P05.01 Prospective validation trial of magnetic resonance imaging based Contrast Clearance Analysis (CCA) to differentiate between pseudoprogression/radiation necrosis and progressive disease following cranial radiotherapy. (9th September 2021)

• Record Type: Journal Article
• Authors: Bodensohn, R; Forbrig, R; Lietke, S; Reis, J; Boulesteix, A; Albert, N L; Dorostkar, M; Corradini, S; Belka, C; Thon, N; Niyazi, M
• Is Part Of: Neuro-oncology. Volume 23: Supplement 2 (2021)
• Page Start: ii23
• Page End: ii23
• Publication Date: 2021-09-09
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab180.077
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Pseudoprogression (PsP) or radiation necrosis (RN) may frequently occur after cranial radiotherapy and show a similar imaging pattern compared to progressive disease (PD). Even for experienced neuroradiologists, it remains challenging to distinguish between these clinically relevant disease states. We aimed to evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) based Contrast Clearance Analysis (CCA) in this clinical setting. MATERIAL AND METHODS: Patients with equivocal imaging findings after cranial radiotherapy were consecutively included into this monocentric prospective study. Assuming a true accuracy of 90% and setting the significance level to 0.05, N=33 patients are required to show that accuracy is larger than 70% with a power of 80% using a one-sided binomial test. CCA was performed by subtraction of imaging features in late vs early T1-weighted sequences after contrast-agent application. Two experienced neuroradiologists evaluated CCA with respect to PsP/RN and PD being blinded for FET PET and histological findings; histopathological diagnosis was based on stereotactic biopsy or resection for space-occupying processes. The radiological assessment was compared with the histopathological results, and its accuracy was calculated statistically. RESULTS: Thirty-three patients were included; sixteen (48.5%) were treated because of a primary brain tumors, and 17 (51.1%) with brain metastases. In one patient, CCA was technically infeasible. The accuracy of CCA in predicting the histological result was 0.84 (95% CI 0.67–0.95; one-sided p=0.05; N=32). An accuracy of 0.85 (95% CI 0.68–0.95; one-sided p=0.04) would have been obtained in case of a correct classification in the non-analyzable case. Sensitivity and specificity of CCA were 0.93 (95%-CI 0.66–1.00) and 0.78 (95% CI 0.52–0.94), respectively. The accuracy in metastases patients was 0.94 (95% CI 0.71 - 1.00) and non-significantly higher compared to primary brain tumor patients with accuracy of 0.73 (95% CI 0.45 - 0.92), p=0.16. CONCLUSION: In this study, CCA was a highly accurate, easy and helpful method for distinguishing PsP or RN from PD after cranial radiotherapy, especially in brain metastases patients after radiosurgical treatment.