scholarly journals Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamidreza Taleghamar ◽  
Hadi Moghadas-Dastjerdi ◽  
Gregory J. Czarnota ◽  
Ali Sadeghi-Naini
Keyword(s):  
Breast Cancer ◽  
Treatment Response ◽  
Quantitative Ultrasound ◽  
Parametric Imaging ◽  
Term Survival ◽  
Adaptive Boosting ◽  
Tumor Margin ◽  
Parametric Images ◽  
Response To Chemotherapy ◽  
Pre Treatment

AbstractThe efficacy of quantitative ultrasound (QUS) multi-parametric imaging in conjunction with unsupervised classification algorithms was investigated for the first time in characterizing intra-tumor regions to predict breast tumor response to chemotherapy before the start of treatment. QUS multi-parametric images of breast tumors were generated using the ultrasound radiofrequency data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for neo-adjuvant chemotherapy followed by surgery. A hidden Markov random field (HMRF) expectation maximization (EM) algorithm was applied to identify distinct intra-tumor regions on QUS multi-parametric images. Several features were extracted from the segmented intra-tumor regions and tumor margin on different parametric images. A multi-step feature selection procedure was applied to construct a QUS biomarker consisting of four features for response prediction. Evaluation results on an independent test set indicated that the developed biomarker coupled with a decision tree model with adaptive boosting (AdaBoost) as the classifier could predict the treatment response of patient at pre-treatment with an accuracy of 85.4% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.89. In comparison, the biomarkers consisted of the features derived from the entire tumor core (without consideration of the intra-tumor regions), and the entire tumor core and the tumor margin could predict the treatment response of patients with an accuracy of 74.5% and 76.4%, and an AUC of 0.79 and 0.76, respectively. Standard clinical features could predict the therapy response with an accuracy of 69.1% and an AUC of 0.6. Long-term survival analyses indicated that the patients predicted by the developed model as responders had a significantly better survival compared to the non-responders. Similar findings were observed for the two response cohorts identified at post-treatment based on standard clinical and pathological criteria. The results obtained in this study demonstrated the potential of QUS multi-parametric imaging integrated with unsupervised learning methods in identifying distinct intra-tumor regions in breast cancer to characterize its responsiveness to chemotherapy prior to the start of treatment.

scholarly journals Long-term Outcomes of Pregnancy-Associated Breast Cancer: A Single Institution Experience

2021 ◽  
Keyword(s):  
Breast Cancer ◽  
Triple Negative ◽  
Long Term Outcomes ◽  
Single Institution ◽  
Term Survival ◽  
Long Term Survival ◽  
Response To Chemotherapy ◽  
Her 2

Background: The incidence of pregnancy-associated breast cancer (PABC) is increasing, especially in the developed countries. Herein, we report the long-term outcomes of PABC from a single institution in an Arab country. Methods: Consecutive patients diagnosed to have PABC between 2005 and 2012 at a tertiary referral hospital from a Gulf cooperation council country were the subjects of the study. Long-term outcomes are reported, with a minimum follow-up of 8 years. Results: A total of 16 patients were evaluable for long-term survival analysis. The median age at the time of diagnosis was 31.5 (26-40) years. Nine (56%) patients were multiparous (> 5 previous pregnancies). The mean gestational age at diagnosis was 19.7±7.4 weeks. Immunohistochemistry revealed the following phenotypes: Luminal A 3 (18.8%); HER-2 enriched 8 (50%); triple-negative 5 (31.2%). Three patients underwent modified radical mastectomy as the initial treatment, of which 2 received adjuvant chemotherapy during pregnancy. For patients who received neoadjuvant or palliative chemotherapy, the response rate was 75% (pCR 2; CR 1; PR 6). After a median follow-up of 60 months, median progression-free survival was 36 months (95%CI 24.2 to 47.8), while the overall survival was 59 months (95%CI 31.6 – 86.4). Age, marker status, Ki-67 score, clinical stage and differentiation grade did not affect the PFS or OS on univariate analysis. Conclusions: Fifty percent of the patient with PABC expressed HER-2/neu protein, and 1/3rd had triple-negative disease. The rate of response to chemotherapy, and long-term survival may help to set a benchmark for studies from the region. Larger cohort studies may help to draw firm conclusions.

Response to neoadjuvant therapy and long-term survival in patients with triple-negative breast cancer (TNBC) in a Peruvian institute.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e12038-e12038
Author(s):  
Katerin Ingrid Rojas
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Pathologic Complete Response ◽  
Neoadjuvant Treatment ◽  
Complete Response ◽  
Age At Diagnosis ◽  
Term Survival ◽  
Response To Chemotherapy ◽  
Significant Difference ◽  
The Mean

e12038 Background: TNBC is defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 expressions (HER-2). This molecular classification is an excellent prognostic and predictive method in breast cancer (BC). This is an aggressive malignancy with a poor prognosis despite the high rates of response to chemotherapy. Methods: Observational descriptive. We included 165 patients with TNBC stage I-III who received neoadjuvant chemotherapy at National Cancer Institute of Peru from 2000 to 2010. Clinical and pathologic complete response rates, survival measurements, and organ-specific rates of relapse were evaluated. Overall survival (OS) and disease free survival (DFS). Results: The mean age at diagnosis was 48.6 years (range, 24-74 years). The mean size tumor before treatment was 7.7 cm (range, 1-25 cm). One hundred and fifty seven patients (95.2%) had ductal carcinoma. One hundred twenty nine cases (78.2%) were histological grade III. According to T stage, 65 (39.4%) T3 and 83 (50.3%) T4. Thirty four cases (20.6%) were N0. Seventy three patients (44.2%) received AC-Paclitaxel schedule. Thirty four patients (20.6%) had CR to neoadjuvant chemotherapy. There is a significant difference about tumor size before and after neoadjuvant treatment (7.7 vs. 3.6, p<0.05).OS at 5 years for patients with residual disease was 83.5%. In patients with complete response the DFS at 5 years was 55.1%. Locoregional and lung were the most frequent site of recurrence (15.8%) and (13.9%) respectively. According Miller and Paine to grade tumor response, 17 patients(10.3%) I ,33 (20.0%) II, 33 (20.0%) III, 20 (12.1%) IV and 27 (16.4%) V. Node response, 20 patients (12.1%) had type A, 51 (30.9%) type B, 23 (13.9%) type C and 34 (20.6%) type D. Conclusions:These results suggest that most TNBC are in accordance with literature data, especially concerning young age at diagnosis, high grade tumors, advances locally stage at diagnosis, and short time to relapse, high response rate to chemotherapy and excellent OS and DFS. We know it is a heterogeneous disease; however the clinical characteristics still play an important role to predict treatment response and survival.

scholarly journals Circulating tumour cell enumeration does not correlate with Miller-Payne grade in a cohort of breast cancer patients undergoing neoadjuvant chemotherapy

2019 ◽  
Author(s):  
Sharon O'Toole ◽  
Cathy Spillane ◽  
Yanmei Huang ◽  
Marie Fitzgerald ◽  
Brendan Ffrench ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Ductal Carcinoma ◽  
Lobular Carcinoma ◽  
Complete Response ◽  
Pathological Response ◽  
Breast Cancer Patients ◽  
Response To Chemotherapy ◽  
Pre Treatment

Abstract Background: Detection and enumeration of Circulating Tumour Cells (CTCs) has been evaluated in many cancers such as breast cancer. However, the full prognostic and predictive power of CTCs for cancer cannot currently be harnessed, and the association between pathological complete response in patients receiving neoadjuvant chemotherapy for breast cancer and CTCs is still not clear. The aim of this study was to assess if CTCs could be used to predict pathological response to neoadjuvant chemotherapy in breast cancer patients. Methods: 26 patients were recruited, and blood samples taken pre- and post-neoadjuvant chemotherapy. CTCs were isolated using the ScreenCell device and stained using a modified Giemsa stain. CTCs were enumerated by 2 pathologists and classified as single CTCs, doublets clusters/microemboli. Counts were then correlated to the pathological response as measured by the Miller-Payne grading system. The associations between CTCs and clusters and pathological variables were evaluated with χ2 or ANOVA tests performed in the SPSS 24.0 statistics software. Results: 89% of the patients had invasive ductal carcinoma and 11% invasive lobular carcinoma. At baseline 85% of patients had CTCs present and only 4 patients were CTC negative. Median baseline CTC count was 7 (0-161) CTCs per 3mls of whole blood. Post chemotherapy, 58% of the patients had an increase in CTCs. This change in CTC count did not correlate with the Miller Payne grade of response to chemotherapy. No significant association was identified between the number of CTCs and clinical characteristics, including patient age, receptor status, tumour grade, disease type, lymph node metastasis, lymphovascular space invasion, radiological response or clinical or pathological stage. However, we did observe a correlation between pre-treatment CTC counts and body mass index, p<0.05. Conclusions: There was no correlation between the pre- and post-chemotherapy total number of CTCs/clusters and the Miller Payne grade. It is not enough to evaluate pathological response for neoadjuvant chemotherapy for breast cancer patients utilising CTCs identified by Giemsa staining alone. Additional characterisation is needed to further characterise CTCs isolated pre- and post-chemotherapy. Long-term follow-up of these patients will determine the significance of CTCs in breast cancer patients undergoing neoadjuvant chemotherapy.

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