Academic Radiology最新文献_第8页

Evaluation of a Virtual Reality CT-Guided Focal Liver Biopsy Module 虚拟现实ct引导局灶性肝活检模块的评估。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.09.050

Blaire K. Rikard BS, MMSc-MEd , David N. Williams PhD , Kate Donovan PhD, MBA, MS , Ivan Dimov MD, MSc , Minh-Thuy Nguyen MD , Anjali Dasari , Jonathan G. Martin MD , Raul N. Uppot MD

Rationale and Objectives

This study evaluated a novel, virtual reality (VR) computed tomography (CT)-guided focal liver biopsy module for improving residents’ knowledge and confidence.

Materials and Methods

Interventional radiology (IR) residents (n = 18) were divided into a control group (PGY-1s) and an intervention group (PGY-2s and PGY-3s). All participants completed pre-, post-, and one-month surveys of confidence and a test of knowledge. The intervention group completed the CT-guided focal liver biopsy VR module between surveys on two occasions. When the intervention group performed the procedure in the VR environment, procedure length, number of scans, and accuracy of needle placement were recorded. Exam scores, confidence ratings, and VR headset performance metrics were analyzed using Wilcoxon signed-rank tests.

Results

The control group demonstrated no significant changes at any timepoint. The intervention group demonstrated significant knowledge gains pre- to post-survey (p = 0.03) with no significant change at follow-up (p = 0.09). Confidence in ordering steps and performing the procedure increased significantly pre- to post- (p = 0.03 vs p = 0.02) and pre- to final- (p = 0.01 vs p = 0.01). VR needle placement accuracy was stable at one month (p = 0.64) though scan counts (p = 0.16) and completion times (p = 0.03) increased.

Conclusion

The VR module improved residents’ knowledge and confidence with gains remaining stable at one month, despite a decline in VR-specific motor skills. These findings demonstrate the benefits of VR as a teaching tool.

基本原理和目的：本研究评估了一种新型的、虚拟现实（VR）计算机断层扫描（CT）引导的局灶性肝活检模块，以提高居民的知识和信心。材料与方法：将18名介入放射科住院医师分为对照组（pgy -1）和干预组（pgy -2和pgy -3）。所有的参与者都完成了一个月前、一个月后和一个月的信心调查和知识测试。干预组两次在调查间隙完成ct引导的局灶肝活检VR模块。当干预组在虚拟现实环境下进行手术时，记录手术时间、扫描次数和针头放置的准确性。使用Wilcoxon符号秩检验分析考试分数、信心评级和VR耳机性能指标。结果：对照组各时间点无明显变化。干预组在调查前后有显著的知识增益（p=0.03），随访时无显著变化（p=0.09）。排序步骤和执行程序的信心在术前至术后（p=0.03 vs p=0.02）和术前至术后（p=0.01 vs p=0.01）显著增加。尽管扫描次数（p=0.16）和完成时间（p=0.03）增加，但VR针头放置精度在1个月时稳定（p=0.64）。结论：尽管VR特定的运动技能有所下降，但VR模块提高了居民的知识和信心，并且在一个月后收益保持稳定。这些发现证明了虚拟现实作为教学工具的好处。

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引用次数: 0

18F-FDG PET Radiomic Analysis to Predict Occult Liver Metastases of Pancreatic Ductal Adenocarcinoma 18F-FDG PET放射组学分析预测胰腺导管腺癌隐匿性肝转移。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.10.024

Jingtao Chen , Zhiang Zhang , Ze Jin , Pengcheng Ma , Zhichen Jiang , Chao Lu , Qicong Zhu , Yiping Mou , Weiwei Jin

Rationale and Objectives

To develop and validate a preoperative predictive model for occult liver metastases (OLM) in pancreatic ductal adenocarcinoma (PDAC) using fluorine-18 fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) radiomics.

Material and Methods

This retrospective study included 117 patients with PDAC who underwent preoperative ¹⁸F-FDG PET/CT and surgical resection. OLM was defined as liver metastases detected during surgery or within 6 months postoperatively. A fully automated pancreas segmentation strategy was employed, and radiomic features were extracted from PET images. Three machine learning models (logistic regression, multilayer perceptron, and adaptive boosting) were developed and compared to a clinical model incorporating jaundice, metabolic tumor diameter, and maximum standardized uptake value. A fusion model integrating PET radiomic features with clinical variables was subsequently constructed. Model performance was evaluated using receiver operating characteristic curves and decision curve analysis.

Results

Among the 117 patients, 15.4% (n = 18) had OLM. The logistic regression radiomics model demonstrated favorable predictive performance (area under the curve [AUC]: 0.936 in the testing cohort) compared to a clinical model based on conventional parameters (AUC: 0.755, P<0.001). Subgroup analyses confirmed robustness across different jaundice statuses, tumor locations, and carbohydrate antigen 19–9 levels. The fusion model that integrates radiomic and clinical features provides a comprehensive tool for preoperative risk stratification, with the potential to guide personalized treatment strategies.

Conclusion

In this exploratory study, the ¹⁸F-FDG PET radiomics model demonstrates promising predictive performance for OLM in PDAC, outperforming conventional clinical parameters. It shows potential as a valuable tool for preoperative risk stratification and may help inform personalized treatment planning.

基本原理和目的：利用氟-18氟脱氧葡萄糖正电子发射断层扫描（18F-FDG PET）放射组学技术，建立并验证胰腺导管腺癌（PDAC）隐匿性肝转移（OLM）的术前预测模型。材料和方法：本回顾性研究纳入117例术前行18F-FDG PET/CT和手术切除的PDAC患者。OLM定义为手术中或术后6个月内发现的肝转移。采用全自动胰腺分割策略，从PET图像中提取放射学特征。开发了三种机器学习模型（逻辑回归、多层感知器和自适应增强），并将其与包含黄疸、代谢性肿瘤直径和最大标准化摄取值的临床模型进行了比较。随后构建了PET放射学特征与临床变量的融合模型。采用受试者工作特征曲线和决策曲线分析对模型性能进行评价。结果：117例患者中，OLM发生率为15.4% （n=18）。与基于常规参数的临床模型（AUC: 0.755）相比，logistic回归放射组学模型具有较好的预测效果（测试队列中曲线下面积[AUC]: 0.936）。结论：在本探索性研究中，18F-FDG PET放射组学模型对PDAC中OLM的预测效果较好，优于常规临床参数。它显示了作为术前风险分层的有价值的工具的潜力，并可能有助于告知个性化的治疗计划。

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引用次数: 0

Individualizing Radiation Risk in Lung Cancer Screening: Towards Precision Dosimetry 肺癌筛查中的个体化辐射风险：迈向精确剂量学。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.10.003

Harleen Kaur, Ritu R. Gill MD, MPH

引用次数: 0

Virtual Clinical Shadowing: The Future of Medical Student Education Through Telemedicine 虚拟临床阴影：医学生远程医疗教育的未来。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.05.030

Minahil Cheema , Omer A. Awan MD, MPH, CIIP

引用次数: 0

Deep Learning Radiomic Signature Predicts the Overall Survival of Patients with Lung Adenocarcinoma by Reflecting the Tumor Heterogeneity and Microenvironment 深度学习放射学特征通过反映肿瘤异质性和微环境来预测肺腺癌患者的总生存期。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.09.033

Chunlei Dai , Bo Huang , Zhe Yu , Jingwei Xu , Jian Li , Jian Yang

Rationale and Objectives

The need for prediction of overall survival (OS) in patients with lung adenocarcinoma (LUAD) has been increasingly recognized. We aimed to generate a computed tomography-derived radiomic signature for predicting prognosis in LUAD patients, and then explored the relationship between radiomic features and tumor heterogeneity and microenvironment.

Materials and Methods

Data of 306 eligible LUAD patients from three institutions were obtained between January 2019 and January 2024. The mainstream Residual Network 50 (ResNet50) was used to develop an image-based deep learning radiomic signature (DLRS). We developed a clinical model and calculated the conventional radiomics score using pyradiomics package. An external cohort from a public database called The Cancer Imaging Archive was obtained for further validation. We performed the time-dependent receiver operator characteristic curve to assess the performance of the models. We divided the whole dataset into high and low-score groups with the help of the DLRS. The differences in tumor heterogeneity and microenvironment between different score groups were investigated using the sequencing data from the corresponding LUAD cohort from the Cancer Genome Atlas.

Results

In the test cohort, the DLRS outperformed the conventional radiomics score and clinical model, with the area under the curves (95%CI) for 1, 3, and 5-year OS of 0.912 (0.881–0.952), 0.851 (0.824–0.901), and 0.841 (0.807–0.878), respectively. Significant differences in survival time were observed between different groups stratified by this signature. It showed great discrimination, calibration, and clinical utility (all p<0.05). Distinct gene expression patterns were identified. The tumor heterogeneity and microenvironment significantly varied between different score groups.

Conclusion

The DLRS could effectively predict the prognosis of LUAD patients by reflecting the tumor heterogeneity and microenvironment.

理由和目的：预测肺腺癌（LUAD）患者总生存期（OS）的必要性已经越来越被认识到。我们的目的是生成一个计算机断层扫描衍生的放射组学特征来预测LUAD患者的预后，然后探索放射组学特征与肿瘤异质性和微环境之间的关系。材料与方法：2019年1月至2024年1月，来自三家机构的306例符合条件的LUAD患者的数据。使用主流的残余网络50 （ResNet50）来开发基于图像的深度学习放射特征（DLRS）。我们开发了一个临床模型，并使用放射组学包计算常规放射组学评分。为了进一步验证，我们从一个名为“癌症影像档案”的公共数据库中获得了一个外部队列。我们进行了随时间变化的接收算子特征曲线来评估模型的性能。在DLRS的帮助下，我们将整个数据集分为高分组和低分组。使用来自Cancer Genome Atlas的相应LUAD队列的测序数据，研究不同评分组之间肿瘤异质性和微环境的差异。结果：在测试队列中，DLRS优于常规放射组学评分和临床模型，1、3和5年OS的曲线下面积（95%CI）分别为0.912（0.881-0.952）、0.851（0.824-0.901）和0.841（0.807-0.878）。通过该特征分层的不同组之间观察到生存时间的显著差异。结论：DLRS可通过反映肿瘤异质性和微环境，有效预测LUAD患者的预后。

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引用次数: 0

Efficacy and Safety of Spontaneous Portosystemic Shunts Embolization for Hepatic Encephalopathy: A Meta-analysis 自发性门静脉分流栓塞治疗肝性脑病的疗效和安全性：一项荟萃分析。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.09.049

Xing Wang , Zhengyu Wang , Bohan Luo , Yong Lv , Guohong Han

Background & Aims

Spontaneous portosystemic shunt (SPSS) embolization represents a promising intervention for refractory hepatic encephalopathy (HE). This systematic review and meta-analysis evaluate the efficacy and safety of SPSS embolization in cirrhotic patients without transjugular intrahepatic portosystemic shunts (TIPS).

Methods

We systematically searched PubMed, Web of Science, Embase, and the Cochrane Library through June 12, 2024 to identify studies investigating SPSS embolization for HE. Meta-analysis was performed using fixed-effect or random-effects models to calculate clinical success (defined as HE remission), procedural success rates, and complication frequencies.

Results

Analysis of 10 retrospective studies encompassing 289 cirrhotic patients yielded the following pooled outcomes: hepatic encephalopathy remission rate of 83.1% (95% CI: 70.4%–93.1%), procedural success rate of 99.8% (95% CI: 98.3%–100%), and long-term adverse event rate of 42.9% (95% CI: 34.7%–51.4%). The predominant long-term complications included ascites (51.6% of complications), variceal progression (23.4%), and thrombosis (8.0%), while primary procedure-related adverse reactions were infection (37%) and fever (29%). Subgroup analyses demonstrated no statistically significant effect of etiology (p = 0.788) or shunt type (p = 0.271) on disease remission rates, but revealed significant differences between surgical approaches (p<0.001), with balloon-occluded retrograde transvenous obliteration (BRTO) showing the highest efficacy (97.4%–100%).

Conclusion

SPSS embolization demonstrates both high efficacy for refractory hepatic encephalopathy (83.1% remission rate) and exceptional procedural success (99.8%). Despite substantial long-term complications (42.9%, predominantly portal hypertension sequelae), current evidence from predominantly retrospective studies supports its consideration as a therapeutic option. Technique selection should be individualized pending further validation of BRTO's superiority.

背景与目的：自发性门系统分流（SPSS）栓塞是治疗难治性肝性脑病（HE）的一种有希望的干预手段。本系统综述和荟萃分析评估了SPSS栓塞治疗肝硬化患者无经颈静脉肝内门静脉系统分流术（TIPS）的有效性和安全性。方法：我们系统地检索PubMed、Web of Science、Embase和Cochrane Library，检索时间截止到2024年6月12日，以确定调查SPSS栓塞治疗HE的研究。采用固定效应或随机效应模型进行meta分析，计算临床成功率（定义为HE缓解）、手术成功率和并发症频率。结果：对包含289例肝硬化患者的10项回顾性研究的分析得出了以下汇总结果：肝性脑病缓解率为83.1% (95% CI: 70.4%-93.1%)，手术成功率为99.8% (95% CI: 98.3%-100%)，长期不良事件发生率为42.9% （95% CI: 34.7%-51.4%）。主要的长期并发症包括腹水（51.6%的并发症）、静脉曲张进展（23.4%）和血栓形成（8.0%），而主要的手术相关不良反应是感染（37%）和发烧（29%）。亚组分析显示，病因学（p=0.788）或分流管类型（p=0.271）对疾病缓解率没有统计学意义，但不同手术入路之间存在显著差异(p)。结论：SPSS栓塞治疗难治性肝性脑病疗效高（缓解率83.1%），手术成功率高（99.8%）。尽管有大量的长期并发症（42.9%，主要是门脉高压后遗症），目前主要来自回顾性研究的证据支持将其作为一种治疗选择。在进一步验证BRTO的优势之前，技术选择应该个性化。

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引用次数: 0

Prognostic Value of Pseudotime from Texture Parameters of [18F]fluorodeoxyglucose PET/CT in Resectable Pancreatic Ductal Adenocarcinoma [18F]氟脱氧葡萄糖PET/CT纹理参数伪时间对可切除胰导管腺癌的预后价值。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.10.016

Wonseok Whi MD, PhD , Seung Hyup Hyun MD, PhD , Hyunjong Lee MD, PhD , Jeong Il Yu MD, PhD , Kwang Hyuck Lee MD, PhD , Jin Seok Heo MD, PhD , Joon Young Choi MD, PhD

Rationale and Objectives

This study evaluates the prognostic value of pseudotime derived from radiomics texture parameters on [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) images of resectable pancreatic ductal adenocarcinoma (PDAC) patients.

Materials and Methods

We retrospectively analyzed data from 711 patients who underwent FDG PET/CT before surgery. We extracted 56 radiomics features and calculated the pseudotime, a continuous metric estimating disease progression, using the Phenopath algorithm. Clinicopathologic features and other conventional PET parameters were also obtained. Correlation analyses were performed between the conventional PET parameters and pseudotime, and survival analysis was performed according to the clinicopathologic variables.

Results

Correlation analysis revealed that pseudotime correlates weakly with SUVmax and SUVmean and strongly with the metabolic tumor volume (MTV) and total lesion glycolysis (TLG). A multivariate survival analysis revealed that pseudotime is an independent predictor of disease-free survival (hazard ratio [HR] = 1.67, p < 0.001, c-index = 0.59), showing stronger prognostic performance than MTV (HR = 1.48, p = 0.009, c = 0.57) and TLG (HR = 1.39, p = 0.03, c = 0.56). When pseudotime was combined with TLG for risk stratification, the integrated model demonstrated the strongest prognostic separation among subgroups. Texture parameters related to homogeneity correlated positively with pseudotime, and those representing heterogeneity showed mixed correlations, highlighting the complexity of tumor biology.

Conclusion

Our findings indicate that pseudotime is a meaningful prognostic biomarker in resectable PDAC patients undergoing surgery, with stronger predictive power than established metabolic parameters. Stratification performance improved when it was combined with conventional markers.

基本原理和目的：本研究评估可切除胰导管腺癌（PDAC）患者的放射组学纹理参数所得伪时间的预后价值。材料和方法：我们回顾性分析了711例术前接受FDG PET/CT检查的患者的资料。我们提取了56个放射组学特征，并使用Phenopath算法计算了假时间，这是一种估计疾病进展的连续度量。同时获得临床病理特征及其他常规PET参数。常规PET参数与假时间进行相关性分析，根据临床病理变量进行生存分析。结果：相关分析显示，假时间与SUVmax和SUVmean相关性较弱，与代谢肿瘤体积（MTV）和病变总糖酵解（TLG）相关性较强。多变量生存分析显示，假时间是无病生存的独立预测因子（风险比[HR] = 1.67, p < 0.001, c-index = 0.59），比MTV （HR = 1.48, p = 0.009, c = 0.57）和TLG （HR = 1.39, p = 0.03, c = 0.56）表现出更强的预后效果。当假时间与TLG相结合进行风险分层时，综合模型显示亚组之间的预后分离最强。同质性相关的纹理参数与伪时间呈正相关，异质性相关的纹理参数与伪时间呈混合相关，凸显了肿瘤生物学的复杂性。结论：我们的研究结果表明，假时间是可切除的PDAC患者接受手术的有意义的预后生物标志物，比既定的代谢参数具有更强的预测能力。与常规标记物联合使用可提高分层效果。

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引用次数: 0

Clinical and Radiologic Contextualization of Automated BAC Quantification: A Commentary 自动BAC定量的临床和放射背景：评论。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.08.057

Ahmet Gürkan Erdemir MD , Gamze Durhan Assoc. Prof.

引用次数: 0

Dual-Vessel Microcirculation Imaging in Discriminating Non-Hodgkin Lymphoma Subtypes Using Super-Resolution Ultrasound: An Exploring Study 超分辨率超声双血管微循环成像鉴别非霍奇金淋巴瘤亚型的探索性研究。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.10.015

YiJie Dong MD , Qing Hua MD , ShuJun Xia MD , CongCong Yuan MD , Cheng Li MD , YanYan Song PhD , YuHang Zheng PhD , RuoLin Tao MD , ZhenHua Liu MD , YuLu Zhang MS , FangGang Wu MS , Wei Guo PhD , Yuan Tian MS , JianQiao Zhou MD

Background

Identifying the subtype of intranodal non-Hodgkin lymphoma (NHL) is crucial for clinical management.

Rationale and Objectives

To display dual-vessel systems (microvascular and microlymphatic circulation) of intranodal NHL using super-resolution ultrasound (SRUS), and explore the diagnostic performance of SRUS imaging for predicting B-cell and T-cell subtypes NHL.

Materials and Methods

A total of 49 patients with intranodal NHL underwent dual-vessel system SRUS imaging via intravenous and intra-lymph node routes. Least absolute shrinkage and selection operator (LASSO) regression, fitted the LASSO model and leave-one-out cross-validation (LOOCV) were used for model development and internal validation.

Results

Among the 49 patients, 40 were diagnosed with B-cell NHL and 9 with T-cell NHL. Variables including LDmax, LDLmin, and VCmin were selected and the logistic regression model achieved discrimination of B-cell and T-cell subtype of lymphoma with an AUC of 0.831 (0.594–0.969).

Conclusion

Dual-vessel SRUS imaging can display real time microvascular and microlymphatic circulation of intranodal NHL in physiological status. With quantitative analysis of SRUS offers a potential non-invasive diagnostic alternative in differentiating NHL subtype.

背景：确定结内非霍奇金淋巴瘤（NHL）亚型对临床治疗至关重要。原理和目的：利用超分辨率超声（SRUS）显示结内NHL的双血管系统（微血管和微淋巴循环），并探讨SRUS成像在预测b细胞和t细胞亚型NHL中的诊断性能。材料和方法：共有49例结内NHL患者通过静脉和淋巴结内途径行双血管系统SRUS成像。最小绝对收缩和选择算子（LASSO）回归，拟合LASSO模型和留一交叉验证（LOOCV）用于模型开发和内部验证。结果：49例患者中，40例诊断为b细胞NHL， 9例诊断为t细胞NHL。选取LDmax、LDLmin、VCmin等变量，logistic回归模型实现了b细胞和t细胞亚型淋巴瘤的区分，AUC为0.831（0.594-0.969）。结论：双血管SRUS成像可实时显示结内NHL生理状态下的微血管和微淋巴循环。SRUS的定量分析为区分NHL亚型提供了一种潜在的非侵入性诊断选择。

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引用次数: 0

A Predictive Model for False-Negative Results in Ultrasound-Guided Percutaneous Transthoracic Needle Lung Biopsy 超声引导下经皮经胸肺穿刺活检假阴性结果的预测模型。

IF 3.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Academic Radiology

Pub Date : 2026-01-01 DOI: 10.1016/j.acra.2025.10.023

Jiawei Yi , Ke Bi , Mengjun Shen , Kaiwen Wu , Xinyu Zhao , Runhe Xia , Yang Cong , Yi Li , Yin Wang

Objectives

This study aimed to develop a post-procedural predictive model for assessing the risk of false-negative results in ultrasound-guided percutaneous transthoracic needle lung biopsy (US-PTLB).

Material and Methods

Two prospective cohorts were designed for model development and validation. Patients scheduled for US-PTLB underwent B-mode ultrasound (B-US), color Doppler flow imaging (CDFI), ultrasound elastography, and contrast-enhanced ultrasound (CEUS) of the lesions, with the final diagnosis confirmed through comprehensive evaluation. Risk factors associated with false-negative results were identified, and multivariate logistic regression was used to construct the predictive model. The model's performance was further evaluated in an independent cohort to assess its impact on reducing the incidence of false-negative results through targeted interventions.

Results

The US-PTLB false-negative risk prediction model was constructed using data from 129 patients, of whom 35 (29.1%) were ultimately diagnosed with false-negative results. Predictors included age, lesion size, elasticity score, lesion necrosis, and enhancement intensity on CEUS. The model demonstrated excellent discrimination, with an area under the curve of 0.922, sensitivity of 88.6%, and specificity of 90.4%. Internal validation in 70 independently collected patients confirmed robust model performance. Application of the model in 423 patients, coupled with second biopsies for high-risk patients, led to a significant reduction in the incidence of false-negative results.

Conclusion

This predictive model, combining clinical parameters with multimodal ultrasound features, serves as a robust post-procedural tool for objectively assessing false-negative risk in ultrasound-guided percutaneous transthoracic needle lung biopsy. Its clinical application enables early risk stratification, minimizes false-negative rates, and enhances diagnostic precision.

目的：本研究旨在建立一种术后预测模型，用于评估超声引导下经皮经胸穿刺肺活检（US-PTLB）假阴性结果的风险。材料和方法：设计了两个前瞻性队列进行模型开发和验证。行US-PTLB的患者对病变行b超（B-US）、彩色多普勒血流显像（CDFI）、超声弹性成像（ultrasound elastography，超声造影）、超声造影（contrast-enhanced ultrasound， CEUS）检查，综合评价后确定最终诊断。确定与假阴性结果相关的危险因素，并采用多因素logistic回归构建预测模型。在一个独立的队列中进一步评估了该模型的性能，以评估其通过有针对性的干预措施减少假阴性结果发生率的影响。结果：利用129例患者的数据构建US-PTLB假阴性风险预测模型，其中35例（29.1%）最终诊断为假阴性。预测因素包括年龄、病变大小、弹性评分、病变坏死和超声造影增强强度。该模型具有良好的鉴别能力，曲线下面积为0.922，灵敏度为88.6%，特异度为90.4%。在70名独立收集的患者中进行的内部验证证实了模型的稳健性能。在423例患者中应用该模型，再加上对高危患者进行第二次活检，导致假阴性结果的发生率显著降低。结论：该预测模型将临床参数与多模态超声特征相结合，可作为超声引导下经皮经胸肺穿刺活检假阴性风险客观评估的可靠术后工具。它的临床应用使早期风险分层，最大限度地减少假阴性率，提高诊断精度。

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引用次数: 0