Senologie - Zeitschrift für Mammadiagnostik und -therapie 2019; 16(02): e8
DOI: 10.1055/s-0039-1687955
Abstracts
Georg Thieme Verlag KG Stuttgart · New York

Automated radiomic MRI phenotyping improves survival prediction in primary breast-cancer

M Dietzel
1   University Hospital Erlangen, Department of Radiology, Erlangen, Deutschland
,
R Schulz-Wendtland
1   University Hospital Erlangen, Department of Radiology, Erlangen, Deutschland
,
S Ellmann
1   University Hospital Erlangen, Department of Radiology, Erlangen, Deutschland
,
E Wenkel
1   University Hospital Erlangen, Department of Radiology, Erlangen, Deutschland
,
M Uder
1   University Hospital Erlangen, Department of Radiology, Erlangen, Deutschland
,
P Baltzer
2   Medical University of Vienna, Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Vienna, Österreich
› Author Affiliations
Further Information

Publication History

Publication Date:
28 May 2019 (online)

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Background:

To investigate whether automated radiomic MRI-phenotyping (ARM) could improve survival prediction in primary breast-cancer.

Methods:

314 consecutive patients with primary invasive breast-cancer received standard staging breast-MRI before the initiation of treatment according to international recommendations. Diagnostic work-up, treatment, and follow-up was done at one tertiary care, academic breast-centre (disease-specific survival/DSS = 279; disease-specific death/DSD = 35; mean survival: 84.5 months). The Nottingham Prognostic Index (NPI) was used as the reference method with which to predict survival of breast-cancer. ARM was accomplished by commercially available, FDA-cleared software.

DSD served as endpoint. Integration of ARM into the NPI gave NPI+ (Cox regression). Prediction of DSD by NPI vs. NPI+ was investigated (Kaplan Meier statistics, HR: Hazard-ratio; alpha = 0.5, Logrank test; predictive accuracy: Harrell's C).

Results:

Prognostication of the endpoint by NPI (Harrell's C = 75.3%) was significantly enhanced by ARM (NPI+: Harrell's C = 81.0%, P = 0.03). Most of all, NPI+ more reliably identified patients with unfavourable outcome compared to NPI alone (HR = 3.14; P = 0.0001).

Zoom Image
Fig. 1: Prediction of patient outcome – comparison of NPI+ vs. NPI.]
Kaplan Meier survival analysis stratified by outcome prediction as disease-specific death or survival (DSD or DSS) by the Nottingham Prognostic Index (NPI) and the NPI+. The NPI+ integrates MRI patterns into the NPI (details see table 2):
· NPI+ more precisely identified patients with unfavourable outcome (DSD).
· The better prediction of unfavourable outcome by NPI+ was not on the price of a worse prediction of disease-specific survival (DSS).

Conclusions:

Automated radiomic MRI-phenotyping (ARM) improved survival prediction in primary breast-cancer. Most of all ARM contributed to the identification of patients at higher risk of an unfavourable outcome.

Future studies should investigate ARM as a potential “gate keeper” in the management of breast-cancer patients. Such a “gate keeper” could assist in selecting patient benefitting from more advanced diagnostic procedures (genetic profiling etc.) in order to decide whether are a more aggressive therapy (chemotherapy) is warranted.