Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm

IF 4.9 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Diagnostic and Interventional Imaging Pub Date : 2024-04-04 DOI:10.1016/j.diii.2024.03.005

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引用次数: 0

Abstract

Purpose

The purpose of this study was to evaluate the capabilities of multiparametric magnetic resonance imaging (MRI) in differentiating between lipid-poor adrenal adenoma (LPAA) and adrenocortical carcinoma (ACC).

Materials and methods

Patients of two centers who underwent surgical resection of LPAA or ACC after multiparametric MRI were retrospectively included. A training cohort was used to build a diagnostic algorithm obtained through recursive partitioning based on multiparametric MRI variables, including apparent diffusion coefficient and chemical shift signal ratio (i.e., tumor signal intensity index). The diagnostic performances of the multiparametric MRI-based algorithm were evaluated using a validation cohort, alone first and then in association with adrenal tumor size using a cut-off of 4 cm. Performances of the diagnostic algorithm for the diagnosis of ACC vs. LPAA were calculated using pathology as the reference standard.

Results

Fifty-four patients (27 with LPAA and 27 with ACC; 37 women; mean age, 48.5 ± 13.3 [standard deviation (SD)] years) were used as the training cohort and 61 patients (24 with LPAA and 37 with ACC; 47 women; mean age, 49 ± 11.7 [SD] years) were used as the validation cohort. In the validation cohort, the diagnostic algorithm yielded best accuracy for the diagnosis of ACC vs. LPAA (75%; 46/61; 95% CI: 55–88) when used without lesion size. Best sensitivity was obtained with the association of the diagnostic algorithm with tumor size (96%; 23/24; 95% CI: 80–99). Best specificity was obtained with the diagnostic algorithm used alone (76%; 28/37; 95% CI: 60–87).

Conclusion

A multiparametric MRI-based diagnostic algorithm that includes apparent diffusion coefficient and tumor signal intensity index helps discriminate between ACC and LPAA with high degrees of specificity and accuracy. The association of the multiparametric MRI-based diagnostic algorithm with adrenal lesion size helps maximize the sensitivity of multiparametric MRI for the diagnosis of ACC.

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利用基于多参数磁共振成像的诊断算法区分肾上腺皮质癌和贫脂肾上腺腺瘤。

目的：本研究旨在评估多参数磁共振成像（MRI）在区分贫脂性肾上腺腺瘤（LPAA）和肾上腺皮质癌（ACC）方面的能力：回顾性纳入两个中心在多参数磁共振成像后接受手术切除LPAA或ACC的患者。根据多参数磁共振成像变量，包括表观弥散系数和化学位移信号比（即肿瘤信号强度指数），利用训练队列建立递归分区诊断算法。首先使用验证队列评估了基于多参数磁共振成像算法的诊断性能，然后以 4 厘米为临界值，评估了该算法与肾上腺肿瘤大小的关联性。以病理学作为参考标准，计算了该诊断算法对 ACC 和 LPAA 的诊断效果：54名患者（27名患有LPAA，27名患有ACC；37名女性；平均年龄（48.5 ± 13.3 [标准差（SD）]岁）被用作训练队列，61名患者（24名患有LPAA，37名患有ACC；47名女性；平均年龄（49 ± 11.7 [标准差（SD）]岁）被用作验证队列。在验证队列中，在不考虑病变大小的情况下，诊断算法对 ACC 与 LPAA 的诊断准确率最高（75%；46/61；95% CI：55-88）。诊断算法与肿瘤大小相关时，灵敏度最高（96%；23/24；95% CI：80-99）。单独使用诊断算法的特异性最佳（76%；28/37；95% CI：60-87）：结论：基于磁共振成像的多参数诊断算法包括表观弥散系数和肿瘤信号强度指数，有助于区分ACC和LPAA，特异性和准确性都很高。基于多参数 MRI 的诊断算法与肾上腺病变大小的关联有助于最大限度地提高多参数 MRI 诊断 ACC 的灵敏度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Diagnostic and Interventional Imaging Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

8.50

自引率

29.10%

发文量

126

审稿时长

11 days

期刊介绍： Diagnostic and Interventional Imaging accepts publications originating from any part of the world based only on their scientific merit. The Journal focuses on illustrated articles with great iconographic topics and aims at aiding sharpening clinical decision-making skills as well as following high research topics. All articles are published in English. Diagnostic and Interventional Imaging publishes editorials, technical notes, letters, original and review articles on abdominal, breast, cancer, cardiac, emergency, forensic medicine, head and neck, musculoskeletal, gastrointestinal, genitourinary, interventional, obstetric, pediatric, thoracic and vascular imaging, neuroradiology, nuclear medicine, as well as contrast material, computer developments, health policies and practice, and medical physics relevant to imaging.