Ductal carcinoma in situ of the breasts: Over‐diagnosis, over‐treatment and a decade of lost direction

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology

Digital twins employ mathematical and computational models to virtually represent a physical object (e.g., planes and human organs), predict the behavior of the object, and enable decision-making to optimize the future behavior of the object. While digital twins have been widely used in engineering for decades, their applications to oncology are only just emerging. Due to advances in experimental techniques quantitatively characterizing cancer, as well as advances in the mathematical and computational sciences, the notion of building and applying digital twins to understand tumor dynamics and personalize the care of cancer patients has been increasingly appreciated. In this review, we present the opportunities and challenges of applying digital twins in clinical oncology, with a particular focus on integrating medical imaging with mechanism-based, tissue-scale mathematical modeling. Specifically, we first introduce the general digital twin framework and then illustrate existing applications of image-guided digital twins in healthcare. Next, we detail both the imaging and modeling techniques that provide practical opportunities to build patient-specific digital twins for oncology. We then describe the current challenges and limitations in developing image-guided, mechanism-based digital twins for oncology along with potential solutions. We conclude by outlining five fundamental questions that can serve as a roadmap when designing and building a practical digital twin for oncology and attempt to provide answers for a specific application to brain cancer. We hope that this contribution provides motivation for the imaging science, oncology, and computational communities to develop practical digital twin technologies to improve the care of patients battling cancer.

Non-surgical treatment for ductal carcinoma in situ of the breasts - a prospective study on patient's perspective

INTRODUCTION

Several ongoing trials are currently investigating the feasibility and non-inferiority of active surveillance for managing low-risk DCIS. However, little is known on the proposed non-surgical treatment for DCIS from patient's perspective.

METHODS

A prospective cohort study was performed on 1000 consecutive patients aged 18 to 90 years old with various breast disorders between 1st July 2019 and 31st December 2019. Patients were asked about their opinions on non-surgical treatments for DCIS after thorough explanation of the clinical scenario.

RESULTS

Median age was 55 years old (Range 18 - 87). 692 patients had past history of breast cancer, 279 patients had benign breast conditions, 29 patients had borderline breast lesions. 891 (89.1%) patients opted for standard surgical excision for low-risk DCIS, most of them (N = 757, 85.0%) decided for operative management for DCIS to avoid life-time anxiety of disease progression. Patients of older age and with history of malignant breast conditions are more likely to choose surgical treatment for DCIS (p<0.0001). Of note, 112 (11.2%) patients in the cohort had history of DCIS with excision done, 111 (99.1%) patients would still decide for surgical excision as the treatment of DCIS, only 1 patient expressed the wish for conservative treatment for DCIS.

CONCLUSION

Majority of patients decided for surgical treatment for DCIS despite being offered the condition that conservative treatment could be oncologically safe. Patient anxiety and cost of extensive breast surveillance are two important factors.