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Karagkounis G, Horvat N, Danilova S, Chhabra S, Narayan RR, Barekzai AB, Kleshchelski A, Joanne C, Gonen M, Balachandran V, Soares KC, Wei AC, Kingham TP, Jarnagin WR, Shia J, Chakraborty J, D'Angelica MI. Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy. Ann Surg Oncol 2024:10.1245/s10434-024-15373-y. [PMID: 39369120 DOI: 10.1245/s10434-024-15373-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 04/14/2024] [Indexed: 10/07/2024]
Abstract
OBJECTIVES This study was designed to assess computed tomography (CT)-based radiomics of colorectal liver metastases (CRLM), extracted from posttreatment scans in estimating pathologic treatment response to neoadjuvant therapy, and to compare treatment response estimates between CT-based radiomics and radiological response assessment by using RECIST 1.1 and CT morphologic criteria. METHODS Patients who underwent resection for CRLM from January 2003-December 2012 at a single institution were included. Patients who did not receive preoperative systemic chemotherapy, or without adequate imaging, were excluded. Imaging characteristics were evaluated based on RECIST 1.1 and CT morphologic criteria. A machine-learning model was designed with radiomic features extracted from manually segmented posttreatment CT tumoral and peritumoral regions to identify pathologic responders (≥ 50% response) versus nonresponders. Statistical analysis was performed at the tumor level. RESULTS Eighty-five patients (median age, 62 years; 55 women) with 95 tumors were included. None of the subjectively evaluated imaging characteristics were associated with pathologic response (p > 0.05). Inter-reader agreement was substantial for RECIST categorical response assessment (K = 0.70) and moderate for CT morphological group response (K = 0.50). In the validation cohort, the machine learning model built with radiomic features obtained an area under the curve (AUC) of 0.87 and outperformed subjective RECIST assessment (AUC = 0.53, p = 0.01) and morphologic assessment (AUC = 0.56, p = 0.02). CONCLUSIONS Radiologist assessment of oligometastatic CRLM after neoadjuvant therapy using RECIST 1.1 and CT morphologic criteria was not associated with pathologic response. In contrast, a machine-learning model based on radiomic features extracted from tumoral and peritumoral regions had high diagnostic performance in assessing responders versus nonresponders.
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Affiliation(s)
- Georgios Karagkounis
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Natally Horvat
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Sofia Danilova
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Salini Chhabra
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Raja R Narayan
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Ahmad B Barekzai
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Adam Kleshchelski
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Chou Joanne
- Department of Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Mithat Gonen
- Department of Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Vinod Balachandran
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Kevin C Soares
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Alice C Wei
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - T Peter Kingham
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - William R Jarnagin
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Jinru Shia
- Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Jayasree Chakraborty
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
| | - Michael I D'Angelica
- Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
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Sun Z, Liu K, Guo Y, Jiang N, Ye M. Surgery paradigm for locally advanced breast cancer following neoadjuvant systemic therapy. Front Surg 2024; 11:1410127. [PMID: 39308852 PMCID: PMC11412956 DOI: 10.3389/fsurg.2024.1410127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024] Open
Abstract
Locally advanced breast cancer (LABC) remains a significant clinical challenge, particularly in developing countries. While neoadjuvant systemic therapy (NST) has improved the pathological complete response (pCR) rates, particularly in HER2-positive and triple-negative breast cancer patients, surgical management post-NST continues to evolve. The feasibility of omitting surgery and the increasing consideration of breast-conserving surgery, immediate reconstruction in LABC patients are important areas of exploration. Accurate assessment of tumor response to NST through advanced imaging and minimally invasive biopsies remains pivotal, though challenges persist in reliably predicting pCR. Additionally, axillary lymph node management continues to evolve, with emerging strategies aiming to minimize the extent of surgery in patients who achieve nodal downstaging post-NST. Minimizing axillary lymph node dissection in favor of less invasive approaches is gaining attention, though further evidence is needed to establish its oncological safety. The potential for personalized treatment approaches, reducing surgical morbidity, and improving quality of life are key goals in managing LABC, while maintaining the priority of achieving favorable long-term outcomes.
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Affiliation(s)
| | | | | | | | - Meina Ye
- Department of Breast Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Alhassan AM. An improved breast cancer classification with hybrid chaotic sand cat and Remora Optimization feature selection algorithm. PLoS One 2024; 19:e0300622. [PMID: 38603682 PMCID: PMC11008855 DOI: 10.1371/journal.pone.0300622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/03/2024] [Indexed: 04/13/2024] Open
Abstract
Breast cancer is one of the most often diagnosed cancers in women, and identifying breast cancer histological images is an essential challenge in automated pathology analysis. According to research, the global BrC is around 12% of all cancer cases. Furthermore, around 25% of women suffer from BrC. Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. Using a BreakHis dataset, we demonstrated in this work the viability of automatically identifying and classifying BrC. The first stage is pre-processing, which employs an Adaptive Switching Modified Decision Based Unsymmetrical Trimmed Median Filter (ASMDBUTMF) to remove high-density noise. After the image has been pre-processed, it is segmented using the Thresholding Level set approach. Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. The suggested strategy facilitates the acquisition of precise functionality attributes, hence simplifying the detection procedure. Additionally, it aids in resolving problems pertaining to global optimization. Following the selection, the best characteristics proceed to the categorization procedure. A DL classifier called the Conditional Variation Autoencoder is used to discriminate between cancerous and benign tumors while categorizing them. Consequently, a classification accuracy of 99.4%, Precision of 99.2%, Recall of 99.1%, F- score of 99%, Specificity of 99.14%, FDR of 0.54, FNR of 0.001, FPR of 0.002, MCC of 0.98 and NPV of 0.99 were obtained using the proposed approach. Furthermore, compared to other research using the current BreakHis dataset, the results of our research are more desirable.
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Affiliation(s)
- Afnan M. Alhassan
- College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia
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4
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He X, Ji J, Qdaisat A, Esteva FJ, Yeung SCJ. Long-term overall survival of patients who undergo breast-conserving therapy or mastectomy for early operable HER2-Positive breast cancer after preoperative systemic therapy: an observational cohort study. LANCET REGIONAL HEALTH. AMERICAS 2024; 32:100712. [PMID: 38495316 PMCID: PMC10943473 DOI: 10.1016/j.lana.2024.100712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 02/15/2024] [Accepted: 02/26/2024] [Indexed: 03/19/2024]
Abstract
Background Understanding the survival outcomes associated with breast-conserving therapy (BCT) and mastectomy after preoperative systemic therapy (PST) enables clinicians to provide more personalized treatment recommendations. However, lack of firm survival benefit data limits the breast surgery choices of human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients who receive PST. We sought to determine whether BCT or mastectomy after PST for early operable HER2-positive breast cancer is associated with better long-term survival outcomes and determine the degree to which PST response affects this association. Methods In this observational cohort study, we compared the long-term survival outcomes of BCT and mastectomy after PST for HER2-positive breast cancer and evaluated the impact of PST response on the relationship between breast surgery performed and survival outcomes. Our cohort included 625 patients with early operable HER2-positive breast cancer who received PST followed by BCT or mastectomy between January 1998 and October 2009. These patients also received standard postoperative radiation, trastuzumab, and endocrine therapy as indicated clinically. We used propensity score matching to assemble mastectomy and BCT cohorts with similar baseline characteristics and used Kaplan-Meier plots and Cox proportional hazards regression to detect associations between surgery types and outcomes. Furthermore, in this study, we analyzed the original data of 625 patients using the inverse probability of treatment weighting (IPTW) method to enhance the reliability of the comparison between the mastectomy and BCT cohorts by addressing potential confounding variables. Findings Propensity score matching yielded cohorts of 221 patients who received BCT and 221 patients who underwent mastectomy. At the median follow-up time of 9.9 years, compared with BCT, mastectomy was associated with worse overall survival (hazard ratio, 1.66; 95% confidence interval [CI]: 1.08-2.57; P = 0.02). In patients who had axillary lymph node pathological complete response, mastectomy was associated with worse overall survival before matching (hazard ratio, 2.17; 95% CI: 1.22-3.86; P < 0.01) and after matching (hazard ratio, 2.12; 95% CI: 1.15-3.89; P = 0.02). Among patients with pathological complete response in the breast, the survival results did not differ significantly between BCT and mastectomy patients. IPTW method validated that BCT offers better overall survival in patients who had axillary lymph node pathological complete response. Interpretation People with HER2-positive breast cancer who have already had PST are more likely to survive after BCT, especially if they get a pathological complete response in the axillary lymph nodes. These findings underscore the necessity for further investigation into how responses to PST can inform the choice of surgical intervention and the potential impact on overall survival. Such insights could lead to the development of innovative tools that support personalized surgical strategies in the management of breast cancer. Funding This work was supported by grants from the Nantong Science and Technology Project (JCZ2022079), Nantong Health Commission Project (QA2021031, MSZ2023040) and National Natural Science Foundation of China (No. 82394430).
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Affiliation(s)
- Xuexin He
- Department of Medical Oncology, Huashan Hospital of Fudan University, Shanghai, China
- Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jiali Ji
- Department of Medical Oncology, Nantong Tumor Hospital, Affiliated Tumor Hospital of Nantong University, Nantong, Jiangsu, China
| | - Aiham Qdaisat
- Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Francisco J. Esteva
- Division of Hematology/Oncology, Northwell Health Cancer Institute at Lenox Hill Hospital, New York, NY, USA
| | - Sai-Ching J. Yeung
- Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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5
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Xu X, Zhao W, Liu C, Gao Y, Chen D, Wu M, Li C, Wang X, Song X, Yu J, Liu Z, Yu Z. The residual cancer burden index as a valid prognostic indicator in breast cancer after neoadjuvant chemotherapy. BMC Cancer 2024; 24:13. [PMID: 38166846 PMCID: PMC10762907 DOI: 10.1186/s12885-023-11719-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/05/2023] [Indexed: 01/05/2024] Open
Abstract
PURPOSE The residual cancer burden index (RCB) was proposed as a response evaluation criterion in breast cancer patients treated with Neoadjuvant Chemotherapy (NAC). This study evaluated the relevance of RCB with replase-free survival (RFS). METHODS The clinical data of 254 breast cancer patients who received NAC between 2016 and 2020 were retrospectively collected. The relationship between clinicopathologic factors and RFS was evaluated using Cox proportional hazards regression models. RFS estimates were determined by Kaplan-Meier(K-M) analysis and compared using the log-rank test. Multivariate logistic regression analysis was used to evaluate the risk factors associated with RCB. Receiver operating characteristic (ROC) curves showed the potential of the RCB and MP grading systems as biomarkers for RFS. RESULTS At a median follow-up of 52 months, 59 patients(23.23%) developed relapse. Multivariate Cox regression showed that older age (P = 0.022), high Pathologic T stage after NAC (P = 0.023) and a high RCB score(P = 0.003) were risk factors for relapse. The outcomes of the multivariate logistic analysis indicated that RCB 0 (pathologic complete response [pCR]) was associated with HER2-positive patients (P = 0.002) and triple-negative breast cancer (TNBC) patients (P = 0.013). In addition, the RCB and MP scoring systems served as prognostic markers for patients who received NAC, and their area under curves (AUCs) were 0.691 and 0.342, respectively. CONCLUSION These data suggest that RCB can be equally applied to predict RFS in Chinese patients with NAC. The application of RCB may help guide the selection of treatment strategies.
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Affiliation(s)
- Xin Xu
- Tianjin Medical University Cancer Institute & Hospital,National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin, 300000, China
- Departments of Oncology, The Second Affiliated Hospital of Shandong First Medical University, Shandong Province, Tai'an, 271000, China
| | - Wei Zhao
- Affiliated Hospital of Jining Medical University, Jining, 272060, China
| | - Cuicui Liu
- Liaocheng People's Hospital, Liaocheng, China
| | - Yongsheng Gao
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Dawei Chen
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Meng Wu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Chao Li
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Xinzhao Wang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Xiang Song
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Jinming Yu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China
| | - Zhaoyun Liu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China.
| | - Zhiyong Yu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China.
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6
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Li X, Lin Z, Yu Q, Qiu C, Lai C, Huang H, Zhang Y, Zhang W, Zhu J, Huang X, Li W. Development and validation of a prognostic model for HER2-low breast cancer to evaluate neoadjuvant therapy. Gland Surg 2023; 12:183-196. [PMID: 36915818 PMCID: PMC10005989 DOI: 10.21037/gs-22-729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/06/2023] [Indexed: 02/17/2023]
Abstract
Background Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC) accounts for 30-51% of all BCs. How to precisely assess the response to neoadjuvant therapy in this heterogenous tumor is currently unanswered. With the advance in multi-omics, refining the molecular subtyping other than the current hormone receptor (HR)-based subtyping to guide the neoadjuvant therapy for HER2-low BC is potentially feasible. Methods The messenger RNA (mRNA), clinical, and pathological data of all HER2-low BC patients (n=368) from the Neoadjuvant I-SPY2 Trial, were retrieved. Ninety-eight patients achieved pathological complete response (pCR) were randomly divided into the training and validation sets with 8:2 ratio. The non-pCR cases were corporated into the above datasets with 1:1 ratio. The rest non-pCR cases were served as the test set. Random forest (RF), support vector machine (SVM), and fully connected neural network (FCNN) were applied to establish a 1-dimensional (1D) model based on mRNA data. The method with best prediction value among the 3 models was selected for further modeling when combining pathological features. A new classification of deep learning (CDn) was proposed based on a multi-omics model. After identifying pCR-related features by the integral gradient and unsupervised hierarchical clustering method, the responses to neoadjuvant therapy associated with these features across different subgroups were analyzed. Results Compared with the RF and SVM models, the FCNN model achieved the best performance [area under the curve (AUC): 0.89] based on the mRNA feature. By combining mRNA and pathological features, the FCNN model proposed 2 new subtypes including CD1 and CD0 for HER2-low BC. CD1 increased the sensitivity to predict pCR by 23.5% [to 87.8%; 95% confidence interval (CI): 78% to 94%] and improved the specificity to pCR by 12.2% (to 77.4%; 95% CI: 69% to 87%) when comparing with the current HR classification for HER2-low BC. Conclusions The new typing method (CD1 and CD0) proposed in this study achieved excellent performance for predicting the pCR to neoadjuvant therapy in HER2-low BC. The patients who were not sensitive to neoadjuvant therapy according to multi-omics models might receive surgical treatment directly.
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Affiliation(s)
- Xiaoping Li
- Department of Breast, Jiangmen Central Hospital, Jiangmen, China
| | - Zhiquan Lin
- Wuyi University, Faculty of Intelligent Manufacturing, Jiangmen, China
| | - Qihe Yu
- Department of Oncology, Jiangmen Central Hospital, Jiangmen, China
| | - Chaoran Qiu
- Department of Breast, Jiangmen Central Hospital, Jiangmen, China
| | - Chan Lai
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, China
| | - Hui Huang
- Department of Breast Surgery, Jiangmen Maternity & Child Health Care Hospital, Jiangmen, China
| | - Yiwen Zhang
- Department of Breast, Jiangmen Central Hospital, Jiangmen, China
| | - Weibin Zhang
- Department of Pathology, Jiangmen Central Hospital, Jiangmen, China
| | - Jintao Zhu
- Department of Breast Surgery, Foshan Fosun Chancheng Hospital, Foshan, China
| | - Xin Huang
- Department of Breast Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Weiwen Li
- Department of Breast, Jiangmen Central Hospital, Jiangmen, China
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7
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Rossi EMC, Invento A, Pesapane F, Pagan E, Bagnardi V, Fusco N, Venetis K, Dominelli V, Trentin C, Cassano E, Gilardi L, Mazza M, Lazzeroni M, De Lorenzi F, Caldarella P, De Scalzi A, Girardi A, Sangalli C, Alberti L, Sacchini V, Galimberti V, Veronesi P. Diagnostic performance of image-guided vacuum-assisted breast biopsy after neoadjuvant therapy for breast cancer: prospective pilot study. Br J Surg 2023; 110:217-224. [PMID: 36477768 PMCID: PMC10364486 DOI: 10.1093/bjs/znac391] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 07/14/2022] [Accepted: 10/23/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Image-guided vacuum-assisted breast biopsy (VABB) of the tumour bed, performed after neoadjuvant therapy, is increasingly being used to assess residual cancer and to potentially identify to identify pathological complete response (pCR). In this study, the accuracy of preoperative VABB specimens was assessed and compared with surgical specimens in patients with triple-negative or human epidermal growth factor receptor 2 (HER2)-positive invasive ductal breast cancer after neoadjuvant therapy. As a secondary endpoint, the performance of contrast-enhanced MRI of the breast and PET-CT for response prediction was assessed. METHODS This single-institution prospective pilot study enrolled patients from April 2018 to April 2021 with a complete response on imaging (iCR) who subsequently underwent VABB before surgery. Those with a pCR at VABB were included in the primary analysis of the accuracy of VABB. The performance of imaging (MRI and PET-CT) was analysed for prediction of a pCR considering both patients with an iCR and those with residual disease at postneoadjuvant therapy imaging. RESULTS Twenty patients were included in the primary analysis. The median age was 44 (range 35-51) years. At surgery, 18 of 20 patients showed a complete response (accuracy 90 (95 per cent exact c.i. 68 to 99) per cent). Only two patients showed residual ductal intraepithelial neoplasia of grade 2 and 3 respectively. In the secondary analysis, accuracy was similar for MRI and PET-CT (77 versus 78 per cent; P = 0.76). CONCLUSION VABB in patients with an iCR might be a promising method to select patients for de-escalation of surgical treatment in triple-negative or HER2-positive breast cancer. The present results support such an approach and should inform the design of future trials on de-escalation of surgery.
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Affiliation(s)
| | - Alessandra Invento
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Filippo Pesapane
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Eleonora Pagan
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, Milan, Italy
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, Milan, Italy
| | - Nicola Fusco
- Division of Pathology, IEO European Institute of Oncology IRCSS, Milan, Italy.,Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Konstantinos Venetis
- Division of Pathology, IEO European Institute of Oncology IRCSS, Milan, Italy.,Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Valeria Dominelli
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Chiara Trentin
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Laura Gilardi
- Division of Nuclear Medicine, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Manuelita Mazza
- Division of Medical Senology, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Matteo Lazzeroni
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Francesca De Lorenzi
- Department of Plastic and Reconstructive Surgery, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Pietro Caldarella
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | | | - Antonia Girardi
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Claudia Sangalli
- Data Management, European Institute of Oncology IRCCS, Milan, Italy
| | - Luca Alberti
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Virgilio Sacchini
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy.,Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy.,Breast Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Viviana Galimberti
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Paolo Veronesi
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy.,Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
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8
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Ciriaco N, Zamora E, Escrivá-de-Romaní S, Miranda Gómez I, Jiménez Flores J, Saura C, Sloane H, Starus A, Fredebohm J, Georgieva L, Speight G, Jones F, Ramón y Cajal S, Espinosa-Bravo M, Peg V. Clearance of ctDNA in triple-negative and HER2-positive breast cancer patients during neoadjuvant treatment is correlated with pathologic complete response. Ther Adv Med Oncol 2022; 14:17588359221139601. [PMID: 36479470 PMCID: PMC9720791 DOI: 10.1177/17588359221139601] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 10/31/2022] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Although the standard of care is to perform surgery of primary breast cancer (BC) after neoadjuvant chemotherapy (NAC), for certain patients achieving clinical complete response (cCR) and pathologic complete response (pCR), omission of surgical treatment may be an option. Levels of circulating tumor DNA (ctDNA) during and after therapy could identify patients achieving minimal residual disease. In this study, we evaluated whether ctDNA clearance during NAC could be a correlate to effective response in human epidermal growth factor receptor 2 positive (HER2+) and triple-negative (TN) BC patients. METHODS A prospective study was conducted to identify patient-specific PIK3CA and TP53 mutations in tissue using next-generation sequencing, which could then be used to track the presence/absence of mutations prior to, during, and following NAC using Sysmex SafeSEQ technology. All patients underwent a surgical excision after NAC, and pCR was assessed. RESULTS A total of 29 TN and HER2+ BC patients were examined and 20 that carried mutations in the PIK3CA and/or TP53 genes were recruited. Overall, 19 of these 20 patients harbored at least one tumor-specific mutation in their plasma at baseline. After NAC, 15 patients (75.0%) achieved pCR according to the histopathologic evaluation of the surgical specimen, and 15 patients (75.0%) had a cCR; 18 of 20 patients (90.0%) had concordant pCR and cCR. The status of 'no mutation detected' (NMD) following NAC in cCR patients correctly identified the pCR in 14 of 15 patients (93.33%), as well as correctly ruled out pCR in three patients, with an accuracy of 89.47%. During the 12-month follow-up after surgery, 40 plasma samples collected from 15 patients all showed no detectable ctDNA (NMD), and no patient recurred. CONCLUSION These findings prompt further research of the value of ctDNA for non-invasive prediction of clinical/pathological response, raising the possibility of sparing surgery following NAC in selected BC patients.
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Affiliation(s)
- Nikaoly Ciriaco
- Pathology Department, Hospital del Mar, Barcelona, Spain
- Universidad Autónoma de Barcelona, Barcelona, Spain
| | - Esther Zamora
- Universidad Autónoma de Barcelona, Barcelona, Spain
- Breast Cancer Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Medical Oncology Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | - Santiago Escrivá-de-Romaní
- Breast Cancer Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Medical Oncology Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | | | - José Jiménez Flores
- Molecular Oncology Lab. Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Cristina Saura
- Medical Oncology Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | - Hillary Sloane
- Sysmex Inostics, Inc., Baltimore, MD, USA
- Sysmex Inostics GmbH, Hamburg, Germany
| | - Anna Starus
- Sysmex Inostics, Inc., Baltimore, MD, USA
- Sysmex Inostics GmbH, Hamburg, Germany
| | - Johannes Fredebohm
- Sysmex Inostics, Inc., Baltimore, MD, USA
- Sysmex Inostics GmbH, Hamburg, Germany
| | | | | | - Frederick Jones
- Sysmex Inostics, Inc., Baltimore, MD, USA
- Sysmex Inostics GmbH, Hamburg, Germany
| | - Santiago Ramón y Cajal
- Universidad Autónoma de Barcelona, Barcelona, Spain
- Pathology Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Spanish Biomedical Research Network Centre in Oncology (CIBERONC), Madrid, Spain
| | | | - Vicente Peg
- Universidad Autónoma de Barcelona, Barcelona, Spain
- Pathology Department, Vall d’Hebron University Hospital, Paseo Vall d’Hebron 119-129, Barcelona 08035, Spain
- Spanish Biomedical Research Network Centre in Oncology (CIBERONC), Madrid, Spain
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9
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Pesapane F, Agazzi GM, Rotili A, Ferrari F, Cardillo A, Penco S, Dominelli V, D'Ecclesiis O, Vignati S, Raimondi S, Bozzini A, Pizzamiglio M, Petralia G, Nicosia L, Cassano E. Prediction of the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients With MRI-Radiomics: A Systematic Review and Meta-analysis. Curr Probl Cancer 2022; 46:100883. [PMID: 35914383 DOI: 10.1016/j.currproblcancer.2022.100883] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 12/30/2022]
Abstract
We performed a systematic review and a meta-analysis of studies using MRI-radiomics for predicting the pathological complete response in breast cancer patients undergoing neoadjuvant therapy , and we evaluated their methodological quality using the radiomics-quality-score (RQS). Random effects meta-analysis was performed pooling area under the receiver operating characteristics curves. Publication-bias was assessed using the Egger's test and visually inspecting the funnel plot. Forty-three studies were included in the qualitative review and 34 in the meta-analysis. Summary area under the receiver operating characteristics curve was 0,78 (95%CI:0,74-0,81). Heterogeneity according to the I2 statistic was substantial (71%) and there was no evidence of publication bias (P-value = 0,2). The average RQS was 12,7 (range:-1-26), with an intra-class correlation coefficient of 0.93 (95%CI:0.61-0.97). Year of publication, field intensity and synthetic RQS score do not appear to be moderators of the effect (P-value = 0.36, P-value = 0.28 and P-value = 0.92, respectively). MRI-radiomics may predict response to neoadjuvant therapy in breast cancer patients but the heterogeneity of the current studies is still substantial.
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Affiliation(s)
- Filippo Pesapane
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy.
| | | | - Anna Rotili
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Federica Ferrari
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Andrea Cardillo
- Radiology Department, Università degli studi di Torino, Turin, Italy
| | - Silvia Penco
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Valeria Dominelli
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Oriana D'Ecclesiis
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Silvano Vignati
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Sara Raimondi
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Anna Bozzini
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Maria Pizzamiglio
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Giuseppe Petralia
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Luca Nicosia
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
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10
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Increasing Imaging Value to Breast Cancer Care Through Prognostic Modeling of Multiparametric MRI Features in Patients Undergoing Neoadjuvant Chemotherapy. Acad Radiol 2022; 29 Suppl 1:S164-S165. [PMID: 35033453 DOI: 10.1016/j.acra.2021.12.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 11/23/2022]
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11
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Franceschini G, Mason EJ, Orlandi A, D'Archi S, Sanchez AM, Masetti R. How will artificial intelligence impact breast cancer research efficiency? Expert Rev Anticancer Ther 2021; 21:1067-1070. [PMID: 34214007 DOI: 10.1080/14737140.2021.1951240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Gianluca Franceschini
- Multidisciplinary Breast Center, Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Elena Jane Mason
- Multidisciplinary Breast Center, Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Armando Orlandi
- Division of Medical Oncology, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Sabatino D'Archi
- Multidisciplinary Breast Center, Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Alejandro Martin Sanchez
- Multidisciplinary Breast Center, Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Riccardo Masetti
- Multidisciplinary Breast Center, Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
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12
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The use of breast ultrasound for prediction of pathologic complete response in different subtypes of early breast cancer within the WSG-ADAPT subtrials. Breast 2021; 59:58-66. [PMID: 34166854 PMCID: PMC8239457 DOI: 10.1016/j.breast.2021.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 06/03/2021] [Accepted: 06/04/2021] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE We assessed the value of breast ultrasound (US) performed at week 3 and 6 and at the end (EOT) of neoadjuvant therapy (NAT) for prediction of pathologic complete response (pCR, ypT0/is ypN0) in patients with HR+/HER2+, HR-/HER2-or HR-/HER2+ early breast cancer enrolled in the WSG-ADAPT subtrials. METHODS US was performed at week 3 and 6 of NAT and at EOT in 401, 517, and 553 patients, respectively. Tumors with complete or partial response by US (RECIST 1.1) were classified as responders and those with stable or progressive disease as non-responders. RESULTS pCR rate was higher in US responders than in non-responders. US tended to yield the highest positive predictive value in HR-/HER2+ (69%) and HR-/HER2-tumors (65%) at week 3, and the highest negative predictive value in HR+/HER2+ tumors at week 6 and at EOT (88.9% and 86.9%, respectively) and in HR-/HER2-tumors at EOT (87.9%). Multivariable analysis of patients with US at week 3 and 6 identified tumor subtype (HR-/HER2+ vs HR+/HER2+; odds ratio (OR) 2.77, 95%CI 1.45-5.29, and OR 4.17, 95%CI 2.26-7.68, respectively) and each 10% change in lesion dimension on US from baseline (OR 1.15, 95%CI 1.08-1.24, and OR 1.25, 95%CI 1.16-1.35, respectively) as parameters associated with pCR. CONCLUSIONS Our data support the use of week 3 and EOT US for prediction of pCR in response-guided NAT and in planning of breast-conserving surgery. Change in tumor diameter on US as a continuous variable could be a valuable alternative to categorical RECIST 1.1 criteria.
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13
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Ishitobi M, Hayashi N. ASO Author Reflections: What will be Required to Safely Omit Breast Surgery for Early-Stage Breast Cancer? Ann Surg Oncol 2020; 28:2553-2554. [PMID: 33047247 DOI: 10.1245/s10434-020-09195-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 09/19/2020] [Indexed: 11/18/2022]
Affiliation(s)
- Makoto Ishitobi
- Department of Breast and Endocrine Surgery, Osaka International Cancer Institute, Osaka, Japan. .,Department of Breast Surgery, Mie University Hospital, Mie, Japan.
| | - Naoki Hayashi
- Department of Breast Surgical Oncology, St. Luke's International Hospital, Tokyo, Japan
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