BMC medical imaging · 2026
Early prediction of pathologic complete response to neoadjuvant chemotherapy based on longitudinal total choline of MR spectroscopy in patients with breast cancer.
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Liu Shuling, Wang Xiaoxia, Jiang Fujie, Tang Sun, Cao Ying, Wang Lu, Chen Huifang, Zeng Xiangfei, Huang Yao, Li Lan, Zhang Renzhi, Zhang Jiuquan
Аннотация
BACKGROUND: Accurately predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) early during treatment could enable therapy adaptation. Total choline (tCho) measured by Proton MR spectroscopy (1H-MRS) reflects tumor metabolism and may serve as an early biomarker, but its predictive performance requires further validation. OBJECTIVES: To investigate the performance of tCho in singlevoxel 1H-MRS to early predict pCR to NAC in breast cancer patients. MATERIALS & METHODS: Patients with primary invasive breast cancer scheduled for NAC were prospectively enrolled from August 2021 to October 2023. The concentration of tCho was measured with 1H-MRS at four time points: T0 (pretreatment), T1, T2, and T3 (after 2, 4, and 6 NAC cycles respectively). The tCho were compared among the four time points and between pCR and non-pCR groups. The diagnostic performance was evaluated using the area under the receiver operating characteristic curves (AUC). RESULTS: 191 patients were enrolled, including 136 patients with non-pCR and 55 patients with pCR. The dynamic changes of tCho showed a downward trend during NAC in the pCR group, non-pCR group, and all molecular subtypes. Among the total patients, tCho at four time points were higher in the non-pCR group than those in the pCR group (all P < 0.05), and with an AUC of 0.72 at T0. In the Luminal B, HER2-enriched and triple-negative subgroups, tCho at T0 were higher in the non-pCR group than that in the pCR group (all P < 0.05). In all patients, tCho combined with the PR and HER2 at T0 showed good predicting performance, with an AUC of 0.85. CONCLUSIONS: tCho could be used as an early predictor of pCR during NAC in breast cancer patients. This may assist in guiding the clinical selection of individualized and effective treatment programs.