Nomogram based on quantitative dynamic contrast-enhanced magnetic resonance imaging, apparent diffusion coefficient, and clinicopathological features for early prediction of pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy

He, Muzhen; Su, Jiawei; Ruan, Huiping; Yang, Song; Ma, M.; Xue, Fei

doi:10.21037/qims-22-869

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…Numerous studies have consistently demonstrated that, compared with MG and ultrasound, MRI has superior reliability in monitoring pathological response and evaluating residual tumor size ( 15 - 18 ). Surgeons’ assessment of the tumor relies heavily on post-NAT imaging.…”

Section: Discussionmentioning

confidence: 99%

Value of mammographic microcalcifications and MRI-enhanced lesions in the evaluation of residual disease after neoadjuvant therapy for breast cancer

Zhu,

Chen,

Liu

et al. 2023

Quant Imaging Med Surg

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Background Microcalcifications persist even if a patient with breast cancer achieves pathologic complete response (pCR) as confirmed by surgery after neoadjuvant treatment (NAT). In practice, surgeons tend to remove all the microcalcifications. This study aimed to explore the correlation between changes in the extent of microcalcification after NAT and pathological tumor response and compare the accuracy of mammography (MG) and magnetic resonance imaging (MRI) in predicting the size of residual tumors. Methods This was a retrospective study which included a consecutive series of patients in Guangdong Provincial People’s Hospital. Between January 2010 and January 2020, 127 patients with breast cancer and Breast Imaging Reporting and Data System (BI-RADS) 4–5 microcalcifications were included in this study. The maximum diameter of the microcalcifications on MG and lesion enhancement on MRI pre- and post-NAT were measured. The correlations between the changes in residual microcalcifications on MG and pCR were analyzed. Intraclass correlation coefficients (ICCs) were computed between the extent of the residual microcalcifications, residual enhancement, and residual tumor size. Results There were no statistically significant differences in the changes in microcalcifications after NAT according to the RECIST criteria on MRI (P=0.09) and Miller-Payne grade (P=0.14). MRI showed a higher agreement than did residual microcalcifications on MG in predicting residual tumor size (ICC: 0.771 vs. 0.097). Conclusions MRI is more accurate for evaluating residual tumor size in breast cancer. In our study, the extent of microcalcifications on MG after NAT had nearly no correlation with the pathological size of the residual tumor. Therefore, residual tumors with microcalcifications may not necessarily be a contraindication to breast-conserving surgery.

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Section: Discussionmentioning

confidence: 99%

Value of mammographic microcalcifications and MRI-enhanced lesions in the evaluation of residual disease after neoadjuvant therapy for breast cancer

Zhu,

Chen,

Liu

et al. 2023

Quant Imaging Med Surg

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Breast Cancer: Multi-b-Value Diffusion Weighted Habitat Imaging in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy

Xu,

Wang,

Wang

et al. 2024

Academic Radiology

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Ki-67 With MRI in Predicting the Complete Pathological Response Post-neoadjuvant Chemotherapy

Kolli,

George,

Aoutla

et al. 2024

Cureus

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Neoadjuvant chemotherapy (NAC) is increasingly used for high-risk breast cancer to achieve pathologic complete response (pCR), an indicator of event-free survival and favorable survival outcomes. Integrating MRI and Ki-67 biomarker analysis into predictive models offers a promising approach to optimize NAC response assessment and guide personalized treatment strategies. This study evaluates the validity of combined MRI and Ki-67 metrics for predicting pCR. We conducted a systematic review and meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, including studies on NAC-treated breast cancer patients assessed by MRI and Ki-67. The predictive models were evaluated based on key parameters, including MRI-based tumor size reduction and Ki-67 levels, with outcomes measured by area under the receiver operating characteristic curve (AUC) and calibration metrics. Findings across ten studies consistently show that high Ki-67 levels and significant tumor size reduction on MRI are predictive of pCR, achieving AUCs near 0.90. The analysis highlighted that models integrating MRI with Ki-67 metrics outperformed single-modality approaches, showing enhanced predictive accuracy and calibration. However, high heterogeneity (I² = 77%) was noted, suggesting variability in imaging and Ki-67 assessment protocols across studies. This study underscores the combined utility of MRI and Ki-67 for the non-invasive prediction of pCR, offering both structural and biological insights into tumor responsiveness. The results align with prior research, affirming the role of Radiomic-clinicopathological models in providing a more comprehensive assessment compared to individual markers. Further refinement of imaging and biomarker protocols could improve model reproducibility and applicability. Our findings highlight the robust predictive accuracy of MRI-Ki-67 integrated models for assessing pCR, marking a significant step toward personalized cancer care. Future studies should focus on refining these models with additional biomarkers and standardized protocols, facilitating their integration into routine clinical oncology to enhance treatment decision-making and patient outcomes.

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Nomogram based on quantitative dynamic contrast-enhanced magnetic resonance imaging, apparent diffusion coefficient, and clinicopathological features for early prediction of pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy

Cited by 3 publications

References 36 publications

Value of mammographic microcalcifications and MRI-enhanced lesions in the evaluation of residual disease after neoadjuvant therapy for breast cancer

Value of mammographic microcalcifications and MRI-enhanced lesions in the evaluation of residual disease after neoadjuvant therapy for breast cancer

Breast Cancer: Multi-b-Value Diffusion Weighted Habitat Imaging in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy

Ki-67 With MRI in Predicting the Complete Pathological Response Post-neoadjuvant Chemotherapy

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