Article(id=1320381114556985771, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320381076653060187, articleNumber=null, orderNo=null, doi=10.11876/mimt202602013, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792732989205, onlineDateStr=2026-10-23, pubDate=1775750400000, pubDateStr=2026-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792732989205, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792732989205, creator=13701087609, updateTime=1792732989205, updator=13701087609, issue=Issue{id=1320381076653060187, tenantId=1146029695717560320, journalId=1319373289681944729, year='2026', volume='32', issue='2', pageStart='1', pageEnd='120', issueExtLink='null', onlineDate='null', pubDate='1775750400000', pubDateStr='2026-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792732980168, creator='13701087609', updateTime=1792746330832, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320437073467789517, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320381076653060187, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320437073467789518, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320381076653060187, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=76, endPage=84, ext={EN=ArticleExt(id=1320381114745729452, articleId=1320381114556985771, tenantId=1146029695717560320, journalId=1319373289681944729, language=EN, title=Value of whole-tumor ADC histogram parameters in differentiating adrenal metastases from adenoma-dominant benign lesions in lung cancer, columnId=null, journalTitle=Modern Instruments & Medical Treatment, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective To explore the diagnostic value of whole-tumor apparent diffusion coefficient (ADC) histogram parameters derived from magnetic resonance imaging (MRI) in differentiating adrenal metastases from benign lesions in patients with lung cancer, with a focus on analyzing the differential efficacy of these parameters for small nodules with a diameter <3 cm.
Methods A retrospective analysis was performed on 149 patients with adrenal space-occupying lesions confirmed by pathology or clinical follow-up, including 84 cases in the benign group (adenomas accounting for 83.3%) and 65 cases in the metastatic group. All patients underwent 3.0 T MRI scanning to obtain ADC maps. Three-dimensional whole-tumor regions of interest (ROI) were manually delineated slice by slice using FireVoxel software, and histogram parameters such as mean, standard deviation, skewness, kurtosis, entropy, and the 1st, 25th, 75th, and 95th percentiles (ADC-1%, ADC-25%, ADC-75%, ADC-95%) were extracted. The Mann-Whitney U test or independent samples t-test was used to compare the parameter differences between the two groups. Three diagnostic models were constructed: a tumor size-only model (Model 1), a histogram-only model (Model 2) and a combined model integrating histogram parameters with tumor size (Model 3). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic efficacy, and subgroup analysis was further performed for lesions with a diameter < 3 cm.
Results The standard deviation, skewness, kurtosis and ADC-95% in the metastatic group were significantly higher than those in the benign group, while ADC-1% was significantly lower (all P < 0.05). Among the individual parameters, standard deviation exhibited the optimal diagnostic performance, with an area under the curve (AUC) of 0.753 (95%CI: 0.676~0.813). The AUC values of Model 2 and Model 3 were 0.809 (95%CI: 0.740~0.866) and 0.821 (95%CI: 0.756~0.871), respectively, with no statistically significant difference between the two models (P = 0.373). In the subgroup of lesions < 3 cm in diameter, the histogram model achieved an AUC of 0.817 (95% CI: 0.738~0.896), and kurtosis was identified as the only independent predictor (OR=1.538, P=0.035). Calibration curves and decision curve analysis verified that the model yielded favorable clinical net benefits.
Conclusion Whole-tumor ADC histogram parameters can effectively quantify the heterogeneity of adrenal tumors and hold important value in differentiating adrenal metastases from benign lesions in lung cancer patients. Notably, kurtosis shows prominent performance in the early malignant identification of small nodules < 3 cm, providing a reliable basis for non-invasive and accurate clinical diagnosis.
, authors=Fei Zou, Liping Hu, Fengjiang Zhou, Mei Sun, Xinhua Tu, Gaoliang Wu, Ji Huang, Yong Cai, Xiaofang Zhang, Lan Liu
*, authorsList=Fei Zou, Liping Hu, Fengjiang Zhou, Mei Sun, Xinhua Tu, Gaoliang Wu, Ji Huang, Yong Cai, Xiaofang Zhang, Lan Liu, authorCompany=null, correspAuthors=Lan Liu, authorNote=null, correspAuthorsNote=null, copyrightStatement=
All copyrights in 2026 belong to the sponsor of the journal.Not content published by the journal may be reproduced or abridged without authorization., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320381114976416173, articleId=1320381114556985771, tenantId=1146029695717560320, journalId=1319373289681944729, language=CN, title=全瘤ADC直方图参数鉴别肺癌肾上腺转移瘤与腺瘤为主良性病变的价值, columnId=1320381058969883180, journalTitle=现代仪器与医疗, columnName=临床研究, runingTitle=null, highlight=null, articleAbstract=
目的 探讨磁共振全瘤表观扩散系数（apparent diffusion coefficient，ADC）直方图参数在肺癌肾上腺转移瘤与良性病变鉴别中的诊断价值，重点分析其对直径<3 cm小结节的鉴别效能。
方法 回顾性分析149例经病理或临床随访证实的肾上腺占位患者，其中良性组84例（腺瘤占83.3%）、转移瘤组65例。所有患者均行3.0 T MRI扫描并获取ADC图像，通过FireVoxel软件逐层勾画全瘤三维感兴趣区域（regions of interest，ROI），提取均值、标准差、偏度、峰度、熵和第1、25、75、95百分位数（ADC-1%、ADC-25%、ADC-75%、ADC-95%）等ADC直方图参数，采用Mann-Whitney U检验或t检验比较两组参数差异，构建肿瘤大小模型（模型1）、直方图模型（模型2）及直方图联合肿瘤大小模型（模型3），通过受试者工作特征（receiver operating characteristic，ROC）曲线分析诊断效能，并针对直径< 3 cm病灶进行亚组分析。
结果 转移瘤组的标准差、偏度、峰度和ADC-95%显著高于良性组，ADC-1%显著低于良性组，差异均有统计学意义（P均<0.05）；单一直方图参数中标准差诊断效能最优，AUC为0.753（95% CI：0.676~0.813）。单纯直方图模型（模型2）与直方图联合肿瘤大小模型（模型3）的AUC分别为0.809（95% CI：0.740~0.866）和0.821（95% CI：0.756~0.871），差异无统计学意义（P=0.373）。直径< 3 cm病灶亚组中，直方图模型AUC为0.817（95% CI：0.738~0.896），多因素Logistic回归分析显示峰度是唯一独立预测因子（OR=1.538，P=0.035），校准曲线及决策曲线证实模型具有良好临床净获益。
结论 全瘤ADC直方图参数可有效量化肾上腺肿瘤异质性，对肺癌肾上腺转移瘤与良性病变鉴别具有重要价值，其中，峰度在< 3 cm小结节的早期恶性识别中表现突出，为临床无创精准诊断提供可靠依据。
, authors=邹飞, 胡利平, 周峰江, 孙美, 涂新华, 吴高亮, 黄骥, 蔡勇, 张小芳, 刘岚
*, authorsList=邹飞, 胡利平, 周峰江, 孙美, 涂新华, 吴高亮, 黄骥, 蔡勇, 张小芳, 刘岚, authorCompany=null, correspAuthors=刘岚, authorNote=
邹飞，女，硕士研究生，主治医师，研究方向：肿瘤影像诊断
, correspAuthorsNote=
刘岚，女，硕士研究生，主任医师，研究方向：肿瘤影像诊断（乳腺）
, copyrightStatement=
2026年版权归本刊主办单位所有未经本刊书面许可, 不得转载、摘编本刊所有文章内容。, copyrightOwner=中国科学器材公司, extLink=null, articleAbsUrl=null, sourceXml=r9H13UfVH440iIECQQXurA==, magXml=i89PnQ+Sm8atidcivt5D2Q==, pdfUrl=null, pdf=dzP2s99J1mzsjK3kL3knzA==, pdfFileSize=2303954, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=m3J+k76Ufd9kUFQfBhXcyw==, mapNumber=null, fund=null)}, authors=[Author(id=1320381116897407410, tenantId=1146029695717560320, journalId=1319373289681944729, articleId=1320381114556985771, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1320381116989682100, tenantId=1146029695717560320, journalId=1319373289681944729, articleId=1320381114556985771, authorId=1320381116897407410, language=EN, stringName=Fei Zou, firstName=Fei, middleName=null, lastName=Zou, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Jiangxi Cancer Hospital, Nanchang 330029, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1320381117060985269, tenantId=1146029695717560320, journalId=1319373289681944729, articleId=1320381114556985771, authorId=1320381116897407410, language=CN, stringName=邹飞, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=江西省肿瘤医院，南昌 330029, bio={"content":"
邹飞，女，硕士研究生，主治医师，研究方向：肿瘤影像诊断
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邹飞，女，硕士研究生，主治医师，研究方向：肿瘤影像诊断
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