Extensive Intraductal Component in Breast Cancer: What Role in Disease-Free Survival?

Corsi, Fabio; Albasini, Sara; Ciciriello, Simone; Villani, Laura; Truffi, Marta; Sevieri, Marta; Sorrentino, Luca

doi:10.1016/j.jss.2022.10.094

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…Наличие или отсутствие внутрипротокового поражения (EIC -extensive intraductal сomponent) и характеристика краев линии резекции являются одними из факторов, играющих важную прогностическую роль в отношении развития регионарного рецидивирования РМЖ [26,27]. I. Gage et al, в исследовании JCRT, проводились органосохраняющая операция и послеоперационная ЛТ.…”

Section: Reviewsunclassified

Combined modality treatment of early breast cancer. Literature review

Akhmetzyanov,

Akhmetzyanova,

Ankhimova

et al. 2024

Sib. onkol. ž.

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The object of the study was to conduct a systematic literature review on combined modality treatment for early-stage breast cancer using postoperative and intraoperative radiation therapy, and consider new treatment approaches for early breast cancer.Material and Methods. The search for sources relevant to the review topic was carried out in the Medline, Cochrane Library, and Elibrary systems. A total of 905 studies on combination treatments for early breast cancer were identified, of which 43 were included in the review.Results. Data analysis showed that the rate of local relapses in early breast cancer was lower in patients who underwent breast-conserving surgery in combination with adjuvant radiation therapy than in patients without adjuvant radiation therapy. Research is ongoing on radiotherapy deintensification using intraoperative radiation therapy for patients at low risk of recurrence. Ongoing clinical trials support the omission of radiotherapy after breast-conserving surgery for elderly women with hormone receptor-positive early-stage breast cancer, who receive adjuvant endocrine therapy. Understanding the characteristics of the tumor process will allow us to personalize the treatment of patients with early breast cancer, reduce the risk of local relapses, and avoid unnecessary treatment-related complications.Conclusion. To improve survival in breast cancer patients is only possible by maximizing the tumor control. The effectiveness of adjuvant radiation therapy, which is an integral component in the combined modality treatment of early breast cancer, has been proven. However, third-generation studies discuss the feasibility of identifying a low-risk group of patients with a favorable clinical prognosis, who receive adequate endocrine therapy, and additional radiation do not provide a significant survival benefit.

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Section: Reviewsunclassified

Combined modality treatment of early breast cancer. Literature review

Akhmetzyanov,

Akhmetzyanova,

Ankhimova

et al. 2024

Sib. onkol. ž.

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“…The rapid growth of digital pathology has opened up possibilities for AI to aid pathologists in diagnosis. Tumor area estimation techniques can assist pathologists by providing more accurate measurements of invasive tumors [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

MurSS: A Multi-Resolution Selective Segmentation Model for Breast Cancer

Lee,

Kwak

et al. 2024

Bioengineering

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Accurately segmenting cancer lesions is essential for effective personalized treatment and enhanced patient outcomes. We propose a multi-resolution selective segmentation (MurSS) model to accurately segment breast cancer lesions from hematoxylin and eosin (H&E) stained whole-slide images (WSIs). We used The Cancer Genome Atlas breast invasive carcinoma (BRCA) public dataset for training and validation. We used the Korea University Medical Center, Guro Hospital, BRCA dataset for the final test evaluation. MurSS utilizes both low- and high-resolution patches to leverage multi-resolution features using adaptive instance normalization. This enhances segmentation performance while employing a selective segmentation method to automatically reject ambiguous tissue regions, ensuring stable training. MurSS rejects 5% of WSI regions and achieves a pixel-level accuracy of 96.88% (95% confidence interval (CI): 95.97–97.62%) and mean Intersection over Union of 0.7283 (95% CI: 0.6865–0.7640). In our study, MurSS exhibits superior performance over other deep learning models, showcasing its ability to reject ambiguous areas identified by expert annotations while using multi-resolution inputs.

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“…Therefore, predicting breast cancer prognosis is an essential area of study. In general, Extensive Intraductal Components (EICs) are an important factor in predicting the prognosis of breast cancer [1] [2]. To calculate the EIC, the area of Ductal Carcinoma In Situ (DCIS) and Invasive Ductal Carcinoma (IDC) regions is required [3].…”

Section: Introductionmentioning

confidence: 99%

MurSS: Multi-resolution Selective Segmentation Model for Breast Cancer

Lee,

Kwak

et al. 2023

Preprint

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We propose the Multi-resolution Selective Segmentation model (MurSS) for segmenting benign, Ductal Carcinoma In Situ, and Invasive Ductal Carcinoma in breast resection Hematoxylin and Eosin stained Whole Slide Images. MurSS simultaneously trains on context information from a wide area at low resolution and content information from a local area at high resolution, aiming for a more accurate diagnosis. Additionally, through the selection stage, it provides solutions for ambiguous tissue regions. Our proposed MurSS achieves a mean Intersection of Union performance of 91.1%, which is at least 16.8% and at most 19.0% higher than well-known image segmentation models.

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Extensive Intraductal Component in Breast Cancer: What Role in Disease-Free Survival?

Cited by 4 publications

References 28 publications

Combined modality treatment of early breast cancer. Literature review

Combined modality treatment of early breast cancer. Literature review

MurSS: A Multi-Resolution Selective Segmentation Model for Breast Cancer

MurSS: Multi-resolution Selective Segmentation Model for Breast Cancer

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