3><div>Two-dimensional real time multislice MR-thermometry is feasible and accurate for monitoring prostate temperature in patients.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 5","pages":"Pages 183-191"},"PeriodicalIF":4.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study was to introduce and evaluate a novel 2D wideband black-blood (BB) LGE sequence, incorporating wideband inversion recovery, wideband T2 preparation, and non-rigid motion correction (MOCO) reconstruction, to improve myocardial scar detection and address artifacts associated with implantable cardioverter defibrillators (ICDs).
Materials and methods
The wideband MOCO free-breathing BB-LGE sequence was tested on a sheep with ischemic scar and in 22 patients with cardiac disease, including 15 with cardiac implants, at 1.5T. Wideband MOCO free-breathing BB-LGE sequence was compared with conventional and wideband breath-held PSIR-LGE and conventional and wideband breath-held BB-LGE techniques. Image sharpness, entropy, and scar-to-blood, scar-to-myocardium, and blood-to-myocardium contrast were analyzed and reconstruction times were measured. Two expert readers assessed the image quality, ICD artifact severity, and the diagnostic confidence with scar extent. Finally, for the animal study, a histology of the heart was performed to confirm the presence and localization of scar tissue.
Results
In the animal, wideband MOCO free-breathing BB-LGE were reconstructed in 0.6 s and demonstrated a 200 % improvement in scar-to-blood contrast compared to wideband breath-held PSIR-LGE, with significant improvement in image sharpness and reduction in entropy. It also effectively minimized ICD artifacts and accurately detected scars. In patients, wideband MOCO free-breathing BB-LGE were reconstructed in 1.5 ± 0.4 (standard deviation) s per slice. Seventeen patients (17/22; 77%) with myocardial scars were confidently diagnosed with wideband MOCO free-breathing BB-LGE, compared to 11 (11/22; 50 %) with wideband breath-held PSIR-LGE (P < 0.01).
Conclusion
Free-breathing wideband T2-prepared black-blood LGE imaging, combined with motion-corrected reconstruction, offers a promising diagnostic approach for the evaluation of myocardial lesions in patients with ICDs.
{"title":"Improved myocardial scar visualization using free-breathing motion-corrected wideband black-blood late gadolinium enhancement imaging in patients with implantable cardiac devices","authors":"Pauline Gut , Hubert Cochet , Panagiotis Antiochos , Guido Caluori , Baptiste Durand , Marion Constantin , Konstantinos Vlachos , Kalvin Narceau , Ambra Masi , Jürg Schwitter , Frederic Sacher , Pierre Jaïs , Matthias Stuber , Aurélien Bustin","doi":"10.1016/j.diii.2024.12.001","DOIUrl":"10.1016/j.diii.2024.12.001","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of this study was to introduce and evaluate a novel 2D wideband black-blood (BB) LGE sequence, incorporating wideband inversion recovery, wideband T2 preparation, and non-rigid motion correction (MOCO) reconstruction, to improve myocardial scar detection and address artifacts associated with implantable cardioverter defibrillators (ICDs).</div></div><div><h3>Materials and methods</h3><div>The wideband MOCO free-breathing BB-LGE sequence was tested on a sheep with ischemic scar and in 22 patients with cardiac disease, including 15 with cardiac implants, at 1.5T. Wideband MOCO free-breathing BB-LGE sequence was compared with conventional and wideband breath-held PSIR-LGE and conventional and wideband breath-held BB-LGE techniques. Image sharpness, entropy, and scar-to-blood, scar-to-myocardium, and blood-to-myocardium contrast were analyzed and reconstruction times were measured. Two expert readers assessed the image quality, ICD artifact severity, and the diagnostic confidence with scar extent. Finally, for the animal study, a histology of the heart was performed to confirm the presence and localization of scar tissue.</div></div><div><h3>Results</h3><div>In the animal, wideband MOCO free-breathing BB-LGE were reconstructed in 0.6 s and demonstrated a 200 % improvement in scar-to-blood contrast compared to wideband breath-held PSIR-LGE, with significant improvement in image sharpness and reduction in entropy. It also effectively minimized ICD artifacts and accurately detected scars. In patients, wideband MOCO free-breathing BB-LGE were reconstructed in 1.5 ± 0.4 (standard deviation) s per slice. Seventeen patients (17/22; 77%) with myocardial scars were confidently diagnosed with wideband MOCO free-breathing BB-LGE, compared to 11 (11/22; 50 %) with wideband breath-held PSIR-LGE (<em>P</em> < 0.01).</div></div><div><h3>Conclusion</h3><div>Free-breathing wideband T2-prepared black-blood LGE imaging, combined with motion-corrected reconstruction, offers a promising diagnostic approach for the evaluation of myocardial lesions in patients with ICDs.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 5","pages":"Pages 169-182"},"PeriodicalIF":4.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142819643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.diii.2025.01.006
Baptiste Bonnet , Lambros Tselikas
{"title":"Robotics and artificial intelligence in the real world of interventional radiology: Innovation or illusion?","authors":"Baptiste Bonnet , Lambros Tselikas","doi":"10.1016/j.diii.2025.01.006","DOIUrl":"10.1016/j.diii.2025.01.006","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 5","pages":"Pages 145-146"},"PeriodicalIF":4.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143123914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.diii.2025.01.002
Farah Cadour , Benjamin Longère
{"title":"Myocardial scar detection in patients with implantable cardiac device: Wideband free-breathing motion-corrected black-blood late gadolinium enhancement could be the answer","authors":"Farah Cadour , Benjamin Longère","doi":"10.1016/j.diii.2025.01.002","DOIUrl":"10.1016/j.diii.2025.01.002","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 5","pages":"Pages 143-144"},"PeriodicalIF":4.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-01DOI: 10.1016/j.diii.2025.01.004
Francois H. Cornelis , Dimitrios K Filippiadis , Philipp Wiggermann , Stephen B. Solomon , David C. Madoff , Laurent Milot , Sylvain Bodard
Purpose
Navigation and robotic systems aim to improve the accuracy and efficiency of percutaneous image-guided interventions, but the evaluation of their autonomy and integration of advanced imaging and artificial intelligence (AI) is lacking. The purpose of this study was to evaluate the level of automation and integration of advanced imaging and artificial intelligence in navigation and robotic systems for percutaneous image-guided interventions, using established and novel metrics to categorize and compare their capabilities.
Materials and methods
Following PRISMA guidelines, a systematic review was conducted to identify studies on clinically validated navigation and robotic systems published between 2000 and May 2024. The PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Data on navigation devices were extracted and analyzed. The levels of autonomy in surgical robotics (LASR) classification system (from 1 to 5) was used to analyze automation. A novel taxonomy, the Levels of Integration of Advanced Imaging and AI (LIAI2) classification system, was created to categorize the integration of imaging technologies and AI (from 1 to 5). These two scores were combined into an aggregate score (from 1 to 10) to reflect the autonomy in percutaneous image-guided intervention.
Results
The review included 20 studies assessing two navigation systems and eight robotic devices. The median LASR score was 1 (Q1, Q3: 1, 1), the median LIAI2 score was 2 (Q1, Q3: 2, 3), and the median aggregate score was 3 (Q1, Q3: 3, 4). Only one robotic system (10 % of those reviewed) achieved the highest LASR qualification in the literature, a level 2/5. Four systems (40 %) shared the highest rating for LIAI2, which was a score of 3/5. Four systems (40 %) achieved the highest aggregate scores of 4/10.
Conclusion
None of the navigation and robotic systems achieved full autonomy for percutaneous image-guided intervention. The LASR and LIAI2 scales can guide innovation by identifying areas for further development and integration.
{"title":"Evaluation of navigation and robotic systems for percutaneous image-guided interventions: A novel metric for advanced imaging and artificial intelligence integration","authors":"Francois H. Cornelis , Dimitrios K Filippiadis , Philipp Wiggermann , Stephen B. Solomon , David C. Madoff , Laurent Milot , Sylvain Bodard","doi":"10.1016/j.diii.2025.01.004","DOIUrl":"10.1016/j.diii.2025.01.004","url":null,"abstract":"<div><h3>Purpose</h3><div>Navigation and robotic systems aim to improve the accuracy and efficiency of percutaneous image-guided interventions, but the evaluation of their autonomy and integration of advanced imaging and artificial intelligence (AI) is lacking. The purpose of this study was to evaluate the level of automation and integration of advanced imaging and artificial intelligence in navigation and robotic systems for percutaneous image-guided interventions, using established and novel metrics to categorize and compare their capabilities.</div></div><div><h3>Materials and methods</h3><div>Following PRISMA guidelines, a systematic review was conducted to identify studies on clinically validated navigation and robotic systems published between 2000 and May 2024. The PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Data on navigation devices were extracted and analyzed. The levels of autonomy in surgical robotics (LASR) classification system (from 1 to 5) was used to analyze automation. A novel taxonomy, the Levels of Integration of Advanced Imaging and AI (LIAI2) classification system, was created to categorize the integration of imaging technologies and AI (from 1 to 5). These two scores were combined into an aggregate score (from 1 to 10) to reflect the autonomy in percutaneous image-guided intervention.</div></div><div><h3>Results</h3><div>The review included 20 studies assessing two navigation systems and eight robotic devices. The median LASR score was 1 (Q1, Q3: 1, 1), the median LIAI2 score was 2 (Q1, Q3: 2, 3), and the median aggregate score was 3 (Q1, Q3: 3, 4). Only one robotic system (10 % of those reviewed) achieved the highest LASR qualification in the literature, a level 2/5. Four systems (40 %) shared the highest rating for LIAI2, which was a score of 3/5. Four systems (40 %) achieved the highest aggregate scores of 4/10.</div></div><div><h3>Conclusion</h3><div>None of the navigation and robotic systems achieved full autonomy for percutaneous image-guided intervention. The LASR and LIAI2 scales can guide innovation by identifying areas for further development and integration.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 5","pages":"Pages 157-168"},"PeriodicalIF":4.9,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.diii.2024.09.009
Maxime Barat , Camille Ollivier , Linda Taibi , Véronique Nitsche , Philippe Sogni , Philippe Soyer , Lucia Parlati , Anthony Dohan , Hendy Abdoul , Marie-Pierre Revel
Purpose
The purpose of this study was to compare levels of pain and anxiety during percutaneous ultrasound-guided liver biopsy between patients receiving standard of care and those receiving standard of care plus the support of Ericksonian hypnosis.
Materials and methods
This prospective, single-center, single-blind, randomized controlled superiority trial included 70 participants. Participants were randomly assigned to either the standard of care group and received oral anxiolytic medications with reassuring conversational support, or to the experimental group, and received Ericksonian hypnosis (i.e., conversational hypnosis) in addition to standard of care. The primary outcome was the level of pain experienced during the biopsy, measured on a 10-point visual analog scale (0 indicating no pain to 10 indicating excruciating pain). Secondary outcomes included anxiety level during the biopsy, pain level within one hour of the biopsy measured using the same 10-point visual analog scale, amount of analgesic medication taken in the 24 h following the biopsy, and patient willingness to undergo another ultrasound-guided percutaneous liver biopsy in the future.
Results
Thirty-six participants were included in the standard of care group, and 34 were included in the experimental group. The mean score of pain experienced during the biopsy was lower in the experimental group (2.4 ± 1.9 [standard deviation (SD)]) compared to the standard of care group (4.4 ± 2.6 [SD]) (P = 0.001). The level of anxiety experienced during the biopsy was lower in the hypnosis group (2.1 ± 1.8 [SD]) compared to the standard of care group (4.8 ± 2.4 [SD]) (P < 0.001). No significant differences in other secondary outcomes were observed between the two groups.
Conclusion
The addition of Ericksonian hypnosis to standard of care reduces the pain experienced by patients during percutaneous ultrasound-guided percutaneous liver biopsy by comparison with standard of care alone.
{"title":"Standard of care versus standard of care plus Ericksonian hypnosis for percutaneous liver biopsy: Results of a randomized control trial","authors":"Maxime Barat , Camille Ollivier , Linda Taibi , Véronique Nitsche , Philippe Sogni , Philippe Soyer , Lucia Parlati , Anthony Dohan , Hendy Abdoul , Marie-Pierre Revel","doi":"10.1016/j.diii.2024.09.009","DOIUrl":"10.1016/j.diii.2024.09.009","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of this study was to compare levels of pain and anxiety during percutaneous ultrasound-guided liver biopsy between patients receiving standard of care and those receiving standard of care plus the support of Ericksonian hypnosis.</div></div><div><h3>Materials and methods</h3><div>This prospective, single-center, single-blind, randomized controlled superiority trial included 70 participants. Participants were randomly assigned to either the standard of care group and received oral anxiolytic medications with reassuring conversational support, or to the experimental group, and received Ericksonian hypnosis (<em>i.e., conversational hypnosis</em>) in addition to standard of care. The primary outcome was the level of pain experienced during the biopsy, measured on a 10-point visual analog scale (0 indicating no pain to 10 indicating excruciating pain). Secondary outcomes included anxiety level during the biopsy, pain level within one hour of the biopsy measured using the same 10-point visual analog scale, amount of analgesic medication taken in the 24 h following the biopsy, and patient willingness to undergo another ultrasound-guided percutaneous liver biopsy in the future.</div></div><div><h3>Results</h3><div>Thirty-six participants were included in the standard of care group, and 34 were included in the experimental group. The mean score of pain experienced during the biopsy was lower in the experimental group (2.4 ± 1.9 [standard deviation (SD)]) compared to the standard of care group (4.4 ± 2.6 [SD]) (<em>P</em> = 0.001). The level of anxiety experienced during the biopsy was lower in the hypnosis group (2.1 ± 1.8 [SD]) compared to the standard of care group (4.8 ± 2.4 [SD]) (<em>P</em> < 0.001). No significant differences in other secondary outcomes were observed between the two groups.</div></div><div><h3>Conclusion</h3><div>The addition of Ericksonian hypnosis to standard of care reduces the pain experienced by patients during percutaneous ultrasound-guided percutaneous liver biopsy by comparison with standard of care alone.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 3","pages":"Pages 93-97"},"PeriodicalIF":4.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.diii.2024.10.001
Laetitia Saccenti , Bilel Ben Jedida , Lise Minssen , Refaat Nouri , Lina El Bejjani , Haifa Remili , An Voquang , Vania Tacher , Hicham Kobeiter , Alain Luciani , Jean Francois Deux , Thu Ha Dao
Purpose
The purpose of this study was to evaluate an artificial intelligence (AI) software that automatically detects and quantifies breast arterial calcifications (BAC).
Materials and methods
Women who underwent both mammography and thoracic computed tomography (CT) from 2009 to 2018 were retrospectively included in this single-center study. Deep learning-based software was used to automatically detect and quantify BAC with a BAC AI score ranging from 0 to 10-points. Results were compared using Spearman correlation test with a previously described BAC manual score based on radiologists’ visual quantification of BAC on the mammogram. Coronary artery calcification (CAC) score was manually scored using a 12-point scale on CT. The diagnostic performance of the marked BAC AI score (defined as BAC AI score ≥ 5) for the detection of marked CAC (CAC score ≥ 4) was analyzed in terms of sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC).
Results
A total of 502 women with a median age of 62 years (age range: 42–96 years) were included. The BAC AI score showed a very strong correlation with the BAC manual score (r = 0.83). Marked BAC AI score had 32.7 % sensitivity (37/113; 95 % confidence interval [CI]: 24.2–42.2), 96.1 % specificity (374/389; 95 % CI: 93.7–97.8), 71.2 % positive predictive value (37/52; 95 % CI: 56.9–82.9), 83.1 % negative predictive value (374/450; 95 % CI: 79.3–86.5), and 81.9 % accuracy (411/502; 95 % CI: 78.2–85.1) for the diagnosis of marked CAC. The AUC of the marked BAC AI score for the diagnosis of marked CAC was 0.64 (95 % CI: 0.60–0.69).
Conclusion
The automated BAC AI score shows a very strong correlation with manual BAC scoring in this external validation cohort. The automated BAC AI score may be a useful tool to promote the integration of BAC into mammography reports and to improve awareness of a woman's cardiovascular risk status.
目的:本研究旨在评估一款可自动检测和量化乳腺动脉钙化(BAC)的人工智能(AI)软件:这项单中心研究回顾性地纳入了 2009 年至 2018 年期间接受乳腺 X 射线照相术和胸部计算机断层扫描(CT)的女性。使用基于深度学习的软件自动检测和量化 BAC,BAC AI 得分从 0 分到 10 分不等。研究结果通过斯皮尔曼相关性检验与之前描述的基于放射科医师对乳房 X 光片上 BAC 的视觉量化的 BAC 人工评分进行了比较。冠状动脉钙化(CAC)评分是在 CT 上使用 12 分制手动评分的。从敏感性、特异性、准确性和接收器操作特征曲线下面积(AUC)等方面分析了标记的 BAC AI 评分(定义为 BAC AI 评分≥5)在检测标记的 CAC(CAC 评分≥4)方面的诊断性能:共纳入 502 名妇女,中位年龄为 62 岁(年龄范围:42-96 岁)。BAC AI 评分与 BAC 手工评分有很强的相关性(r = 0.83)。标记的 BAC AI 评分具有 32.7 % 的灵敏度(37/113;95 % 置信区间 [CI]:24.2-42.2)、96.1 % 的特异性(374/389;95 % CI:93.7-97.8)、71.2 % 的阳性预测值(37/52;95 % CI:56.诊断明显 CAC 的阳性预测值为 71.2%(37/52;95 % CI:56.9-82.9),阴性预测值为 83.1%(374/450;95 % CI:79.3-86.5),准确率为 81.9%(411/502;95 % CI:78.2-85.1)。诊断明显 CAC 的 BAC AI 评分的 AUC 为 0.64(95 % CI:0.60-0.69):结论:在这一外部验证队列中,自动 BAC AI 评分与手动 BAC 评分显示出很强的相关性。自动 BAC AI 评分可能是促进将 BAC 纳入乳腺 X 射线摄影报告并提高对妇女心血管风险状况认识的有用工具。
{"title":"Evaluation of a deep learning-based software to automatically detect and quantify breast arterial calcifications on digital mammogram","authors":"Laetitia Saccenti , Bilel Ben Jedida , Lise Minssen , Refaat Nouri , Lina El Bejjani , Haifa Remili , An Voquang , Vania Tacher , Hicham Kobeiter , Alain Luciani , Jean Francois Deux , Thu Ha Dao","doi":"10.1016/j.diii.2024.10.001","DOIUrl":"10.1016/j.diii.2024.10.001","url":null,"abstract":"<div><h3>Purpose</h3><div>The purpose of this study was to evaluate an artificial intelligence (AI) software that automatically detects and quantifies breast arterial calcifications (BAC).</div></div><div><h3>Materials and methods</h3><div>Women who underwent both mammography and thoracic computed tomography (CT) from 2009 to 2018 were retrospectively included in this single-center study. Deep learning-based software was used to automatically detect and quantify BAC with a BAC AI score ranging from 0 to 10-points. Results were compared using Spearman correlation test with a previously described BAC manual score based on radiologists’ visual quantification of BAC on the mammogram. Coronary artery calcification (CAC) score was manually scored using a 12-point scale on CT. The diagnostic performance of the marked BAC AI score (defined as BAC AI score ≥ 5) for the detection of marked CAC (CAC score ≥ 4) was analyzed in terms of sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC).</div></div><div><h3>Results</h3><div>A total of 502 women with a median age of 62 years (age range: 42–96 years) were included. The BAC AI score showed a very strong correlation with the BAC manual score (<em>r</em> = 0.83). Marked BAC AI score had 32.7 % sensitivity (37/113; 95 % confidence interval [CI]: 24.2–42.2), 96.1 % specificity (374/389; 95 % CI: 93.7–97.8), 71.2 % positive predictive value (37/52; 95 % CI: 56.9–82.9), 83.1 % negative predictive value (374/450; 95 % CI: 79.3–86.5), and 81.9 % accuracy (411/502; 95 % CI: 78.2–85.1) for the diagnosis of marked CAC. The AUC of the marked BAC AI score for the diagnosis of marked CAC was 0.64 (95 % CI: 0.60–0.69).</div></div><div><h3>Conclusion</h3><div>The automated BAC AI score shows a very strong correlation with manual BAC scoring in this external validation cohort. The automated BAC AI score may be a useful tool to promote the integration of BAC into mammography reports and to improve awareness of a woman's cardiovascular risk status.</div></div>","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 3","pages":"Pages 98-104"},"PeriodicalIF":4.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.diii.2024.10.007
Mohamed S. Muneer , Rowa A. Mohamed , Tarik F. Massoud
{"title":"CT features of tension neck subcutaneous emphysema (tension pneumocollum)","authors":"Mohamed S. Muneer , Rowa A. Mohamed , Tarik F. Massoud","doi":"10.1016/j.diii.2024.10.007","DOIUrl":"10.1016/j.diii.2024.10.007","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 3","pages":"Pages 107-108"},"PeriodicalIF":4.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142576623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.diii.2024.12.003
Anita Paisant , Sébastien Mulé
{"title":"Shaping the future of MRI in upper abdominal imaging: The promise of deep learning reconstruction","authors":"Anita Paisant , Sébastien Mulé","doi":"10.1016/j.diii.2024.12.003","DOIUrl":"10.1016/j.diii.2024.12.003","url":null,"abstract":"","PeriodicalId":48656,"journal":{"name":"Diagnostic and Interventional Imaging","volume":"106 3","pages":"Pages 83-84"},"PeriodicalIF":4.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}