ArticleBMC medical imaging2026
Early prediction of pathologic complete response to neoadjuvant chemotherapy based on longitudinal total choline of MR spectroscopy in patients with breast cancer.
Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAccurately 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.
objectivesTo investigate the performance of tCho in singlevoxel 1H-MRS to early predict pCR to NAC in breast cancer patients. MATERIALS &
methodsPatients 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).
results191 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.
conclusionstCho 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.
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