Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma.

Inadequate molecular and clinical stratification of the patients with high-risk diffuse large B-cell lymphoma (DLBCL) is a clinical challenge hampering the establishment of personalized therapeutic options. We studied the translational significance of liquid biopsy in a uniformly treated trial cohort. Pretreatment circulating tumor DNA (ctDNA) revealed hidden clinical and biological heterogeneity, and high ctDNA burden determined increased risk of relapse and death independently of conventional risk factors. Genomic dissection of pretreatment ctDNA revealed translationally relevant phenotypic, molecular, and prognostic information that extended beyond diagnostic tissue biopsies. During therapy, chemorefractory lymphomas exhibited diverging ctDNA kinetics, whereas end-of-therapy negativity for minimal residual disease (MRD) characterized cured patients and resolved clinical enigmas, including false residual PET positivity. Furthermore, we discovered fragmentation disparities in the cell-free DNA that characterize lymphoma-derived ctDNA and, as a proof-of-concept for their clinical application, used machine learning to show that end-of-therapy fragmentation patterns predict outcome. Altogether, we have discovered novel molecular determinants in the liquid biopsy that can noninvasively guide treatment decisions.

Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast-based MRI in rectal cancer.

BACKGROUND: Dynamic contrast-based MRI and intravoxel incoherent motion imaging (IVIM) MRI are both methods showing promise as diagnostic and prognostic tools in rectal cancer. Both methods aim at measuring perfusion-related parameters, but the relationship between them is unclear. PURPOSE: To investigate the relationship between perfusion- and permeability-related parameters obtained by IVIM-MRI, T1 -weighted dynamic contrast-enhanced (DCE)-MRI and T2 *-weighted dynamic susceptibility contrast (DSC)-MRI. STUDY TYPE: Prospective. SUBJECTS: In all, 94 patients with histologically confirmed rectal cancer. FIELD STRENGTH/SEQUENCE: Subjects underwent pretreatment 1.5T clinical procedure MRI, and in addition a study-specific diffusion-weighted sequence (b = 0, 25, 50, 100, 500, 1000, 1300 s/mm2 ) and a multiecho dynamic contrast-based echo-planer imaging sequence. ASSESSMENT: Median tumor values were obtained from IVIM (perfusion fraction [f], pseudodiffusion [D*], diffusion [D]), from the extended Tofts model applied to DCE data (Ktrans , kep , vp , ve ) and from model free deconvolution of DSC (blood flow [BF] and area under curve). A subgroup of the excised tumors underwent immunohistochemistry with quantification of microvessel density and vessel size. STATISTICAL TEST: Spearman's rank correlation test. RESULTS: D* was correlated with BF (rs = 0.47, P < 0.001), and f was negatively correlated with kep (rs = -0.31, P = 0.002). BF was correlated with Ktrans (rs = 0.29, P = 0.004), but this correlation varied extensively when separating tumors into groups of low (rs = 0.62, P < 0.001) and high (rs = -0.06, P = 0.68) BF. Ktrans was negatively correlated with vessel size (rs = -0.82, P = 0.004) in the subgroup of tumors with high BF. DATA CONCLUSION: We found an association between D* from IVIM and BF estimated from DSC-MRI. The relationship between IVIM and DCE-MRI was less clear. Comparing parameters from DSC-MRI and DCE-MRI highlights the importance of the underlying biology for the interpretation of these parameters. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1114-1124.