Academic Radiology最新文献_第5页

AI Applied to Breast Cancer: Early Detection and Explainable Predictive Models as the Basis of Precision Medicine 人工智能应用于乳腺癌：作为精准医疗基础的早期检测和可解释预测模型。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2025.01.045

Carmelo Militello

引用次数: 0

Advances in spatial resolution and radiation dose reduction using super-resolution deep learning–based reconstruction for abdominal computed tomography: A phantom study 利用基于深度学习的超分辨率重建技术提高腹部计算机断层扫描的空间分辨率并减少辐射剂量：模型研究。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.09.012

Yoshinori Funama , Yasunori Nagayama , Daisuke Sakabe , Yuya Ito , Yutaka Chiba , Takeshi Nakaura , Seitaro Oda , Masafumi Kidoh , Toshinori Hirai

Rationale and Objectives

This study evaluated the performance of super-resolution deep learning-based reconstruction (SR-DLR) and compared with it that of hybrid iterative reconstruction (HIR) and normal-resolution DLR (NR-DLR) for enhancing image quality in computed tomography (CT) images across various field of view (FOV) sizes, radiation doses, and noise reduction strengths.

Materials and Methods

A Catphan phantom equipped with an external body ring was used. CT images were reconstructed using filtered back-projection (FBP), HIR, NR-DLR, and SR-DLR across three noise reduction strengths: mild, standard, and strong. The noise power spectrum (NPS) was obtained from the FBP, HIR, NR-DLR, and SR-DLR images at various FOVs, radiation doses, and noise reduction strengths. The noise magnitude ratio (NMR) and central frequency ratio (CFR) were calculated from the HIR, NR-DLR, and SR-DLR images relative to the FBP images using NPS. The high-contrast value was obtained from the amplitude values of the peaks and valleys of profile curve and the task-based transfer function were also analyzed.

Results

SR-DLR consistently demonstrated superior noise reduction capabilities, with NMR of 0.29–0.36 at reduced dose and 0.35–0.45 at standard dose, outperforming HIR and showing comparable efficiency to NR-DLR. The high-contrast values for SR-DLR were highest at mild and standard levels for both low and standard doses (0.610 and 0.726 at mild and 0.725 and 0.603 at standard levels). At the standard dose, the spatial resolution of SR-DLR was significantly improved, regardless of the noise reduction strength and FOV.

Conclusion

SR-DLR images achieved more substantial noise reduction than HIR and similar noise reduction as NR-DLR reconstructions while also improving spatial resolution.

理论依据和目标：本研究评估了基于深度学习的超分辨率重建（SR-DLR）的性能，并将其与混合迭代重建（HIR）和正常分辨率 DLR（NR-DLR）进行了比较，以提高不同视场（FOV）大小、辐射剂量和降噪强度的计算机断层扫描（CT）图像的质量：使用一个装有体外环的 Catphan 模型。使用滤波背投影（FBP）、HIR、NR-DLR 和 SR-DLR，在三种降噪强度（轻微、标准和强烈）下重建 CT 图像。从不同视场角、辐射剂量和降噪强度下的 FBP、HIR、NR-DLR 和 SR-DLR 图像中获得噪声功率谱（NPS）。使用 NPS 计算了 HIR、NR-DLR 和 SR-DLR 图像相对于 FBP 图像的噪声幅度比 (NMR) 和中心频率比 (CFR)。高对比度值从轮廓曲线的峰值和谷值的振幅值中获得，基于任务的传递函数也得到了分析：SR-DLR 始终表现出卓越的降噪能力，减量时的 NMR 为 0.29-0.36，标准剂量时为 0.35-0.45，优于 HIR，与 NR-DLR 的效率相当。在低剂量和标准剂量下，SR-DLR 的高对比度值在轻度和标准剂量下都是最高的（轻度剂量下分别为 0.610 和 0.726，标准剂量下分别为 0.725 和 0.603）。在标准剂量下，SR-DLR 的空间分辨率显著提高，与降噪强度和 FOV 无关：SR-DLR图像的降噪效果比HIR更显著，降噪效果与NR-DLR重建相似，同时还提高了空间分辨率。

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引用次数: 0

Tumor Apparent Diffusion Coefficient is Associated with Early Recurrence of Intrahepatic Cholangiocarcinoma 肿瘤表观弥散系数与肝内胆管癌早期复发有关

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.09.035

Ruofan Sheng MD , Beixuan Zheng MD , Donglong He MB , Wei Sun MM , Yunfei Zhang PhD , Chun Yang MD , Mengsu Zeng PhD, MD

Rationale and Objectives

Identifying intrahepatic cholangiocarcinoma (iCCA) patients who are at high risk for early recurrence (ER) can guide personalized treatment strategy and improve survival. This study aimed to investigate the value of preoperative MRI, especially diffusion-weighted imaging, in predicting ER, including in patients receiving neoadjuvant therapy.

Materials and methods

This study included 175 pathologically-confirmed iCCA patients who underwent curative resection (114 men, 61 women; mean age 59.0 ± 9.56 years). MRI features, particularly apparent diffusion coefficient (ADC), were analyzed and compared between ER and non-ER cases. Survival analyses of ER were evaluated using Cox regression and Kaplan-Meier analysis.

Results

ER occurred in 54.3% (95/175) of patients. Multivariate logistic regression analysis identified tumor ADC as the only independent predictor of ER (odds ratio = 0.034, P < 0.001), with AUCs of 0.758 (95%CI 0.664, 0.836) in the testing cohort and 0.779 (95%CI 0.622, 0.893) in the validation cohort. The optimal ADC threshold was 1.273 × 10⁻³ mm²/s. Tumor ADC was comparable to the AJCC 8th staging system in predicting ER (AUC 0.758 vs 0.650 in testing cohort and 0.779 vs 0.661 in validation cohort). Multivariate Cox analysis identified high tumor burden score (HR = 1.109, P = 0.009), non-smooth margin (HR = 2.265, P = 0.008) and tumor ADC (HR = 0.111, P < 0.001) as independent risk factors for ER. Lower ADC values were linked to shorter RFS in both testing and validation cohorts (P < 0.001 and 0.0219), as well as in patients receiving neoadjuvant therapy (P = 0.003).

Conclusion

Preoperative MRI, particularly ADC, can help predict ER in iCCA, regardless of the application of neoadjuvant therapy, comparable to the AJCC 8th staging system.

理由和目标：识别肝内胆管癌（iCCA）早期复发（ER）高风险患者可指导个性化治疗策略并提高生存率。本研究旨在探讨术前磁共振成像（尤其是弥散加权成像）在预测早期复发（ER）（包括接受新辅助治疗的患者）方面的价值：本研究纳入了175例经病理证实接受根治性切除术的iCCA患者（男性114例，女性61例；平均年龄59.0 ± 9.56岁）。对 MRI 特征，尤其是表观弥散系数（ADC）进行了分析，并对 ER 和非 ER 病例进行了比较。采用 Cox 回归和 Kaplan-Meier 分析法评估了 ER 的生存分析：结果：54.3%的患者（95/175）发生了ER。多变量逻辑回归分析发现，肿瘤 ADC 是ER 的唯一独立预测因子（几率比 = 0.034，P -3 mm2/s）。在预测ER方面，肿瘤ADC与AJCC第8期分期系统相当（测试队列的AUC为0.758 vs 0.650，验证队列的AUC为0.779 vs 0.661）。多变量 Cox 分析确定了高肿瘤负荷评分（HR = 1.109，P = 0.009）、非平滑边缘（HR = 2.265，P = 0.008）和肿瘤 ADC（HR = 0.111，P 结论：MRI 和 ADC 预测ER 的准确率分别为 0.758 和 0.650：无论是否采用新辅助治疗，术前磁共振成像（尤其是 ADC）都能帮助预测 iCCA 的 ER，与 AJCC 第 8 期分期系统相当。

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引用次数: 0

A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients 基于超声深度学习提名图预测乳腺癌患者新辅助化疗后腋窝淋巴结状态的多中心队列研究

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.09.065

Shuhan Sun , Yajing Chen , Yutong Liu , Cuiying Li , Shumei Miao , Bin Yang , Feihong Yu MD

Rationale and Objectives

The aim of this study was to evaluate the capability of an ultrasound (US)-based deep learning (DL) nomogram for predicting axillary lymph node (ALN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients and its potential to assist radiologists in diagnosis.

Methods

Two medical centers retrospectively recruited 535 node-positive breast cancer patients who had undergone NAC. Center 1 included 288 patients in the training cohort and 123 patients in the internal validation cohort, while center 2 enrolled 124 patients for the external validation cohort. Five DL models (ResNet 34, ResNet 50, VGG19, GoogLeNet, and DenseNet 121) were trained on pre- and post-NAC US images, and the best model was chosen. A US-based DL nomogram was constructed using DL predictive probabilities and clinicopathological characteristics. Furthermore, the performances of radiologists were compared with and without the assistance of the nomogram.

Result

ResNet 50 performed best among all DL models, achieving areas under the curve (AUCs) of 0.837 and 0.850 in the internal and external validation cohorts, respectively. The US-based DL nomogram demonstrated strong predictive ability for ALN status post-NAC, with AUCs of 0.890 and 0.870 in the internal and external validation cohorts, respectively, outperforming both the clinical model and the DL model (p all < 0.05, except p = 0.19 for DL model in external validation cohort). Moreover, the nomogram significantly improved radiologists’ diagnostic ability.

Conclusion

The US-based DL nomogram is promising for predicting ALN status post-NAC and could assist radiologists for better diagnostic performance.

理论依据和目标：本研究旨在评估基于超声（US）的深度学习（DL）提名图预测乳腺癌患者新辅助化疗（NAC）后腋窝淋巴结（ALN）状态的能力及其协助放射医师诊断的潜力：两个医疗中心回顾性招募了535名接受新辅助化疗的结节阳性乳腺癌患者。中心 1 将 288 名患者纳入训练队列，将 123 名患者纳入内部验证队列，中心 2 将 124 名患者纳入外部验证队列。五个 DL 模型（ResNet 34、ResNet 50、VGG19、GoogLeNet 和 DenseNet 121）在 NAC 前后的 US 图像上进行了训练，并选出了最佳模型。利用 DL 预测概率和临床病理特征构建了基于 US 的 DL 提名图。此外，还比较了放射科医生在使用和不使用提名图的情况下的表现：结果：在所有 DL 模型中，ResNet 50 的表现最佳，在内部和外部验证队列中的曲线下面积（AUC）分别达到 0.837 和 0.850。基于美国的 DL 直方图对 NAC 后的 ALN 状态具有很强的预测能力，在内部和外部验证队列中的 AUC 分别为 0.890 和 0.870，优于临床模型和 DL 模型（除外部验证队列中 DL 模型的 p = 0.19 外，其余 p 均小于 0.05）。此外，该提名图还大大提高了放射医师的诊断能力：结论：基于美国 DL 的提名图有望预测 NAC 后的 ALN 状态，并能帮助放射科医生提高诊断能力。

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引用次数: 0

A Nomogram for the Prediction of Invasiveness in Invasive Pulmonary Adenocarcinoma on the Basis of Multimodal PET/CT Parameters 根据 PET/CT 多模态参数预测浸润性肺腺癌侵袭性的提名图

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.10.019

Ning Ma , Hongyan Du , Jun Li , Zhan Li , Shiyi Wang , Duxia Yu , Yu Wu , Ying Shan , Mengjie Dong

Objective

We investigated the value of PET/CT-based multimodal parameters in predicting the degree of differentiation and epidermal growth factor receptor (EGFR) mutations in invasive lung adenocarcinoma (ILA) and assessed the correlation between PET/CT-based multimodal parameters and Ki67.

Methods

We retrospectively collected 113 patients with ILA who underwent PET/CT examination, and differences in PET/CT multimodal parameters between different differentiation groups were analyzed. Binary logistic regression was used to establish a multiparameter model for predicting EGFR mutation, and ROC curve was used to compare the diagnostic efficiency. Independent predictors of the Ki67 index were screened using multiple linear regression analysis.

Results

The poorly differentiated group was more likely to have large-diameter, solid foci, pleural pulling signs, and vacuolar signs compared with other groups (all P < 0.05). The differences in metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in all three different differentiated groups were statistically significant compared to the other parameters (all P < 0.05). The PET/CT regression model predicted EGFR mutations with an AUC of 0.820 and was higher than other models; the sensitivity, specificity, positive predictive value, and negative predictive value for discriminating EGFR mutations were 84.74%, 70.37%, 75.76%, and 80.85%, respectively. PET/CT multiple linear regression analysis showed that vascular convergence, SUVpeak, MTV, and TLG explaining 62.0% changes in Ki67 (R² = 0.620). SUVpeak, MTV, and TLG (r = 0.580, r = 0.662, and r = 0.680, all P < 0.001) were all strongly correlated with increased Ki67 index.

Conclusion

MTV and TLG can better identify the degree of ILA differentiation compared to CT and other PET parameters. The nomogram constructed by multimodal PET/CT parameters can better dynamically monitor the changes of EGFR status and Ki67 index.

目的我们研究了基于PET/CT的多模态参数在预测浸润性肺腺癌（ILA）分化程度和表皮生长因子受体（EGFR）突变方面的价值，并评估了基于PET/CT的多模态参数与Ki67之间的相关性：我们回顾性收集了113例接受PET/CT检查的ILA患者，分析了不同分化组间PET/CT多模态参数的差异。利用二元逻辑回归建立预测表皮生长因子受体突变的多参数模型，并利用ROC曲线比较诊断效率。采用多元线性回归分析筛选了Ki67指数的独立预测因子：与其他组相比，分化不良组更容易出现大直径、实性病灶、胸膜牵拉征和空泡征（均为 P 2 = 0.620）。SUVpeak、MTV 和 TLG（r = 0.580、r = 0.662 和 r = 0.680，均为 P 结论：与 CT 和其他 PET 参数相比，MTV 和 TLG 能更好地识别 ILA 的分化程度。由 PET/CT 多模态参数构建的提名图能更好地动态监测表皮生长因子受体状态和 Ki67 指数的变化。

{"title":"A Nomogram for the Prediction of Invasiveness in Invasive Pulmonary Adenocarcinoma on the Basis of Multimodal PET/CT Parameters","authors":"Ning Ma , Hongyan Du , Jun Li , Zhan Li , Shiyi Wang , Duxia Yu , Yu Wu , Ying Shan , Mengjie Dong","doi":"10.1016/j.acra.2024.10.019","DOIUrl":"10.1016/j.acra.2024.10.019","url":null,"abstract":"<div><h3>Objective</h3><div>We investigated the value of PET/CT-based multimodal parameters in predicting the degree of differentiation and epidermal growth factor receptor (EGFR) mutations in invasive lung adenocarcinoma (ILA) and assessed the correlation between PET/CT-based multimodal parameters and Ki67.</div></div><div><h3>Methods</h3><div>We retrospectively collected 113 patients with ILA who underwent PET/CT examination, and differences in PET/CT multimodal parameters between different differentiation groups were analyzed. Binary logistic regression was used to establish a multiparameter model for predicting EGFR mutation, and ROC curve was used to compare the diagnostic efficiency. Independent predictors of the Ki67 index were screened using multiple linear regression analysis.</div></div><div><h3>Results</h3><div>The poorly differentiated group was more likely to have large-diameter, solid foci, pleural pulling signs, and vacuolar signs compared with other groups (all <em>P</em> < 0.05). The differences in metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in all three different differentiated groups were statistically significant compared to the other parameters (all <em>P</em> < 0.05). The PET/CT regression model predicted EGFR mutations with an AUC of 0.820 and was higher than other models; the sensitivity, specificity, positive predictive value, and negative predictive value for discriminating EGFR mutations were 84.74%, 70.37%, 75.76%, and 80.85%, respectively. PET/CT multiple linear regression analysis showed that vascular convergence, SUVpeak, MTV, and TLG explaining 62.0% changes in Ki67 (R<sup>2</sup> = 0.620). SUVpeak, MTV, and TLG (r = 0.580, r = 0.662, and r = 0.680, all <em>P</em> < 0.001) were all strongly correlated with increased Ki67 index.</div></div><div><h3>Conclusion</h3><div>MTV and TLG can better identify the degree of ILA differentiation compared to CT and other PET parameters. The nomogram constructed by multimodal PET/CT parameters can better dynamically monitor the changes of EGFR status and Ki67 index.</div></div>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"32 3","pages":"Pages 1696-1705"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548783","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}

引用次数: 0

CT-Defined Coronary Artery Calcification as a Prognostic Marker for Overall Survival in Lung Cancer: A Systematic Review and Meta-analysis CT 定义的冠状动脉钙化是肺癌患者总生存期的预后标志：系统回顾与元分析》。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.10.046

Hans-Jonas Meyer MD , Andreas Wienke PhD , Alexey Surov MD

Rationale and Objectives

Coronary artery calcification (CAC) can be quantified by computed tomography (CT). It is an important predictive and prognostic imaging marker for cardiovascular disease. The prognostic role for CAC in oncological patients is provided in preliminary studies, especially in lung cancer patients. The aim of the present study was to establish the effect of CAC score on overall survival (OS) in lung cancer patients based on the published literature

Materials and Methods

Literature databases were screened for papers analyzing the association between CAC and overall survival in lung cancer patients up to June 2024. The primary endpoint of the present systematic review was the OS. Overall, seven studies were suitable for the analysis and were included.

Results

The included studies comprised 2292 patients undergoing curative treatment. The pooled hazard ratio for the association between CAC score and OS was HR = 1.42 (95% CI = (1.19; 1.69), p < 0.0001) in the univariable analysis and HR = 1.56 (95% CI = (1.25; 1.94), p < 0.0001) in the multivariable analysis. The pooled odds ratio for the association between CAC score and major cardiovascular events was OR = 1.97 (95% CI = (1.24; 3.13)], p = 0.004.

Conclusion

CT-defined CAC has a meaningful impact on overall survival and prediction of major cardiovascular events in lung cancer patients undergoing curative treatment. The sole presence of CAC on staging CT should be reported as an important prognostic marker in these patients.

理由和目标：冠状动脉钙化（CAC）可通过计算机断层扫描（CT）进行量化。它是心血管疾病的重要预测和预后成像标记。初步研究表明，CAC 对肿瘤患者，尤其是肺癌患者有预后作用。本研究的目的是根据已发表的文献，确定 CAC 评分对肺癌患者总生存期（OS）的影响材料与方法：在文献数据库中筛选了截至 2024 年 6 月分析 CAC 与肺癌患者总生存期之间关系的论文。本系统综述的主要终点是 OS。共有七项研究适合进行分析并被纳入：结果：纳入的研究包括2292名接受根治性治疗的患者。CAC评分与OS之间的汇总危险比为HR= 1.42（95% CI=（1.19；1.69），P 结论：CAC评分与OS之间的关联性是非常重要的：CT定义的CAC对接受根治性治疗的肺癌患者的总生存期和主要心血管事件的预测有重要影响。在分期 CT 上仅出现 CAC 就应作为这些患者的重要预后指标。

{"title":"CT-Defined Coronary Artery Calcification as a Prognostic Marker for Overall Survival in Lung Cancer: A Systematic Review and Meta-analysis","authors":"Hans-Jonas Meyer MD , Andreas Wienke PhD , Alexey Surov MD","doi":"10.1016/j.acra.2024.10.046","DOIUrl":"10.1016/j.acra.2024.10.046","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>Coronary artery calcification (CAC) can be quantified by computed tomography (CT). It is an important predictive and prognostic imaging marker for cardiovascular disease. The prognostic role for CAC in oncological patients is provided in preliminary studies, especially in lung cancer patients. The aim of the present study was to establish the effect of CAC score on overall survival (OS) in lung cancer patients based on the published literature</div></div><div><h3>Materials and Methods</h3><div>Literature databases were screened for papers analyzing the association between CAC and overall survival in lung cancer patients up to June 2024. The primary endpoint of the present systematic review was the OS. Overall, seven studies were suitable for the analysis and were included.</div></div><div><h3>Results</h3><div>The included studies comprised 2292 patients undergoing curative treatment. The pooled hazard ratio for the association between CAC score and OS was HR= 1.42 (95% CI=(1.19; 1.69), p < 0.0001) in the univariable analysis and HR= 1.56 (95% CI=(1.25; 1.94), p < 0.0001) in the multivariable analysis. The pooled odds ratio for the association between CAC score and major cardiovascular events was OR= 1.97 (95% CI=(1.24; 3.13)], p = 0.004.</div></div><div><h3>Conclusion</h3><div>CT-defined CAC has a meaningful impact on overall survival and prediction of major cardiovascular events in lung cancer patients undergoing curative treatment. The sole presence of CAC on staging CT should be reported as an important prognostic marker in these patients.</div></div>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"32 3","pages":"Pages 1306-1312"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142677772","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}

引用次数: 0

Early Detection of Breast Cancer in MRI Using AI 利用人工智能在核磁共振成像中早期检测乳腺癌。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.10.014

Lukas Hirsch , Yu Huang , Hernan A. Makse , Danny F. Martinez , Mary Hughes , Sarah Eskreis-Winkler , Katja Pinker , Elizabeth A. Morris , Lucas C. Parra , Elizabeth J. Sutton

Rationale and Objectives

To develop and evaluate an AI algorithm that detects breast cancer in MRI scans up to one year before radiologists typically identify it, potentially enhancing early detection in high-risk women.

Materials and Methods

A convolutional neural network (CNN) AI model, pre-trained on breast MRI data, was fine-tuned using a retrospective dataset of 3029 MRI scans from 910 patients. These contained 115 cancers that were diagnosed within one year of a negative MRI. The model aimed to identify these cancers, with the goal of predicting cancer development up to one year in advance. The network was fine-tuned and tested with 10-fold cross-validation. Mean age of patients was 52 years (range, 18–88 years), with average follow-up of 4.3 years (range 1–12 years).

Results

The AI detected cancers one year earlier with an area under the ROC curve of 0.72 (0.67–0.76). Retrospective analysis by a radiologist of the top 10% highest risk MRIs as ranked by the AI could have increased early detection by up to 30%. (35/115, CI:22.2–39.7%, 30% sensitivity). A radiologist identified a visual correlate to biopsy-proven cancers in 83 of prior-year MRIs (83/115, CI: 62.1–79.4%). The AI algorithm identified the anatomic region where cancer would be detected in 66 cases (66/115, CI:47.8–66.5%); with both agreeing in 54 cases (54/115, CI:%37.5–56.4%).

Conclusion

This novel AI-aided re-evaluation of "benign" breasts shows promise for improving early breast cancer detection with MRI. As datasets grow and image quality improves, this approach is expected to become even more impactful.

原理与目标开发并评估一种人工智能算法，该算法可在放射科医生通常发现乳腺癌之前一年从核磁共振扫描中检测出乳腺癌，从而提高高危女性的早期检测率：在乳腺核磁共振成像数据上预先训练了卷积神经网络（CNN）人工智能模型，并使用来自 910 名患者的 3029 次核磁共振成像扫描的回顾性数据集对该模型进行了微调。其中有 115 例癌症是在核磁共振成像呈阴性后一年内确诊的。该模型旨在识别这些癌症，目的是提前一年预测癌症的发展。对网络进行了微调，并通过 10 倍交叉验证进行了测试。患者的平均年龄为52岁（18-88岁不等），平均随访时间为4.3年（1-12年不等）：结果：人工智能提前一年发现癌症，ROC 曲线下面积为 0.72（0.67-0.76）。由放射科医生对人工智能排名前 10%的高风险 MRI 进行回顾性分析，可将早期发现率提高 30%。(35/115，CI:22.2-39.7%，灵敏度为 30%）。在 83 例前一年的 MRI 中，放射科医生发现了与活检证实的癌症有视觉关联的病灶（83/115，CI：62.1-79.4%）。人工智能算法在66个病例（66/115，CI：47.8-66.5%）中确定了可检测到癌症的解剖区域；在54个病例（54/115，CI：%37.5-56.4%）中，两者的结果一致：这种新颖的人工智能辅助重新评估 "良性 "乳房的方法有望提高磁共振成像的早期乳腺癌检测水平。随着数据集的增加和图像质量的提高，这种方法有望发挥更大的作用。

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引用次数: 0

T2WI and ADC radiomics combined with a nomogram based on clinicopathologic features to quantitatively predict microsatellite instability in colorectal cancer T2WI和ADC放射组学与基于临床病理特征的提名图相结合，定量预测结直肠癌的微卫星不稳定性。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.10.002

Leping Peng , Xiuling Zhang , Yuanhui Zhu , Liuyan Shi , Kai Ai , Gang Huang , Wenting Ma , Zhaokun Wei , Ling Wang , Yaqiong Ma , Lili Wang

Rationale and Objectives

Microsatellite instability (MSI) stratification can guide the clinical management of patients with colorectal cancer (CRC). This study aimed to establish a radiomics model for predicting the MSI status of patients with CRC before treatment.

Materials and Methods

This retrospective study was performed on 366 patients diagnosed with CRC who underwent preoperative magnetic resonance imaging (MRI) and immunohistochemical staining between February 2016 and September 2023. The participants were divided randomly into training and testing cohorts in a 7:3 ratio. The tumor volume of interest (VOI) was manually delineated on T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) sequences using 3D Slicer software, and radiomics features were extracted. Feature selection was performed using the least absolute shrinkage and selection operator method. A radiomics nomogram was developed using multiple logistic regression, and the predictive performance of the models was evaluated and compared using receiver operating characteristic curves. The calibration curve, clinical decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical application value of the model.

Results

The radiomics normogram combined with history of chronic enteritis, tumor location, MR–reported inflammatory response, D2–40, carcinoembryonic antigen, tumor protein 53, and monocyte was an excellent predictive tool. The area under the curve for the training and testing cohorts were 0.927 and 0.984, respectively. The DCA and CIC demonstrated favorable clinical application and net benefit.

Conclusions

A radiomics nomogram based on T2WI and ADC sequences and clinicopathologic features can effectively and noninvasively predict the MSI status in CRC. This approach helps clinicians in stratifying CRC patients and making clinical decisions for personalized treatment.

理由和目标：微卫星不稳定性（MSI）分层可指导结直肠癌（CRC）患者的临床治疗。本研究旨在建立一个放射组学模型，用于在治疗前预测 CRC 患者的 MSI 状态：这项回顾性研究的对象是在2016年2月至2023年9月期间接受术前磁共振成像（MRI）和免疫组化染色的366名确诊为CRC的患者。参与者按 7:3 的比例随机分为训练组和测试组。使用 3D Slicer 软件在 T2 加权成像（T2WI）和表观扩散系数（ADC）序列上手动划定感兴趣肿瘤体积（VOI），并提取放射组学特征。特征选择采用最小绝对收缩和选择算子法。使用多重逻辑回归法建立了放射组学提名图，并使用接收者操作特征曲线对模型的预测性能进行了评估和比较。校准曲线、临床决策曲线分析（DCA）和临床影响曲线（CIC）用于评估模型的临床应用价值：放射组学标准图与慢性肠炎病史、肿瘤位置、MR报告的炎症反应、D2-40、癌胚抗原、肿瘤蛋白53和单核细胞相结合，是一种很好的预测工具。训练组和测试组的曲线下面积分别为 0.927 和 0.984。DCA和CIC显示了良好的临床应用和净效益：结论：基于 T2WI 和 ADC 序列以及临床病理特征的放射组学提名图可以有效、无创地预测 CRC 的 MSI 状态。这种方法有助于临床医生对 CRC 患者进行分层，并做出个性化治疗的临床决策。

{"title":"T2WI and ADC radiomics combined with a nomogram based on clinicopathologic features to quantitatively predict microsatellite instability in colorectal cancer","authors":"Leping Peng , Xiuling Zhang , Yuanhui Zhu , Liuyan Shi , Kai Ai , Gang Huang , Wenting Ma , Zhaokun Wei , Ling Wang , Yaqiong Ma , Lili Wang","doi":"10.1016/j.acra.2024.10.002","DOIUrl":"10.1016/j.acra.2024.10.002","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>Microsatellite instability (MSI) stratification can guide the clinical management of patients with colorectal cancer (CRC). This study aimed to establish a radiomics model for predicting the MSI status of patients with CRC before treatment.</div></div><div><h3>Materials and Methods</h3><div>This retrospective study was performed on 366 patients diagnosed with CRC who underwent preoperative magnetic resonance imaging (MRI) and immunohistochemical staining between February 2016 and September 2023. The participants were divided randomly into training and testing cohorts in a 7:3 ratio. The tumor volume of interest (VOI) was manually delineated on T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) sequences using 3D Slicer software, and radiomics features were extracted. Feature selection was performed using the least absolute shrinkage and selection operator method. A radiomics nomogram was developed using multiple logistic regression, and the predictive performance of the models was evaluated and compared using receiver operating characteristic curves. The calibration curve, clinical decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical application value of the model.</div></div><div><h3>Results</h3><div>The radiomics normogram combined with history of chronic enteritis, tumor location, MR–reported inflammatory response, D2–40, carcinoembryonic antigen, tumor protein 53, and monocyte was an excellent predictive tool. The area under the curve for the training and testing cohorts were 0.927 and 0.984, respectively. The DCA and CIC demonstrated favorable clinical application and net benefit.</div></div><div><h3>Conclusions</h3><div>A radiomics nomogram based on T2WI and ADC sequences and clinicopathologic features can effectively and noninvasively predict the MSI status in CRC. This approach helps clinicians in stratifying CRC patients and making clinical decisions for personalized treatment.</div></div>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"32 3","pages":"Pages 1431-1450"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142569856","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}

引用次数: 0

Prognostic value of extracellular volume fraction in myocardial infarction and myocardial infarction with nonobstructive coronary arteries: A multicenter study 细胞外体积分数对心肌梗死和冠状动脉非阻塞性心肌梗死的预后价值：一项多中心研究。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.11.015

Bowen Li MD , Yan Gao MD , Jian Wang MD , Runze Zhu MD , Shifeng Yang MD, PhD , Congshan Ji MD, PhD , Ying Wang MD , Ximing Wang MD, PhD , Hui Gu MD, PhD

Rationale and Objectives

The aim of the present retrospective study was to evaluate the prognostic role of the extracellular volume fraction (ECV) in patients with myocardial infarction (MI) and myocardial infarction with nonobstructive coronary arteries (MINOCA). The present study hypothesized that ECV is associated with major adverse cardiovascular events (MACEs) in MI and MINOCA patients.

Materials and Methods

Cardiac magnetic resonance (CMR) imaging was performed on 351 consecutive patients (mean age: 58 ± 12 years; 252 [71.8%] males) who were diagnosed with MI between October 2015 and November 2023. From CMR imaging, the extent of late gadolinium enhancement (LGE), native T1 and ECV were derived. Patients were categorized into groups according to the degree of coronary artery stenosis, namely, patients with MINOCA and patients with obstructive MI. Follow-up was performed to assess MACEs.

Results

The final cohort consisted of 61 MINOCA patients and 290 obstructive MI patients. During a mean follow-up of 27 ± 16 months, there was no statistically significant difference in the incidence of MACEs between patients with MINOCA and those with obstructive MI, and the two groups of patients had similar ECVs (32.2 ± 3.6 vs. 32.3 ± 6.0, p = 0.864). According to the multivariate Cox regression, ECV was an independent predictor of MACEs (HR: 1.13; p < 0.001) and significantly improved the prognostic value of the baseline multivariate models (C-statistic improvement: 0.816–0.864, p = 0.001). Similarly, ECV maintained an independent association with MACEs in the MINOCA (HR: 1.35; p < 0.001) and obstructive MI (HR: 1.13; p < 0.001) groups.

Conclusion

In MI and MINOCA patients, ECV is an independent predictor of MACEs. MINOCA is not a benign disease, and its long-term prognosis is as poor as that of patients with obstructive MI.

依据和目的：本回顾性研究旨在评估细胞外体积分数（ECV）在心肌梗死（MI）和冠状动脉非阻塞性心肌梗死（MINOCA）患者中的预后作用。本研究假设 ECV 与 MI 和 MINOCA 患者的主要不良心血管事件（MACE）有关：对 2015 年 10 月至 2023 年 11 月期间被诊断为心肌梗死的 351 名连续患者（平均年龄：58 ± 12 岁；252 名[71.8%]男性）进行了心脏磁共振（CMR）成像。通过 CMR 成像，得出了晚期钆增强 (LGE)、原生 T1 和 ECV 的程度。根据冠状动脉狭窄程度将患者分为两组，即 MINOCA 患者和阻塞性 MI 患者。进行随访以评估MACEs：最终结果：61 名 MINOCA 患者和 290 名阻塞性 MI 患者组成了最终队列。在平均 27 ± 16 个月的随访期间，MINOCA 患者和梗阻性心肌梗死患者的 MACE 发生率没有明显的统计学差异，两组患者的 ECV 值相似（32.2 ± 3.6 vs. 32.3 ± 6.0，p = 0.864）。根据多变量 Cox 回归，ECV 是 MACEs 的独立预测因子（HR：1.13；P 结论：ECV 是 MACEs 的独立预测因子：在心肌梗死和 MINOCA 患者中，ECV 是 MACEs 的独立预测因子。MINOCA 并非良性疾病，其长期预后与梗阻性 MI 患者一样差。

{"title":"Prognostic value of extracellular volume fraction in myocardial infarction and myocardial infarction with nonobstructive coronary arteries: A multicenter study","authors":"Bowen Li MD , Yan Gao MD , Jian Wang MD , Runze Zhu MD , Shifeng Yang MD, PhD , Congshan Ji MD, PhD , Ying Wang MD , Ximing Wang MD, PhD , Hui Gu MD, PhD","doi":"10.1016/j.acra.2024.11.015","DOIUrl":"10.1016/j.acra.2024.11.015","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>The aim of the present retrospective study was to evaluate the prognostic role of the extracellular volume fraction (ECV) in patients with myocardial infarction (MI) and myocardial infarction with nonobstructive coronary arteries (MINOCA). The present study hypothesized that ECV is associated with major adverse cardiovascular events (MACEs) in MI and MINOCA patients.</div></div><div><h3>Materials and Methods</h3><div>Cardiac magnetic resonance (CMR) imaging was performed on 351 consecutive patients (mean age: 58 ± 12 years; 252 [71.8%] males) who were diagnosed with MI between October 2015 and November 2023. From CMR imaging, the extent of late gadolinium enhancement (LGE), native T1 and ECV were derived. Patients were categorized into groups according to the degree of coronary artery stenosis, namely, patients with MINOCA and patients with obstructive MI. Follow-up was performed to assess MACEs.</div></div><div><h3>Results</h3><div>The final cohort consisted of 61 MINOCA patients and 290 obstructive MI patients. During a mean follow-up of 27 ± 16 months, there was no statistically significant difference in the incidence of MACEs between patients with MINOCA and those with obstructive MI, and the two groups of patients had similar ECVs (32.2 ± 3.6 vs. 32.3 ± 6.0, <em>p</em> = 0.864). According to the multivariate Cox regression, ECV was an independent predictor of MACEs (HR: 1.13; <em>p</em> < 0.001) and significantly improved the prognostic value of the baseline multivariate models (C-statistic improvement: 0.816–0.864, <em>p</em> = 0.001). Similarly, ECV maintained an independent association with MACEs in the MINOCA (HR: 1.35; <em>p</em> < 0.001) and obstructive MI (HR: 1.13; <em>p</em> < 0.001) groups.</div></div><div><h3>Conclusion</h3><div>In MI and MINOCA patients, ECV is an independent predictor of MACEs. MINOCA is not a benign disease, and its long-term prognosis is as poor as that of patients with obstructive MI.</div></div>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":"32 3","pages":"Pages 1313-1323"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142696056","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}

引用次数: 0

Comparative Efficacy of Non-contrast vs. Contrast-enhanced CT Radiomics in Predicting Coronary Artery Plaques Among Patients with Low Agatston Scores 非对比与增强CT放射组学预测低Agatston评分患者冠状动脉斑块的比较疗效。

IF 3.8 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2025-03-01 DOI: 10.1016/j.acra.2024.11.063

Jianhua Liang , Congcong Lin , Hongliang Qi , Yongkai Lin , Liwei Deng , Jieyao Wu , Chunyang Yang , Zhiyuan He , Jiaqing Li , Hanwei Li , Debin Hu , Hongwen Chen , Yuanzhang Li

Rationale and Objectives

Patients with a low Agatston score often present with clinical signs and symptoms suggestive of coronary artery disease, despite having minimal calcium deposits. This study aimed to compare the efficacy of low-dose non-contrast cardiac CT with coronary computed tomography angiography (CCTA) in pericoronary adipose tissue (PCAT) radiomics for predicting coronary artery plaques, using CCTA as the reference standard.

Materials and Methods

This retrospective study analyzed 459 patients with suspected coronary artery disease and a coronary artery calcium score < 100 Agatston units, who were treated between June 2021 and December 2023 at a tertiary hospital. Three predictive models for coronary artery plaques were developed: (1) a clinical factor model, (2) a hybrid model integrating clinical factors and CT PCAT radiomics, and (3) a hybrid model integrating clinical factors and CCTA PCAT radiomics. Multivariable logistic regression and receiver operating characteristic curve evaluations were performed to develop and validate predictive models.

Results

Both hybrid models showed significant correlations in the training set (r = 0.890, P < 0.001) and the validation set (r = 0.920, P < 0.001). The mean agreement in the training set is 0, with 3.42% (11/322) of the data points outside the 95% CI (−0.18–0.18, P < 0.001). The mean agreement in the validation set is −0.244, with 6.57% (9/137) of the data points outside the 95% CI (−0.443–0.045, P < 0.001).

Conclusions

Non-contract CT PCAT radiomics showed comparable efficacy to CCTA PCAT radiomics in predicting coronary artery plaques among patients with low Agatston scores.

理由和目的：Agatston评分低的患者通常表现为提示冠状动脉疾病的临床体征和症状，尽管有少量的钙沉积。本研究旨在比较低剂量非对比心脏CT与冠状动脉计算机断层血管造影（CCTA）在冠状动脉周围脂肪组织（PCAT）放射组学中预测冠状动脉斑块的疗效，以CCTA为参考标准。材料和方法：本回顾性研究分析了2021年6月至2023年12月在某三级医院就诊的459例冠状动脉疾病疑似患者，冠状动脉钙评分< 100 Agatston单位。建立了三种冠状动脉斑块预测模型：(1)临床因素模型，(2)临床因素与CT PCAT放射组学的混合模型，(3)临床因素与CCTA PCAT放射组学的混合模型。采用多变量逻辑回归和受试者工作特征曲线评估来建立和验证预测模型。结果：两种混合模型在训练集（r = 0.890, P < 0.001）和验证集（r = 0.920, P < 0.001）上均具有显著相关性。训练集中的平均一致性为0，有3.42%（11/322）的数据点在95% CI之外（-0.18-0.18,P < 0.001）。验证集中的平均一致性为-0.244，有6.57%（9/137）的数据点在95% CI之外（-0.443-0.045,P < 0.001）。结论：非收缩CT PCAT放射组学与CCTA PCAT放射组学在预测低Agatston评分患者的冠状动脉斑块方面具有相当的疗效。

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引用次数: 0