Article
Radiology, Nuclear Medicine & Medical Imaging
Toulsie Ramtohul, Clara Tescher, Pauline Vaflard, Joanna Cyrta, Noemie Girard, Caroline Malhaire, Anne Tardivon
Summary: The study aimed to evaluate whether semiquantitative perfusion parameters calculated at initial ultrafast DCE MRI can predict pathologic response after neoadjuvant chemotherapy in breast cancer patients. The results showed that the wash-in slope (WIS) parameter was an independent predictor associated with pathologic complete response, and it could differentiate subgroups of breast cancer patients with different rates of pathologic complete response.
Article
Oncology
Frederik Knude Palshof, Charlotte Lanng, Niels Kroman, Cemil Benian, Ilse Vejborg, Anne Bak, Maj-Lis Talman, Eva Balslev, Tove Filtenborg Tvedskov
Summary: The study found that MRI was more specific than US in predicting pCR in breast cancer patients receiving NACT, but not specific enough to be a valid predictor for omitting surgery. MRI should be preferred for future studies on predicting pCR in NACT patients.
ANNALS OF SURGICAL ONCOLOGY
(2021)
Article
Multidisciplinary Sciences
Sunghoon Joo, Eun Sook Ko, Soonhwan Kwon, Eunjoo Jeon, Hyungsik Jung, Ji-Yeon Kim, Myung Jin Chung, Young-Hyuck Im
Summary: The study developed a deep learning model that integrates clinical information and MRI images to predict pathologic complete response to neoadjuvant chemotherapy in breast cancer patients. The model trained on all datasets showed better performance compared to using only clinical information.
SCIENTIFIC REPORTS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Soo-Yeon Kim, Nariya Cho, Yunhee Choi, Su Hyun Lee, Su Min Ha, Eun Sil Kim, Jung Min Chang, Woo Kyung Moon
Summary: A nomogram incorporating MRI and clinical-pathologic variables was developed to predict pathologic complete response after neoadjuvant chemotherapy in breast cancer. The nomogram showed good discrimination and calibration abilities, effectively identifying independent variables associated with pCR.
Article
Radiology, Nuclear Medicine & Medical Imaging
Ying Cao, Xiaoxia Wang, Lan Li, Jinfang Shi, Xiangfei Zeng, Yao Huang, Huifang Chen, Fujie Jiang, Ting Yin, Dominik Nickel, Jiuquan Zhang
Summary: This study evaluated the temporal trends of ultrafast DCE-MRI during neoadjuvant chemotherapy (NAC) and investigated whether the changes in DCE-MRI parameters could early predict pathologic complete response (pCR) of breast cancer. The results showed that the changes in ultrafast DCE-MRI parameters were associated with pCR, and the combination with clinicopathologic characteristics improved the prediction of pCR.
DIAGNOSTIC AND INTERVENTIONAL IMAGING
(2023)
Article
Multidisciplinary Sciences
Zijian Zhou, Beatriz E. Adrada, Rosalind P. Candelaria, Nabil A. Elshafeey, Medine Boge, Rania M. Mohamed, Sanaz Pashapoor, Jia Sun, Zhan Xu, Bikash Panthi, Jong Bum Son, Mary S. Guirguis, Miral M. Patel, Gary J. Whitman, Tanya W. Moseley, Marion E. Scoggins, Jason B. White, Jennifer K. Litton, Vicente Valero, Kelly K. Hunt, Debu Tripathy, Wei Yang, Peng Wei, Clinton Yam, Mark D. Pagel, Gaiane M. Rauch, Jingfei Ma
Summary: Deep learning based on multiparametric MRI can potentially predict TNBC patients' pCR status in the breast early during NAST.
SCIENTIFIC REPORTS
(2023)
Article
Oncology
Liangcun Guo, Siyao Du, Si Gao, Ruimeng Zhao, Guoliang Huang, Feng Jin, Yuee Teng, Lina Zhang
Summary: This study investigates the value of delta-radiomics after the first cycle of neoadjuvant chemotherapy (NAC) using dynamic contrast-enhanced (DCE) MRI for early prediction of pathological complete response (pCR) in patients with breast cancer. The results show that the delta-radiomics model based on early phases of DCE-MRI can effectively predict pCR in breast cancer patients. This model provides strong support for clinical decision-making and helps patients benefit the most from NAC.
Article
Radiology, Nuclear Medicine & Medical Imaging
Jieun Kim, Boo-Kyung Han, Eun Young Ko, Eun Sook Ko, Ji Soo Choi, Ko Woon Park
Summary: This study investigated the predictability of breast MRI for pathologic complete response (pCR) by molecular subtype in patients with breast cancer receiving neoadjuvant chemotherapy (NAC) and explored the MRI findings that can mimic residual malignancy. The results showed that the diagnostic accuracy of MRI for predicting pCR differed by molecular subtypes, and subtle residual enhancement observed on MRI after NAC was associated with false-negative findings.
EUROPEAN RADIOLOGY
(2022)
Article
Oncology
Li-Yun Xie, Kun Wang, Hai-Lu Chen, Yan-Xia Shi, Yuan-Qi Zhang, Hao-Yu Lin, Yuan-Ke Liang, Ying-Sheng Xiao, Zhi-Yong Wu, Zhong-Yu Yuan, Si-Qi Qiu
Summary: The study identified clinical T stage, clinical N stage, and tumor expression of ALDH3A2 as potential markers for predicting tumor recurrence in patients who achieved a tumor pCR after NAC.
FRONTIERS IN ONCOLOGY
(2022)
Article
Oncology
He Dou, Siyuan Jia, Yuling Ba, Danli Luo, Pingyang Yu, Fucheng Li, Youyu Wang, Xingyan Chen, Min Xiao
Summary: This study analyzed the clinicopathological characteristics and chemotherapeutic response of patients with postpartum breast cancer (PPBC). The results showed that PPBC patients were younger, more likely to undergo breast-conserving surgery, and more likely to achieve pathological complete remission (pCR). PPBC was found to be an independent predictor of pCR attainment in breast cancer patients and demonstrated higher sensitivity to chemotherapy.
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2023)
Article
Medicine, General & Internal
Elizabeth J. Sutton, Lior Z. Braunstein, Mahmoud B. El-Tamer, Edi Brogi, Mary Hughes, Yolanda Bryce, Jill S. Gluskin, Simon Powell, Alyssa Woosley, Audree Tadros, Varadan Sevilimedu, Danny F. Martinez, Larowin Toni, Olga Smelianskaia, C. Gregory Nyman, Pedram Razavi, Larry Norton, Maggie M. Fung, James D. Sedorovich, Virgilio Sacchini, Elizabeth A. Morris
Summary: The study found that the accuracy of MRI-guided biopsy in diagnosing post-NAC pCR approaches that of reference-standard surgical resection, indicating it may be a viable alternative for this population after NAC and further investigation is warranted.
Article
Oncology
Ji-Yeon Kim, Eunjoo Jeon, Soonhwan Kwon, Hyungsik Jung, Sunghoon Joo, Youngmin Park, Se Kyung Lee, Jeong Eon Lee, Seok Jin Nam, Eun Yoon Cho, Yeon Hee Park, Jin Seok Ahn, Young-Hyuck Im
Summary: This study developed a machine learning model based on pretreatment clinical and pathological characteristics from EMR data to accurately predict pathologic complete response to neoadjuvant chemotherapy in breast cancer patients. The model showed varying performance in predicting pCR across different molecular subtypes.
BREAST CANCER RESEARCH AND TREATMENT
(2021)
Article
Oncology
Sara P. Myers, Gillian M. Ahrendt, Joanna S. Lee, Jennifer G. Steiman, Atilla Soran, Ronald R. Johnson, Priscilla F. McAuliffe, Emilia J. Diego
Summary: The study revealed that breast pCR and ypN0 primarily occurred in HER2+ and TNBC subtypes, and factors such as age, tumor subtype, and clinical stage were associated with ypN0. The impact of cN status on ypN0 varied among different tumor subtypes.
ANNALS OF SURGICAL ONCOLOGY
(2021)
Article
Oncology
Andre Pfob, Chris Sidey-Gibbons, Geraldine Rauch, Bettina Thomas, Benedikt Schaefgen, Sherko Kuemmel, Toralf Reimer, Markus Hahn, Marc Thill, Jens-Uwe Blohmer, John Hackmann, Wolfram Malter, Inga Bekes, Kay Friedrichs, Sebastian Wojcinski, Sylvie Joos, Stefan Paepke, Tom Degenhardt, Joachim Rom, Achim Rody, Marion van Mackelenbergh, Maggie Banys-Paluchowski, Regina Grosse, Mattea Reinisch, Maria Karsten, Michael Golatta, Joerg Heil
Summary: Neoadjuvant systemic treatment is effective for breast cancer patients, but current nonsurgical methods cannot accurately identify patients without residual cancer. We developed an intelligent vacuum-assisted biopsy approach using machine learning algorithm, which can reliably exclude residual cancer.
JOURNAL OF CLINICAL ONCOLOGY
(2022)
Article
Oncology
Shin-Cheh Chen, Chi-Chang Yu, Hsien-Kun Chang, Yung-Chang Lin, Yung-Feng Lo, Shih-Che Shen, Wen-Lin Kuo, Hsiu-Pei Tsai, Hsu-Huan Chou, Chia-Hui Chu, Wen-Chi Shen, Ren-Chin Wu, Shir-Hwa Ueng, Yi-Ting Huang
Summary: This study analyzed the differences in breast pathologic complete response (B-pCR) and axillary node pCR (N-pCR) rates in different intrinsic subtypes of early breast cancer after neoadjuvant chemotherapy (NAC). They found that N-non pCR or T-non pCR patients had the worst outcomes.