Breast Implant Associated Anaplastic Large Cell Lymphoma (ALCL): Current Recommendations on Diagnosis and Treatment Strategies

Ibrahim, Amir; Atiyeh, Bishara S.; Sarhane, Karim A.; Clemens, Mark W.

doi:10.1007/978-3-319-18726-6_147

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…In addition, state-of-the-art machine learning models have been used, although recently, innovative approaches have been proposed, which see the use of deep learning techniques also on structured data, such as clinical data [ 30 , 31 ]. Other interesting information could be to evaluate the results in patients with genetic mutations with prosthetic reconstruction and in patients diagnosed with periprosthetic large T-cell lymphoma (Bi-ALCL), where prosthetic contracture is included in the differential diagnosis [ 32 , 33 ].…”

Section: Discussionmentioning

confidence: 99%

A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer Patients

et al. 2023

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In recent years, immediate breast reconstruction after mastectomy surgery has steadily increased in the treatment pathway of breast cancer (BC) patients due to its potential impact on both the morpho-functional and aesthetic type of the breast and the quality of life. Although recent studies have demonstrated how recent radiotherapy techniques have allowed a reduction of adverse events related to breast reconstruction, capsular contracture (CC) remains the main complication after post-mastectomy radio-therapy (PMRT). In this study, we evaluated the association of the occurrence of CC with some clinical, histological and therapeutic parameters related to BC patients. We firstly performed bivariate statistical tests and we then evaluated the prognostic predictive power of the collected data by using machine learning techniques. Out of a sample of 59 patients referred to our institute, 28 patients (i.e., 47%) showed contracture after PMRT. As a result, only estrogen receptor status (ER) and molecular subtypes were significantly associated with the occurrence of CC after PMRT. Different machine learning models were trained on a subset of clinical features selected by a feature importance approach. Experimental results have shown that collected features have a non-negligible predictive power. The extreme gradient boosting classifier achieved an area under the curve (AUC) value of 68% and accuracy, sensitivity, and specificity values of 68%, 64%, and 74%, respectively. Such a support tool, after further suitable optimization and validation, would allow clinicians to identify the best therapeutic strategy and reconstructive timing.

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Section: Discussionmentioning

confidence: 99%

A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer Patients

et al. 2023

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“…Breast Implant-associated Anaplastic Large Cell Lymphoma (BIA-ALCL) is one of the most discussed topics in specialized literature dedicated to the use of breast implants, raising the interest of the international scientific community dedicated to understanding the impact of elective breast augmentation and alloplastic reconstruction after mastectomy on the quality of life and the life expectancy of the patients. ALCL occupies the third position in the incidence of peripheral T-cell lymphoma, BIA-ALCL being introduced by the World Health Organization in 2016 in the classification of these diseases together with ALK (-) and ALK (+) systemic lymphoma, as well as the related form of skin cancer [1,2]. The immunohistochemical defining elements of this subtype of cancer are CD30 positivity, as well as the ALK (-) character [3], criteria that are part of the BIA-ALCL diagnostic protocol.…”

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confidence: 99%

Research Related to Breast Implant-associated Anaplastic Large Cell Lymphoma and its Influence on the Decision-Making Process Related to Reconstructive Techniques Analysis of a series of cases and literature review

Marinescu¹,

Bejinariu²,

Giuglea³

2019

Mat.Plast.

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The worldwide increasing number of reports related to new cases of Breast Implant-associated Anaplastic Large Cell Lymphoma (BIA-ALCL) raises the interest of the scientific community in understanding the pathophysiology and the prognosis of these patients. This material presents the impact that BIA-ALCL exerts on the reconstructive options for patients who have undergone mastectomy. The research is based on data obtained from the analysis of a group of patients who have undergone 71 surgeries performed within the National Breast Reconstruction Program between 2015 and 2019. The statistical analysis revealed that 35.14% of the patients that were examined during the breast reconstruction consult refused the use of alloplastic techniques by invoking the potential associated risks described in the insufficient documentation of BIA-ALCL pathophysiology. Improving BIA-ALCL detection and reporting systems has led to an accelerated increase in the number of new diagnosed cases, determining the patients� reticence towards the use of alloplastic reconstructive techniques.

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Breast Implant Associated Anaplastic Large Cell Lymphoma (ALCL): Current Recommendations on Diagnosis and Treatment Strategies

Cited by 2 publications

References 11 publications

A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer Patients

A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer Patients

Research Related to Breast Implant-associated Anaplastic Large Cell Lymphoma and its Influence on the Decision-Making Process Related to Reconstructive Techniques Analysis of a series of cases and literature review

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