Abstract PO-014: Deep learning-based segmentation accurately captures histological features in cancer-free lymph nodes of breast cancer patients

2021 ◽  
Author(s):  
Gregory Verghese ◽  
Anita Grigoriadis ◽  
Amit Sethi ◽  
Amit Lohan ◽  
Nikhil Cherian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Histological Features

scholarly journals Lesion-Based Bone Metastasis Detection in Chest Bone Scintigraphy Images of Prostate Cancer Patients Using Pre-Train, Negative Mining, and Deep Learning

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 518
Author(s):  
Da-Chuan Cheng ◽  
Te-Chun Hsieh ◽  
Kuo-Yang Yen ◽  
Chia-Hung Kao
Keyword(s):  
Breast Cancer ◽  
Prostate Cancer ◽  
Deep Learning ◽  
Bone Metastasis ◽  
Cancer Patients ◽  
Bone Scintigraphy ◽  
Breast Cancer Patients ◽  
Location Detection ◽  
The Mean ◽  
Mean Sensitivity

This study aimed to explore efficient ways to diagnose bone metastasis early using bone scintigraphy images through negative mining, pre-training, the convolutional neural network, and deep learning. We studied 205 prostate cancer patients and 371 breast cancer patients and used bone scintigraphy data from breast cancer patients to pre-train a YOLO v4 with a false-positive reduction strategy. With the pre-trained model, transferred learning was applied to prostate cancer patients to build a model to detect and identify metastasis locations using bone scintigraphy. Ten-fold cross validation was conducted. The mean sensitivity and precision rates for bone metastasis location detection and classification (lesion-based) in the chests of prostate patients were 0.72 ± 0.04 and 0.90 ± 0.04, respectively. The mean sensitivity and specificity rates for bone metastasis classification (patient-based) in the chests of prostate patients were 0.94 ± 0.09 and 0.92 ± 0.09, respectively. The developed system has the potential to provide pre-diagnostic reports to aid in physicians’ final decisions.

scholarly journals Morbidity after conventional dissection of axillary lymph nodes in breast cancer patients

2014 ◽  
Vol 12 (1) ◽  
Author(s):  
Emerson Wander Silva Soares ◽  
Hildebrando Massahiro Nagai ◽  
Luis César Bredt ◽  
Ademar Dantas da Cunha ◽  
Reginaldo José Andrade ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Breast Cancer Patients

Additional axillary metastases and stage migration in breast cancer patients with micrometastases or submicrometastases in sentinel lymph nodes

Cancer ◽  
2006 ◽  
Vol 107 (3) ◽  
pp. 467-471 ◽  
Author(s):  
Maartje C. van Rijk ◽  
Johannes L. Peterse ◽  
Omgo E. Nieweg ◽  
Hester S. A. Oldenburg ◽  
Emiel J. Th. Rutgers ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Sentinel Lymph Nodes ◽  
Stage Migration ◽  
Breast Cancer Patients ◽  
Axillary Metastases

Does BMI affect the detection of sentinel lymph nodes with indocyanine green in early breast cancer patients?

2017 ◽  
Vol 49 (4) ◽  
pp. 165-170 ◽  
Author(s):  
Stephanie Rauch ◽  
Anton Haid ◽  
Zerina Jasarevic ◽  
Christoph H. Saely ◽  
Alexander Becherer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Indocyanine Green ◽  
Cancer Patients ◽  
Early Breast Cancer ◽  
Sentinel Lymph Nodes ◽  
Breast Cancer Patients

Postmastectomy Radiotherapy in T1–2 Female Breast Cancer Patients with 1–3 Positive Axillary Lymph Nodes: A Propensity Score Matched SEER Analysis

2021 ◽  
Author(s):  
Gang Xu ◽  
Shanshan Bu ◽  
Xiushen Wang ◽  
Hong Ge
Keyword(s):  
Breast Cancer ◽  
Propensity Score ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Female Breast Cancer ◽  
Axillary Lymph ◽  
Breast Cancer Patients ◽  
Postmastectomy Radiotherapy ◽  
Female Breast ◽  
Positive Lymph Nodes

Abstract Purpose The application of postmastectomy radiotherapy (PMRT) in T1–2 female breast cancer patients with 1–3 positive lymph nodes has been controversial. We sought to determine the survival benefits of PMRT in the patients with T1–2 and 1–3 positive nodes. Methods A retrospective study using the Surveillance, Epidemiology, and End Results (SEER) Regs Custom Data (with additional treatment fields) from 2001 to 2011 was performed. Patients who received PMRT were matched by the propensity score with patients who did not receive PMRT. The Overall survival (OS) and breast cancer-specific survival (BCSS) were analyzed. Results We identified 56,725 female breast cancer patients with T1–2 and 1–3 positive nodes, and 18,646 patients were included in the analysis. After propensity score matching (1:1), with a median follow-up of 116 months, PMRT showed an increase in the OS (P = 0.018) but had no effect on the BCSS. The 10-year OS rates were 76.8% and 74.4%, and the 10-year BCSS rates were 82.8% and 82.2% for the patients who received and who did not receive PMRT, respectively. Only patients with 3 positive nodes could gain the benefit of PMRT for BCSS. Conclusion PMRT for patients with T1–2 and 1–3 positive lymph nodes could increase the 10-year OS, and had no effect on the 10-year BCSS. Subgroup analysis indicated that only patients with 3 positive lymph nodes could benefit from PMRT for both the OS and BCSS.

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