Evaluating the ability of an artificial-intelligence cloud-based platform designed to provide information prior to locoregional therapy for breast cancer in improving patient’s satisfaction with therapy: The CINDERELLA trial

Kaidar‐Person, Orit; Antunes, Marília; Cardoso, Jaime S.; Ciani, Oriana; Cruz, Hany Kelly Araujo; Micco, Rosa Di; Gentilini, Oreste; Gonçalves, Tiago; Gouveia, Pedro; Heil, Joerg; Kabata, Paweł; Lopes, Daniela; Martinho, Marta; Martins, Henrique; Mavioso, Carlos; Mika, Martin; Montenegro, Helena; Oliveira, Hélder P.; Pfob, André; Rotmensz, Nicole; Schinköthe, Timo; Silva, Giovani L.; Tarricone, R.; Cardoso, M.J.

doi:10.1371/journal.pone.0289365

Cited by 9 publications

(1 citation statement)

References 22 publications

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“…A randomized control trial aimed at evaluating the ability of an AI model to educate women about the expected aesthetic outcomes following locoregional breast cancer surgery is currently being carried out. The model is expected to improve women’s satisfaction with breast surgery, raise their psychological status, and reduce the need for subsequent plastic surgeries ( 146 ). A ML model was also applied in predicting the financial burden of breast cancer surgery.…”

Section: Resultsmentioning

confidence: 99%

Use of artificial intelligence in breast surgery: a narrative review

Seth,

Lim,

Joseph

et al. 2024

Gland Surg

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Background and Objective We have witnessed tremendous advances in artificial intelligence (AI) technologies. Breast surgery, a subspecialty of general surgery, has notably benefited from AI technologies. This review aims to evaluate how AI has been integrated into breast surgery practices, to assess its effectiveness in improving surgical outcomes and operational efficiency, and to identify potential areas for future research and application. Methods Two authors independently conducted a comprehensive search of PubMed, Google Scholar, EMBASE, and Cochrane CENTRAL databases from January 1, 1950, to September 4, 2023, employing keywords pertinent to AI in conjunction with breast surgery or cancer. The search focused on English language publications, where relevance was determined through meticulous screening of titles, abstracts, and full-texts, followed by an additional review of references within these articles. The review covered a range of studies illustrating the applications of AI in breast surgery encompassing lesion diagnosis to postoperative follow-up. Publications focusing specifically on breast reconstruction were excluded. Key Content and Findings AI models have preoperative, intraoperative, and postoperative applications in the field of breast surgery. Using breast imaging scans and patient data, AI models have been designed to predict the risk of breast cancer and determine the need for breast cancer surgery. In addition, using breast imaging scans and histopathological slides, models were used for detecting, classifying, segmenting, grading, and staging breast tumors. Preoperative applications included patient education and the display of expected aesthetic outcomes. Models were also designed to provide intraoperative assistance for precise tumor resection and margin status assessment. As well, AI was used to predict postoperative complications, survival, and cancer recurrence. Conclusions Extra research is required to move AI models from the experimental stage to actual implementation in healthcare. With the rapid evolution of AI, further applications are expected in the coming years including direct performance of breast surgery. Breast surgeons should be updated with the advances in AI applications in breast surgery to provide the best care for their patients.

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Section: Resultsmentioning

confidence: 99%

Use of artificial intelligence in breast surgery: a narrative review

Seth,

Lim,

Joseph

et al. 2024

Gland Surg

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A look into the neighboring discipline: eHealth in oncology

Overkamp

2024

Chirurgie

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Artificial-Intelligence Cloud-Based Platform to Support Shared Decision-Making in the Locoregional Treatment of Breast Cancer: Protocol for a Multidimensional Evaluation Embedded in the CINDERELLA Clinical Trial

Borsoi,

Listorti,

Ciani

2024

PharmacoEconomics Open

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Background Shared decision-making (SDM) plays a crucial role in breast cancer care by empowering patients and reducing decision regret. Patient decision aids (PtDAs) are valuable tools for facilitating SDM, now available in digital and artificial intelligence (AI)-powered formats to offer increasingly personalized contents. The ongoing CINDERELLA clinical trial (ClinicalTrials.gov: NCT05196269) evaluates an innovative AI cloud-based approach using a web platform and a mobile application (CINDERELLA APProach) versus the conventional approach to support SDM in breast cancer patients undergoing locoregional treatment. This protocol outlines a trial-based multidimensional evaluation, encompassing economic, financial, implementability, and environmental considerations associated with the CINDERELLA APProach. Methods A within-trial cost-consequence and cost-utility analysis from a societal perspective will be performed using patient-level data on outcomes and resource use. The latter will be valued in monetary terms using country-specific unit costs or patient valuations. A budget impact analysis will be performed over 1 and 5 years from the budget holder perspectives. The CINDERELLA APProach implementability will be assessed through an evaluation of its usability, acceptability, organizational impact, and overall feasibility. The environmental impact will be quantitatively assessed across several dimensions, such as quantity, appropriateness, and emissions, supplemented by qualitative insights. Overall, data for the evaluation will be gathered from patient questionnaires, interviews with patients and managers, focus groups with healthcare professionals, and app electronic data. Discussion A thorough understanding of the broad consequences of the CINDERELLA APProach may foster its successful translation into real-world settings, hopefully benefiting breast cancer patients and clinical practice. Supplementary Information The online version contains supplementary material available at 10.1007/s41669-024-00519-1.

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Evaluating the ability of an artificial-intelligence cloud-based platform designed to provide information prior to locoregional therapy for breast cancer in improving patient’s satisfaction with therapy: The CINDERELLA trial

Cited by 9 publications

References 22 publications

Use of artificial intelligence in breast surgery: a narrative review

Use of artificial intelligence in breast surgery: a narrative review

A look into the neighboring discipline: eHealth in oncology

Artificial-Intelligence Cloud-Based Platform to Support Shared Decision-Making in the Locoregional Treatment of Breast Cancer: Protocol for a Multidimensional Evaluation Embedded in the CINDERELLA Clinical Trial

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