Online

ESTRO 2020

Session Item

Saturday
November 28
10:30 - 11:30
Online
Proffered papers 7: Evaluating and predicting toxicity in RT
1208
Proffered Papers
RTT
10:40 - 10:50
Cardiovascular risk assessment based on cardiac calcifications on breast RT planning CT scans
Helena Verkooijen, The Netherlands
OC-0109

Abstract

Cardiovascular risk assessment based on cardiac calcifications on breast RT planning CT scans
Authors: Erwin L.A. Blezer (University Medical Center Utrecht- University of Utrecht, Division of Imaging and Oncology, Utrecht, The Netherlands), Marleen J. Emaus (University Medical Center Utrecht- University of Utrecht, Division of Imaging and Oncology, Utrecht, The Netherlands), Roxanne GAL (University Medical Center Utrecht- University of Utrecht, Division of Imaging and Oncology, Utrecht, The Netherlands), Sofie A.M. Gernaat (Karolinska Institutet, Department of Oncology-Pathology, Stockholm, Sweden), Madelijn L. Gregorowitsch (University Medical Center Utrecht- University of Utrecht, Division of Imaging and Oncology, Utrecht, The Netherlands), Ivana Išgum (Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands), Ivana Išgum (Amsterdam University Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands), Ivana Išgum (University Medical Center Utrecht- University of Utrecht, Image Sciences Institute, Utrecht, The Netherlands), Nikolas Lessmann (University Medical Center Utrecht- University of Utrecht, Image Sciences Institute, Utrecht, The Netherlands), Hanneke Meijer (Radboudumc, Department of Radiation Oncology, Nijmegen, The Netherlands), Joan Penninkhof (Erasmus MC Cancer Institute, Department of Radiation Oncology, Rotterdam, The Netherlands), Jean-Philippe Pignol (Dalhousie University, Department of Radiation Oncology, Halifax- Nova Scotia, Canada), Margriet G.A. Sattler (Erasmus MC Cancer Institute, Department of Radiation Oncology, Rotterdam, The Netherlands), Arco J. Teske (University Medical Center Utrecht- University of Utrecht, Department of Cardiology, Utrecht, The Netherlands), Desirée H.J.G. van den Bongaard (Amsterdam University Medical Center, Department of Radiation Oncology, Amsterdam, The Netherlands), Julia J. van Tol-Geerdink (Radboudumc, Department of Radiation Oncology, Nijmegen, The Netherlands), Sanne G.M. van Velzen (Amsterdam University Medical Center, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands), Sanne G.M. van Velzen (University Medical Center Utrecht- University of Utrecht, Image Sciences Institute, Utrecht, The Netherlands), Helena M. Verkooijen (University Medical Center Utrecht- University of Utrecht, Division of Imaging and Oncology, Utrecht, The Netherlands), Janneke Verloop (Netherlands Comprehensive Cancer Organisation, Department of Research, Utrecht, The Netherlands)
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Purpose or Objective

With improved breast cancer survival, the prevention of treatment-induced toxicity is becoming increasingly important. Adjuvant treatments including anthracyclines, targeted and radiotherapy are associated with an increased risk of cardiovascular disease (CVD). Breast cancer patients with pre-existing CVD risk factors have the highest risk of treatment induced cardiotoxicity. Coronary artery calcium (CAC) is a strong independent CVD risk factor and can be quantified on dedicated cardiac computed tomography (CT) scans. Before adjuvant treatment with radiotherapy, a CT scan of the chest is performed for radiotherapy treatment planning. These CT scans allow routinely assessing CAC scores in breast cancer patients, and thereby detecting patients at increased CVD risk. In the Bragatston study, we evaluate the association between automatically measured CAC on radiotherapy planning CT scans and the risk of CVD events in breast cancer patients.

Material and Methods

In this multicenter historical cohort study, breast cancer patients receiving radiotherapy between 2005-16 were included. CAC scores were automatically extracted from the planning CT scan using an in house developed deep learning algorithm and categorized following the five-level scale Agatston classification (0, 1-10, 11-100, 101-399, >400 units). Tumor and treatment characteristics were obtained from the Netherlands Cancer Registry, the Netherlands Comprehensive Cancer Organisation. Data on occurrence of CVD were obtained from Dutch Hospital Data (DHD) and the National Cause of Death Register, Statistics Netherlands. Cox proportional hazard regression models were used to evaluate the association between CAC scores and CVD events, adjusted for age and calendar year at planning CT.

Results

Data from 14,034 patients were included. The mean age at the planning CT was 58 years (SD=11). Twenty-eight percent of the patients had a CAC score of >0 (Table 1). Over a median follow-up time of 52 months (IQR: 27-82), 8.2% of the patients (n=1148) were admitted to the hospital for CVD events and 93 patients (0.7%) died from this disease. After adjustment for age and calendar year at planning CT, the incidence of CVD events increased with higher CAC scores (CAC 1-10 HR=1.3, 95%CI:1.0-1.5; CAC 11-100 HR=1.7, 95%CI:1.5-2.1; CAC 101-400 HR=2.2, 95%CI:1.7-2.7; CAC >400 HR=3.7, 95%CI:2.9-4.6).

Conclusion

CAC detected on the radiotherapy planning CT is strongly associated with an increased risk of CVD events. This finding is relevant for breast cancer patients since early identification of high risk patients enables switching to less cardiotoxic breast cancer treatment (e.g. adaptation of radiotherapy target volumes or technique, chemotherapy dose reduction). Also, patients can adopt targeted cardio-preventive interventions (e.g. lifestyle changes, pharmaco-prevention, close monitoring for early detection of cardiotoxicity). Hence, the burden of CVD in breast cancer survivors can be reduced and better overall survival rates can be achieved.