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A modified diffusion-weighted magnetic resonance imaging–based model from the radiologist’s perspective: improved performance in determining the surgical resectability of advanced high-grade serous ovarian cancer - 22/06/24

Doi : 10.1016/j.ajog.2024.02.302 
Jing Lu, MD, PhD a, b, Qinhao Guo, MD, PhD b, c, Ya Zhang, MD, PhD d, Shuhui Zhao, MD, PhD e, Ruimin Li, MD, PhD a, b, Yi Fu, MD a, b, Zheng Feng, MD, PhD b, c, Yong Wu, MD, PhD b, c, Rong Li, BD a, b, Xiaojie Li, BD f, Jinwei Qiang, MD, PhD g, Xiaohua Wu, MD, PhD b, c, Yajia Gu, MD, PhD a, b, Haiming Li, MD, PhD a, b,
a Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China 
b Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China 
c Department of Gynecological Oncology, Fudan University Shanghai Cancer Center, Shanghai, China 
d Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, Yunnan, China 
e Department of Radiology, Xinhua Hospital affiliated with the Shanghai Jiaotong University School of Medicine, Shanghai, China 
f Department of Radiology, Kunming Second People's Hospital, Kunming, Yunnan, China 
g Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China 

Corresponding author: Haiming Li, MD, PhD.

Abstract

Background

Complete resection of all visible lesions during primary debulking surgery is associated with the most favorable prognosis in patients with advanced high-grade serous ovarian cancer. An accurate preoperative assessment of resectability is pivotal for tailored management.

Objective

This study aimed to assess the potential value of a modified model that integrates the original 8 radiologic criteria of the Memorial Sloan Kettering Cancer Center model with imaging features of the subcapsular or diaphragm and mesenteric lesions depicted on diffusion-weighted magnetic resonance imaging and growth patterns of all lesions for predicting the resectability of advanced high-grade serous ovarian cancer.

Study Design

This study included 184 patients with high-grade serous ovarian cancer who underwent preoperative diffusion-weighted magnetic resonance imaging between December 2018 and May 2023 at 2 medical centers. The patient cohort was divided into 3 subsets, namely a study cohort (n=100), an internal validation cohort (n=46), and an external validation cohort (n=38). Preoperative radiologic evaluations were independently conducted by 2 radiologists using both the Memorial Sloan Kettering Cancer Center model and the modified diffusion-weighted magnetic resonance imaging–based model. The morphologic characteristics of the ovarian tumors depicted on magnetic resonance imaging were assessed as either mass-like or infiltrative, and transcriptomic analysis of the primary tumor samples was performed. Univariate and multivariate statistical analyses were performed.

Results

In the study cohort, both the scores derived using the Memorial Sloan Kettering Cancer Center (intraclass correlation coefficients of 0.980 and 0.959, respectively; both P<.001) and modified diffusion-weighted magnetic resonance imaging–based models (intraclass correlation coefficients of 0.962 and 0.940, respectively; both P<.001) demonstrated excellent intra- and interobserver agreement. The Memorial Sloan Kettering Cancer Center model (odds ratio, 1.825; 95% confidence interval, 1.390–2.395; P<.001) and the modified diffusion-weighted magnetic resonance imaging–based model (odds ratio, 1.776; 95% confidence interval, 1.410–2.238; P<.001) independently predicted surgical resectability. The modified diffusion-weighted magnetic resonance imaging–based model demonstrated improved predictive performance with an area under the curve of 0.867 in the study cohort and 0.806 and 0.913 in the internal and external validation cohorts, respectively. Using the modified diffusion-weighted magnetic resonance imaging–based model, patients with scores of 0 to 2, 3 to 4, 5 to 6, 7 to 10, and ≥11 achieved complete tumor debulking rates of 90.3%, 66.7%, 53.3%, 11.8%, and 0%, respectively. Most patients with incomplete tumor debulking had infiltrative tumors, and both the Memorial Sloan Kettering Cancer Center and the modified diffusion-weighted magnetic resonance imaging–based models yielded higher scores. The molecular differences between the 2 morphologic subtypes were identified.

Conclusion

When compared with the Memorial Sloan Kettering Cancer Center model, the modified diffusion-weighted magnetic resonance imaging–based model demonstrated enhanced accuracy in the preoperative prediction of resectability for advanced high-grade serous ovarian cancer. Patients with scores of 0 to 6 were eligible for primary debulking surgery.

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Key words : diffusion-weighted imaging, magnetic resonance imaging, morphological characteristics, MSKCC model, ovarian cancer, primary debulking surgery, transcriptomics


Plan


 J.L., Q.G., Y.Z., and S.Z. are combined first authors.
 X.W., Y.G., and H.L. are combined senior authors.
 The authors report no conflict of interest.
 This study was supported by the National Natural Science Foundations of China under grant numbers 82271940 and 82203723, the Natural Science Foundation of Shanghai under grant number 22ZR1412500, and the Shanghai Anticancer Association EYAS PROJECT under grant number SACA-CY22B09.
 Cite this article as: Lu J, Guo Q, Zhang Y, et al. A modified diffusion-weighted magnetic resonance imaging–based model from the radiologist’s perspective: improved performance in determining the surgical resectability of advanced high-grade serous ovarian cancer. Am J Obstet Gynecol 2024;231:117.e1-17.


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Vol 231 - N° 1

P. 117.e1-117.e17 - juillet 2024 Retour au numéro
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