ADC histogram analysis can predict tumor proliferation, survival in immunocompetent patients with PCNSL

Reviewed by Emily Henderson, B.Sc.Jan 12 2021

The cover for issue 45 of Oncotarget features Figure 3, "Representative images of whole tumor volume segmentation of the co-registered T1 post-contrast sequence and apparent diffusion coefficient (ADC) map, yielding the corresponding ADC histogram distribution utilized for data analysis," recently published in "Diffusion-weighted MR imaging histogram analysis in HIV positive and negative patients with primary central nervous system lymphoma as a predictor of outcome and tumor proliferation" by Khan, et al.

This author reported that the aim of this study is to investigate the correlation between ADC parameters, Ki-67 expression, overall survival, and progression-free survival in PCNSL.

Selection criteria yielded 90 patients, 23 patients living with HIV, and 67 immunocompetent patients.

In patients with available Ki-67 expression data, nADCmean, nADC15, and nADC75 inversely correlated with Ki-67 expression.

For PLWH, there was no correlation between ADC parameters and Ki-67 expression or clinical outcomes.

ADC histogram analysis can predict tumor proliferation and survival in immunocompetent patients with PCNSL, but with limited utility in PLWH.

Primary central nervous system lymphoma (PCNSL) is a rare subgroup of non-Hodgkin lymphoma confined to the central nervous system, with more than 90% of cases classified as Diffuse Large B-cell Lymphoma."

Dr. Bilal Khan, Baylor College of Medicine

Diffusion-weighted imaging and corresponding apparent diffusion coefficient maps can provide a representation of the cellular microenvironment with several studies demonstrating that ADC values can predict tumor cellularity across various neoplasms, including lymphomas.

In a recent similar study of whole tumor histogram analysis in PCNSL performed by the authors of this study, multiple ADC parameters were inversely correlated with Ki-67 expression and associated with poorer OS.

However, tumor segmentation was performed using only the ADC sequence with the potential inclusion of intra-tumoral necrosis, hemorrhage or regions outside of the actual solid tumor that would otherwise have been excluded with contrast co-registration, ultimately providing a suboptimal representation of true tumor parenchyma.

The primary aim of this study is to more comprehensively evaluate the relationship between ADC calculations with tumor Ki-67 expression and clinical outcomes using a larger patient sample with the inclusion of PLWH and whole tumor segmentation with T1 post-contrast co-registration.

The Oncotarget author's hypothesis is that ADC values will inversely correlate with Ki-67 expression and that tumors with higher ADC values above the median will have improved OS and PFS.

The Khan Research Team concluded in their Oncotarget Research Paper that the role of MR in PCNSL historically has been the detection and qualitative evaluation of response to treatment.

DWI and derived ADC maps have been a well-established tool in neuroimaging, but the use of ADC histogram profiling has not been widely accepted in daily practice.

This data expands the role of conventional MR imaging by utilizing quantitative ADC histogram analysis to predict clinical outcomes and tumor expression of Ki-67, a biomarker for tumor proliferative activity, in immunocompetent PCNSL patients.

The role of using ADC as an imaging biomarker in PLWH may be limited.

Quantitative ADC histogram analysis should be strongly considered as part of the imaging protocol in the evaluation of immunocompetent patients with PCNSL.