Exploring the value of arterial spin labeling and six diffusion MRI models in differentiating solid benign and malignant renal tumors.

Autor: Gao M; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., Li S; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., Yuan G; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., Qu W; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., He K; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., Liao Z; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., Yin T; MR Research Collaboration Team, Siemens Healthineers Ltd, Chengdu, China., Chen W; MR Research Collaboration Team, Siemens Healthineers Ltd, Wuhan, China., Chu Q; Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China., Li Z; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. zhenli@hust.edu.cn.
Jazyk: angličtina
Zdroj: European radiology experimental [Eur Radiol Exp] 2024 Dec 05; Vol. 8 (1), pp. 135. Date of Electronic Publication: 2024 Dec 05.
DOI: 10.1186/s41747-024-00537-y
Abstrakt: Objective: To explore the value of three-dimensional arterial spin labeling (ASL) and six diffusion magnetic resonance imaging (MRI) models in differentiating solid benign and malignant renal tumors.
Methods: This retrospective study included 89 patients with renal tumors. All patients underwent ASL and ZOOMit diffusion-weighted imaging (DWI) examinations and were divided into three groups: clear cell renal cell carcinoma (ccRCC), non-ccRCC, and benign renal tumors (BRT). The mean and peak renal blood flow (RBFmean and RBFpeak) from ASL and fourteen diffusion parameters from mono-exponential DWI (Mono_DWI), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), fractional order calculus (FROC), and continuous-time random-walk (CTRW) model were analyzed. Binary logistic regression was used to determine the optimal parameter combinations. The diagnostic performance of various MRI-derived parameters and their combinations was compared.
Results: Among the six diffusion models, the SEM model achieved the highest performance in differentiating ccRCC from non-ccRCC (area under the receiver operating characteristic curve [AUC] 0.880) and from BRT (AUC 0.891). IVIM model achieved the highest AUC (0.818) in differentiating non-ccRCC from BRT. Among all the MRI-derived parameters, RBFpeak combined with DKI_MK yielded the highest AUC (0.970) in differentiating ccRCC from non-ccRCC, and the combination of RBFpeak, SEM_DDC, and FROC_μ yielded the highest AUC (0.992) for differentiating ccRCC from BRT.
Conclusion: ASL and all diffusion models showed similar diagnostic performance in differentiating ccRCC from non-ccRCC or BRT, while the IVIM model performed better in distinguishing non-ccRCC from BRT. Combining ASL with diffusion models can provide additional value in predicting ccRCC.
Relevance Statement: Considering the increasing detection rate of incidental renal masses, accurate discrimination of benign and malignant renal tumors is crucial for decision-making. Combining ASL with diffusion MRI models offers a promising solution to this clinical issue.
Key Points: All assessed models were effective for differentiating ccRCC from non-ccRCC or BRT. ASL and all diffusion models showed similar performance in differentiating ccRCC from non-ccRCC or BRT. Combining ASL with diffusion models significantly improved diagnostic efficacy in predicting ccRCC. IVIM model could better differentiate non-ccRCC from BRT.
Competing Interests: Declarations. Ethics approval and consent to participate: This retrospective study was approved by the Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology and in accordance with the Declaration of Helsinki. The requirement for informed consent was waived. Consent for publication: All patients have approved this manuscript for publication. Competing interests: TY and WC are employed by Siemens Healthineers Ltd. All remaining authors declare no conflicts of interest in the present study.
(© 2024. The Author(s).)
Databáze: MEDLINE
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