CARLOS SHIMIZU
Índice h a partir de 2011
5
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Câncer do Estado de São Paulo, Hospital das Clínicas, Faculdade de Medicina - Médico
LIM/24 - Laboratório de Oncologia Experimental, Hospital das Clínicas, Faculdade de Medicina
LIM/24 - Laboratório de Oncologia Experimental, Hospital das Clínicas, Faculdade de Medicina
7 resultados
Resultados de Busca
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- Core needle biopsy in fibroepithelial tumors: predicting factors for phyllodes tumors(2021) REIS, Yedda Nunes; MAESAKA, Jonathan Yugo; SHIMIZU, Carlos; SOARES-JUNIOR, Jose Maria; BARACAT, Edmund Chada; FILASSI, Jose RobertoOBJECTIVES: This study aimed to evaluate the clinical and imaging predictive factors for the diagnosis of phyllodes tumors in patients with inconclusive results from core needle biopsy (fibroepithelial lesions). METHODS: We retrospectively analyzed data of patients who underwent surgical excision of breast lesions previously diagnosed as fibroepithelial lesions. Numeric variables were analyzed using the Shapiro-Wilk and t-tests, and categorical variables were analyzed using the chi-square and Fisher's exact tests. Multivariate logistic regression was performed to calculate odds ratios and detect predictive factors for the diagnosis of PT. RESULTS: A total of 89 biopsy samples were obtained from 77 patients, of which 43 were confirmed as fibroadenomas, 43 as phyllodes tumors, and 3 as other benign, non-fibroepithelial breast lesions. The mean tumor size was 3.61 cm (range, 0.8-10 cm) for phyllodes tumors and 2.4 cm (range, 0.8-7.9 cm) for fibroadenomas. The predictive factor for phyllodes tumor diagnosis was lesion size >3 cm (p< 0.001). CONCLUSION: Our data indicate that fibroepithelial lesions of the breast larger than 3 cm are more likely to be phyllodes tumors.
- Pre-treatment MRI tumor features and post-treatment mammographic findings: may they contribute to refining the prediction of pathologic complete response in post-neoadjuvant breast cancer patients with radiologic complete response on MRI?(2022) THOMPSON, Bruna M.; CHALA, Luciano F.; SHIMIZU, Carlos; MANO, Max S.; FILASSI, Jose R.; GEYER, Felipe C.; TORRES, Ulysses S.; MELLO, Giselle Guedes Netto de; LEITE, Claudia da CostaPurpose Radiologic complete response (rCR) in breast cancer patients after neoadjuvant chemotherapy (NAC) does not necessarily correlate with pathologic complete response (pCR), a marker traditionally associated with better outcomes. We sought to verify if data extracted from two important steps of the imaging workup (tumor features at pre-treatment MRI and post-treatment mammographic findings) might assist in refining the prediction of pCR in post-NAC patients showing rCR. Methods A total of 115 post-NAC women with rCR on MRI (2010-2016) were retrospectively assessed. Pre-treatment MRI (lesion morphology, size, and distribution) and post-treatment mammographic findings (calcification, asymmetry, mass, architectural distortion) were assessed, as well as clinical and molecular variables. Bivariate and multivariate analyses evaluated correlation between such variables and pCR. Post-NAC mammographic findings and their correlation with ductal in situ carcinoma (DCIS) were evaluated using Pearson's correlation. Results Tumor distribution at pre-treatment MRI was the only significant predictive imaging feature on multivariate analysis, with multicentric lesions having lower odds of pCR (p = 0.035). There was no significant association between tumor size and morphology with pCR. Mammographic residual calcifications were associated with DCIS (p = 0.009). The receptor subtype remained as a significant predictor, with HR-HER2 + and triple-negative status demonstrating higher odds of pCR on multivariate analyses. Conclusions Multicentric lesions on pre-NAC MRI were associated with a lower chance of pCR in post-NAC rCR patients. The receptor subtype remained a reliable predictor of pCR. Residual mammographic calcifications correlated with higher odds of malignancy, making the correlation between mammography and MRI essential for surgical planning.
- AXILLARY LYMPH NODE SONOGRAPHIC FEATURES AND BREAST TUMOR CHARACTERISTICS AS PREDICTORS OF MALIGNANCY: A NOMOGRAM TO PREDICT RISK(2017) TEIXEIRA, Patricia Akissue de Camargo; CHALA, Luciano F.; SHIMIZU, Carlos; FILASSI, Jose R.; MAESAKA, Jonathan Y.; BARROS, Nestor deThe purpose of this study was to build a mathematical model to predict the probability of axillary lymph node metastasis based on the ultrasonographic features of axillary lymph nodes and the tumor characteristics. We included 74 patients (75 axillae) with invasive breast cancer who underwent axillary ultrasonography ipsilateral to the tumor and fine-needle aspiration of one selected lymph node. Lymph node pathology results from sentinel lymph node biopsy or surgical dissection were correlated with lymph node ultrasonographic data and with the cytologic findings of fine-needle aspiration. Our mathematical model of prediction risk of lymph node metastasis included only pre-surgical data from logistic regression analysis: lymph node cortical thickness (p = 0.005), presurgical tumor size (p = 0.030), menopausal status (p = 0.017), histologic type (p = 0.034) and tumor location (p = 0.011). The area under the receiver operating characteristic curve of the model was 0.848, reflecting an excellent discrimination of the model. This nomogram may assist in the choice of the optimal axillary approach. (E-mail: pakissue@gmail.com) (C) 2017 World Federation for Ultrasound in Medicine & Biology.
- Pathological macroscopic evaluation of breast density versus mammographic breast density in breast cancer conserving surgery(2023) REIS, Yedda Nunes; MOTA, Bruna Salani; MOTA, Rosa Maria Salani; SHIMIZU, Carlos; RICCI, Marcos Desiderio; AGUIAR, Fernando Nalesso; SOARES-JR, Jose Maria; BARACAT, Edmund Chada; FILASSI, Jose RobertoCorrelation between imaging and anatomopathological breast density has been superficially explored and is heterogeneous in current medical literature. It is possible that mammographic and pathological findings are divergent. The aim of this study is to evaluate the association between breast density classified by mammography and breast density of pathological macroscopic examination in specimens of breast cancer conservative surgeries. Post-hoc, exploratory analysis of a prospective randomized clinical trial of patients with breast cancer candidates for breast conservative surgery. Breast mammographic density (MD) was analyzed according to ACR BI-RADS (R) criteria, and pathologic macroscopic evaluation of breast density (PMBD) was estimated by visually calculating the ratio between stromal and fatty tissue. From 412 patients, MD was A in 291 (70,6%), B in 80 (19,4%) B, C in 35 (8,5%), and D in 6 (1,5%). Ninety-nine percent (201/203) of patients classified as A+B in MD were correspondently classified in PMBD. Conversely, only 18.7% (39/209) of patients with MD C+D were classified correspondently in PMBD (p < 0.001). Binary logistic regression showed age (OR 1.06, 1.01-1.12 95% CI, p 0.013) and nulliparity (OR 0.39, 0.17-0.96 95% CI, p 0.039) as predictors of A+B PMBD.Conclusion: Mammographic and pathologic macroscopic breast density showed no association in our study for breast C or D in breast image. The fatty breast was associated with older patients and the nulliparity decreases the chance of fatty breasts nearby 60%.
- Effects of preoperative magnetic resonance image on survival rates and surgical planning in breast cancer conservative surgery: randomized controlled trial (BREAST-MRI trial)(2023) MOTA, Bruna Salani; REIS, Yedda Nunes; BARROS, Nestor de; CARDOSO, Natalia Pereira; MOTA, Rosa Maria Salani; SHIMIZU, Carlos; TUCUNDUVA, Tatiana Cardoso de Mello; FERREIRA, Vera Christina Camargo de Siqueira; GONCALVES, Rodrigo; DORIA, Maira Teixeira; RICCI, Marcos Desiderio; TRINCONI, Angela Francisca; CAMARGO, Cristina Pires; RIERA, Rachel; BARACAT, Edmund Chada; JR, Jose Maria Soares; FILASSI, Jose RobertoBackgroundBreast magnetic resonance imaging (MRI) has high sensitivity in detecting invasive neoplasms. Controversy remains about its impact on the preoperative staging of breast cancer surgery. This study evaluated survival and surgical outcomes of preoperative MRI in conservative breast cancer surgery.MethodsA phase III, randomized, open-label, single-center trial including female breast cancer participants, stage 0-III disease, and eligible for breast-conserving surgery. We compared the role of including MRI in preoperative evaluation versus radiologic exam routine with mammography and ultrasound in breast cancer conservative candidates. The primary outcome was local relapse-free survival (LRFS), and secondary outcomes were overall survival (OS), mastectomy rate, and reoperation rate.Results524 were randomized to preoperative MRI group (n = 257) or control group (n = 267). The survival analysis showed a 5.9-years LRFS of 99.2% in MRI group versus 98.9% in control group (HR = 0.72; 95% CI 0.12-4.28; p = 0.7) and an OS of 95.3% in the MRI group versus 96.3% in the control group (HR = 1.37 95% CI 0.59-3.19; p = 0.8). Surgical management changed in 21 ipsilateral breasts in the MRI group; 21 (8.3%) had mastectomies versus one in the control group. No difference was found in reoperation rates, 22 (8.7%) in the MRI group versus 23 (8.7%) in the control group (RR = 1.002; 95% CI 0.57-1.75; p = 0.85).ConclusionPreoperative MRI increased the mastectomy rates by 8%. The use of preoperative MRI did not influence local relapse-free survival, overall survival, or reoperation rates.
- MRI as a complementary tool for the assessment of suspicious mammographic calcifications: Does it have a role?(2021) NINNO, Andrea Alves Maciel Di; MELLO, Giselle Guedes Netto de; TORRES, Ulysses S.; SHIMIZU, Carlos; TUCUNDUVA, Tatiana Cardoso de Mello; REIS, Fatima Regina Silva; ANANIAS, Mariana Pinheiro Ferri; LEDERMAN, Henrique ManoelIntroduction: Mammography remains the standard imaging modality for the identification and characterization of breast calcifications. However, its low specificity results in high biopsy rates in cases of suspicious calcifications. Objectives: To evaluate the diagnostic performance of MRI as an additional tool in the assessment of suspicious mammographic calcifications and to identify the enhancement patterns most related to malignancy. Methods: An observational, prospective, cross-sectional, bi-centre study was conducted including consecutive patients with suspicious calcification groups on mammography (BI-RADS? 4 and 5). Anatomopathological results obtained from biopsies were considered the reference standard, and the patients were followed up for at least two years. MRI examinations were interpreted by two radiologists in consensus. The chi-square test was used to evaluate the correlation between MRI features and histological results. The overall diagnostic performance of MRI for malignancy was calculated. Results: 162 female patients were included (mean age, 53 years; range 34?82 years), with 163 mammographic lesions, of which 77 (47.2%) were benign, 64 (39.3%) malignant, and 22 (13.5%) precursor lesions on histopathology. Malignant lesions demonstrated a significantly higher presence of enhancement (56/64; 87.5%) than benign lesions (17/77; 22.1%) (p < 0.001). Non-mass enhancement (NME) was the morphology most related to malignant lesions (38/56; 67.9%). The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of MRI for malignancy were 81.5%, 87.5%, 77.8%, 71.8%, and 90.5%, respectively. Conclusion: MRI performed as an adjunct tool allows to increase imaging specificity for malignancy in suspicious calcifications, which may contribute to reduce the need for biopsy.
- Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network(2022) PETRINI, Daniel G. P.; SHIMIZU, Carlos; ROELA, Rosimeire A.; VALENTE, Gabriel Vansuita; FOLGUEIRA, Maria Aparecida Azevedo Koike; KIM, Hae YongSome recent studies have described deep convolutional neural networks to diagnose breast cancer in mammograms with similar or even superior performance to that of human experts. One of the best techniques does two transfer learnings: the first uses a model trained on natural images to create a ""patch classifier"" that categorizes small subimages; the second uses the patch classifier to scan the whole mammogram and create the ""single-view whole-image classifier"". We propose to make a third transfer learning to obtain a ""two-view classifier"" to use the two mammographic views: bilateral craniocaudal and mediolateral oblique. We use EfficientNet as the basis of our model. We ""end-to-end"" train the entire system using CBIS-DDSM dataset. To ensure statistical robustness, we test our system twice using: (a) 5-fold cross validation; and (b) the original training/test division of the dataset. Our technique reached an AUC of 0.9344 using 5-fold cross validation (accuracy, sensitivity and specificity are 85.13% at the equal error rate point of ROC). Using the original dataset division, our technique achieved an AUC of 0.8483, as far as we know the highest reported AUC for this problem, although the subtle differences in the testing conditions of each work do not allow for an accurate comparison. The inference code and model are available at https://github.com/dpetrini/two-views-classifier