Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Saturday
May 07
10:30 - 11:30
Poster Station 1
03: Functional imaging & modelling
Eliana Maria Vasquez Osorio, United Kingdom
1300
Poster Discussion
Physics
Feasibility of Image-Based Data Mining in Breast Radiotherapy
Tanwiwat Jaikuna, United Kingdom
PD-0163

Abstract

Feasibility of Image-Based Data Mining in Breast Radiotherapy
Authors:

Tanwiwat Jaikuna1, Marianne Aznar1, Peter Hoskin1, Marcel Van Herk1, Catharine M L West1, Azria David2, Sara Gutiérrez-Enríquez3, Tiziana Rancati4, Barry S Rosenstein5, Dirk de Ruysscher6,7, Elena Sperk8, Paul Symonds9, Christopher J Talbot9, Maria Carmen De Santis10, Ana Vega11, Adam Webb12, Jenny Chang-Claude13, Petra Seibold14, Zoe Lingard1, Eliana Vasquez Osorio1

1The University of Manchester, Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Christie NHS Foundation Trust Hospital, Manchester, United Kingdom; 2Université Montpellier, Department of Radiation Oncology, Montpellier Cancer Institute, Inserm, France; 3Vall d'Hebron Institute of Oncology, Hereditary Cancer Genetics Group, Barcelona, Spain; 4Fondazione IRCCS Istituto Nazionale dei Tumori, Prostate Cancer Program, Milan, Italy; 5Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Department of Genetics and Genomic Sciences, New York, USA; 6Maastricht University Medical Center, Department of Radiation Oncology (Maastro Clinic), GROW School for Oncology and Developmental Biology, Maastricht, The Netherlands; 7KU Leuven, Radiation Oncology, Leuven, Belgium; 8University of Heidelberg, Department of Radiation Oncology, Universitätsklinikum Mannheim, Medical Faculty Mannheim, Mannheim, Germany; 9University of Leicester, Leicester Cancer Research Centre, Leicester, United Kingdom; 10Fondazione IRCCS Isituto Nazionale dei Tumori, Radiation Oncology 1, Milan, Italy; 11Instituto de Investigación Sanitaria de Santiago de Compostela, Fundación Pública Galega de Medicina Xenómica, Grupo de Medicina Xenómica (USC), Biomedical Network on Rare Diseases (CIBERER), Santiago de Compostela, Spain; 12University of Leicester, Department of Genetics and Genome Biology, Leicester, United Kingdom; 13University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; 14German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany

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Purpose or Objective

Breast pain following cancer treatment reduces the patient’s quality of life. Although the correlation between pain and radiation hotspot has been established in  previous studies, the impact of the location of the hotspot has not been identified. Voxel-wise image-based data mining (IBDM) can identify specific dose patterns correlated with radiotherapy toxicity and identify sensitive sub-regions. However, IBDM has not been applied to breast radiotherapy as a consequence of variations in volumes (breast size) and set-up positions in this patient population. We aimed to demonstrate the feasibility of applying IBDM to breast cancer patients treated with supine post-lumpectomy radiotherapy in a large multi-centre study.

Material and Methods

IBDM was applied to 177 patients from 8 centres in the REQUITE study (www.requite.eu). All patients were treated supine with different arm positions; both arms up (n=118), left arm up (n=32), or right arm up (n=27). Planning dose distributions were normalised to a single reference patient using NiftyReg deformable image registration (DIR). The region of interest was the breast +/-5 cm in the superior-inferior direction. DIR performance was assessed using the normalised correlation coefficient (NCC). The dose in each voxel was converted into EQD2 using α/β=1.7 for moderate or marked normal tissue toxicity in the breast or chest wall. For this feasibility study, the outcome of interest was patient-reported pain at 1-year post-radiotherapy (any pain vs no pain). The region associated with pain was identified using voxel-wise t-test and permutation testing (n=1000). The correlation between breast pain and mean and max EQD2 in the identified region, as well as other clinical variables were investigated using univariable and multivariable logistic regression analysis (SPSS v.25).

Results

Patient characteristics are summarised in Table 1. DIR accuracy on the breast was acceptable (NCC=0.92 (IQR 0.14), where 1 is the ideal value), but was considerably affected by the difference in arm positions (Mann-Whitney test between both arms up and ipsilateral arm up only, p=0.05). IBDM identified a sensitive region which correlated with breast pain in the upper part of the treated breast (Figure 1.A-B). The mean and max EQD2 within the identified region, fractionation, and breast cup size were significant in univariable analysis (Figure 1.C). However, only fractionation and breast cup size remained significant on multivariable analysis.

Conclusion

IBDM is feasible in breast radiotherapy and the accuracy of DIR was found acceptable. Nevertheless, larger cohorts of patients are needed to clarify the existence of a sensitive sub-region related to breast pain and/or other side effects. Further work will investigate increasing the power of the analysis by mirroring the patients’ anatomy to overlay left/right-sided dose distribution, and including patients treated in the prone position.