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- Title
Early MRI Predictors of Relapse in Primary Central Nervous System Lymphoma Treated with MATRix Immunochemotherapy.
- Authors
Cornell, Isabel; Al Busaidi, Ayisha; Wastling, Stephen; Anjari, Mustafa; Cwynarski, Kate; Fox, Christopher P.; Martinez-Calle, Nicolas; Poynton, Edward; Maynard, John; Thust, Steffi C.
- Abstract
Primary Central Nervous System Lymphoma (PCNSL) is a highly malignant brain tumour. We investigated dynamic changes in tumour volume and apparent diffusion coefficient (ADC) measurements for predicting outcome following treatment with MATRix chemotherapy in PCNSL. Patients treated with MATRix (n = 38) underwent T1 contrast-enhanced (T1CE) and diffusion-weighted imaging (DWI) before treatment, after two cycles and after four cycles of chemotherapy. Response was assessed using the International PCNSL Collaborative Group (IPCG) imaging criteria. ADC histogram parameters and T1CE tumour volumes were compared among response groups, using one-way ANOVA testing. Logistic regression was performed to examine those imaging parameters predictive of response. Response after two cycles of chemotherapy differed from response after four cycles; of the six patients with progressive disease (PD) after four cycles of treatment, two (33%) had demonstrated a partial response (PR) or complete response (CR) after two cycles. ADCmean at baseline, T1CE at baseline and T1CE percentage volume change differed between response groups (0.005 < p < 0.038) and were predictive of MATRix treatment response (area under the curve: 0.672–0.854). Baseline ADC and T1CE metrics are potential biomarkers for risk stratification of PCNSL patients early during remission induction therapy with MATRix. Standard interim response assessment (after two cycles) according to IPCG imaging criteria does not reliably predict early disease progression in the context of a conventional treatment approach.
- Subjects
CENTRAL nervous system; KIRKENDALL effect; REMISSION induction; DIFFUSION magnetic resonance imaging; LYMPHOMAS
- Publication
Journal of Personalized Medicine, 2023, Vol 13, Issue 7, p1182
- ISSN
2075-4426
- Publication type
Article
- DOI
10.3390/jpm13071182