Dynamic contrast-enhanced magnetic resonance imaging biomarkers predict chemotherapeutic responses and survival in primary central-nervous-system lymphoma

Prognostic Assessment in Patients With Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Using MRI-Based Radiomics

BACKGROUND

Primary central nervous system lymphoma (PCNSL) carries a poor prognosis. Radiomics may hold potential value in prognostic assessment.

PURPOSE

To develop and validate an MRI-based radiomics model and combine it with clinical factors to assess progression-free survival (PFS) and overall survival (OS) of patients with PCNSL.

STUDY TYPE

Retrospective and prospective.

POPULATION

Three hundred seventy-nine patients (179 female, 53 ± 7 years) from 2014 to 2022.

FIELD STRENGTH/SEQUENCE

T2/fluid-attenuated inversion recovery, contrast-enhanced T1WI and diffusion-weighted echo-planar imaging sequences on 3.0 T.

ASSESSMENT

Radiomics features were extracted from enhanced tumor regions on preoperative multi-sequence MRI. Using a least absolute shrinkage and selection operator (LASSO) Cox regression model to select radiomic signatures in training cohort (N = 169). Cox proportional hazards models were constructed for clinical, radiomics, and combined models, with internal (N = 72) and external (N = 32) cohorts validating model performance.

STATISTICAL TESTS

Chi-squared, Mann-Whitney, Kaplan-Meier, log-rank, LASSO, Cox, decision curve analysis, time-dependent Receiver Operating Characteristic, area under the curve (AUC), and likelihood ratio test. P-value <0.05 was considered significant.

RESULTS

Follow-up duration was 28.79 ± 22.59 months (median: 25). High-risk patients, determined by the median radiomics score, showed significantly lower survival rates than low-risk patients. Compared with NCCN-IPI, conventional imaging and clinical models, the combined model achieved the highest C-index for both PFS (0.660 internal, 0.802 external) and OS (0.733 internal, 0.781 external) in validation. Net benefit was greater with radiomics than with clinical alone. The combined model exhibited performance with AUCs of 0.680, 0.752, and 0.830 for predicting 1-year, 3-year, and 5-year PFS, and 0.770, 0.789, and 0.863 for OS in internal validation, with PFS AUCs of 0.860 and 0.826 and OS AUCs of 0.859 and 0.748 for 1-year and 3-year survival in external validation.

DATA CONCLUSION

Incorporating a multi-sequence MR-based radiomics model into clinical models enhances the assess accuracy for the prognosis of PCNSL.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

CT-defined sarcopenia predicts treatment response in primary central nervous system lymphomas

OBJECTIVE

Body composition assessment derived from cross-sectional imaging has shown promising results as a prognostic biomarker in several tumor entities. Our aim was to analyze the role of low skeletal muscle mass (LSMM) and fat areas for prognosis of dose-limiting toxicity (DLT) and treatment response in patients with primary central nervous system lymphoma (PCNSL).

METHODS

Overall, 61 patients (29 female patients, 47.5%) with a mean age of 63.8 ± 12.2 years, range 23-81 years, were identified in the data base between 2012 and 2020 with sufficient clinical and imaging data. Body composition assessment, comprising LSMM and visceral and subcutaneous fat areas, was performed on one axial slice on L3-height derived from staging computed tomography (CT) images. DLT was assessed during chemotherapy in clinical routine. Objective response rate (ORR) was measured on following magnetic resonance images of the head accordingly to the Cheson criteria.

RESULTS

Twenty-eight patients had DLT (45.9%). Regression analysis revealed that LSMM was associated with objective response, OR = 5.19 (95% CI 1.35-19.94, p = 0.02) (univariable regression), and OR = 4.23 (95% CI 1.03- 17.38, p = 0.046) (multivariable regression). None of the body composition parameters could predict DLT. Patients with normal visceral to subcutaneous ratio (VSR) could be treated with more chemotherapy cycles compared to patients with high VSR (mean, 4.25 vs 2.94, p = 0.03). Patients with ORR had higher muscle density values compared to patients with stable and/or progressive disease (34.46 ± vs 28.18 ± HU, p = 0.02).

CONCLUSIONS

LSMM is strongly associated with objective response in patients with PCNSL. Body composition parameters cannot predict DLT.

CLINICAL RELEVANCE STATEMENT

Low skeletal muscle mass on computed tomography (CT) is an independent prognostic factor of poor treatment response in central nervous system lymphoma. Analysis of the skeletal musculature on staging CT should be implemented into the clinical routine in this tumor entity.

KEY POINTS

• Low skeletal muscle mass is strongly associated with the objective response rate. • No body composition parameters could predict dose-limiting toxicity.

Utility of contrast-enhanced MRI radiomics features combined with clinical indicators for predicting induction chemotherapy response in primary central nervous system lymphoma

PURPOSE

To assess the utility of combining contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics features with clinical variables in predicting the response to induction chemotherapy (IC) for primary central nervous system lymphoma (PCNSL).

METHODS

A total of 131 patients with PCNSL (101 in the training set and 30 in the testing set) who had undergone contrast-enhanced MRI scans were retrospectively analyzed. Pyradiomics was utilized to extract radiomics features, and the clinical variables of the patients were gathered. Radiomics prediction models were developed using different combinations of feature selection methods and machine learning models, and the best combination was ultimately chosen. We screened clinical variables associated with treatment outcomes and developed clinical prediction models. The predictive performance of radiomics model, clinical model, and combined model, which integrates the best radiomics model and clinical characteristics, was independently assessed and compared using Receiver Operating Characteristic (ROC) curves.

RESULTS

In total, we extracted 1598 features. The best radiomics model we selected as the best utilized T-test and Recursive Feature Elimination (RFE) for feature selection and logistic regression for model building. Serum Interleukin 2 Receptor (IL-2R) and Eastern Cooperative Oncology Group (ECOG) Score were utilized to develop a clinical predictive model for assessing the response to induction chemotherapy. The results of the testing set revealed that the combined prediction model (radiomics and IL-2R) achieved the highest area under the ROC curve at 0.868 (0.683, 0.967), followed by the radiomics model at 0.857 (0.681, 0.957), and the clinical prediction model (IL-2R and ECOG) at 0.618 (0.413, 0.797). The combined model was significantly more accurate than the clinical model, with an AUC of 0.868 compared to 0.618 (P < 0.05). While the radiomics model had slightly better predictive power than the clinical model, this difference was not statistically significant (AUC, 0.857 vs. 0.618, P > 0.05).

CONCLUSIONS

Our prediction model, which combines radiomics signatures from CE-MRI with serum IL-2R, can effectively stratify patients with PCNSL before high-dose methotrexate (HD-MTX) -based chemotherapy.

Dual-Layer Spectral Detector Computed Tomography Quantitative Parameters: A Potential Tool for Lymph Node Activity Determination in Lymphoma Patients

Dual-energy CT has shown promising results in determining tumor characteristics and treatment effectiveness through spectral data by assessing normalized iodine concentration (nIC), normalized effective atomic number (nZeff), normalized electron density (nED), and extracellular volume (ECV). This study explores the value of quantitative parameters in contrast-enhanced dual-layer spectral detector CT (SDCT) as a potential tool for detecting lymph node activity in lymphoma patients. A retrospective analysis of 55 lymphoma patients with 289 lymph nodes, assessed through 18FDG-PET/CT and the Deauville five-point scale, revealed significantly higher values of nIC, nZeff, nED, and ECV in active lymph nodes compared to inactive ones (p < 0.001). Generalized linear mixed models showed statistically significant fixed-effect parameters for nIC, nZeff, and ECV (p < 0.05). The area under the receiver operating characteristic curve (AUROC) values of nIC, nZeff, and ECV reached 0.822, 0.845, and 0.811 for diagnosing lymph node activity. In conclusion, the use of g nIC, nZeff, and ECV as alternative imaging biomarkers to PET/CT for identifying lymph node activity in lymphoma holds potential as a reliable diagnostic tool that can guide treatment decisions.

[18F]FDG PET-MRI provides survival biomarkers in primary central nervous system lymphoma in the elderly: an ancillary study from the BLOCAGE trial of the LOC network

PURPOSE

Primary central nervous system lymphoma (PCNSL) incidence is rising among elderly patients, presenting challenges due to poor prognosis and treatment-related toxicity risks. This study explores the potential of combining [18F]fluorodeoxyglucose ([18F]FDG) PET scans and multimodal MRI for improving management in elderly patients with de novo PCNSL.

METHODS

Immunocompetent patients over 60 years with de novo PCNSL were prospectively enrolled in a multicentric study between January 2016 and April 2021. Patients underwent brain [18F]FDG PET-MRI before receiving high-dose methotrexate-based chemotherapy. Relationships between extracted PET (metabolic tumor volume (MTV), sum of MTV for up to five lesions (sumMTV), metabolic imaging lymphoma aggressiveness score (MILAS)) and MRI parameters (tumor contrast-enhancement size, cerebral blood volume (CBV), cerebral blood flow (CBF), apparent diffusion coefficient (ADC)) and treatment response and outcomes were analyzed.

RESULTS

Of 54 newly diagnosed diffuse large B-cell PCNSL patients, 52 had positive PET and MRI with highly [18F]FDG-avid and contrast-enhanced disease (SUVmax: 27.7 [22.8-36]). High [18F]FDG uptake and metabolic volume were significantly associated with low ADCmean values and high CBF at baseline. Among patients, 69% achieved an objective response at the end of induction therapy, while 17 were progressive. Higher cerebellar SUVmean and lower sumMTV at diagnosis were significant predictors of complete response: 6.4 [5.7-7.7] vs 5.4 [4.5-6.6] (p = 0.04) and 5.5 [2.1-13.3] vs 15.9 [4.2-19.5] (p = 0.01), respectively. Two-year overall survival (OS) was 71%, with a median progression-free survival (PFS) of 29.6 months and a median follow-up of 37 months. Larger tumor volumes on PET or enhanced T1-weighted MRI were significant predictors of poorer OS, while a high MILAS score at diagnosis was associated with early death (< 1 year).

CONCLUSION

Baseline cerebellar metabolism and sumMTV may predict response to end of chemotherapy in PCNSL. Tumor volume and MILAS at baseline are strong prognostic factors.

Early MRI Predictors of Relapse in Primary Central Nervous System Lymphoma Treated with MATRix Immunochemotherapy

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. ADC_mean 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.

The findings on the CEUS of diffuse large B cell lymphoma in abdomen: A case report and literature review

Background

PET-CT is the first choice for the imaging diagnosis of intraperitoneal lymphomas. Contrast-enhanced ultrasound (CEUS) is rare in the diagnosis of intraperitoneal nodal lymphoma.

Case summary

A 62-year-old man was admitted for examination with "right upper abdominal pain". Ultrasound was used to refer to the masses in the hilar region, spleen, and anterior sacral region respectively. The masses were all hypoechoic, and blood flow signals could be detected by CDFI. Laboratory tests of CA125 were within normal limits. CEUS examination was performed on the three masses respectively. The three masses showed different perfusion patterns. Thickened vessels appeared around the mass in the hilar region, a peripheral centrally directed perfusion pattern was observed in the splenic mass, and blood supply vessels appeared in the center of the presacral mass with a significant filling defect. They all showed a contrast pattern with rapid clearance and hypoenhancement compared with the surrounding areas. Ultrasound guided needle biopsy revealed non-Hodgkin's lymphoma, diffuse large B-cell lymphoma, non-germinal center origin. After biopsy, the patient was treated with R-CHOP regimen for chemotherapy, and the tumor disappeared by routine ultrasound review after 5 cycles of chemotherapy.

Conclusion

To the best of our knowledge, this report is the first to describe the findings of CEUS in intraperitoneal nodal lymphoma. CEUS has various manifestations in intraperitoneal nodal lymphoma. Future studies are still needed to explore the diagnostic features of CEUS in intraperitoneal nodal lymphoma.

Prognostic factors in primary central nervous system lymphoma

PURPOSE OF REVIEW

Primary central nervous system lymphoma (PCNSL) is a rare and aggressive extranodal diffuse large B cell lymphoma. Despite its apparent immunopathological homogeneity, PCNSL displays a wide variability in outcome. Identifying prognostic factors is of importance for patient stratification and clinical decision-making. The purpose of this review is to focus on the clinical, neuroradiological and biological variables correlated with the prognosis at the time of diagnosis in immunocompetent patients.

RECENT FINDINGS

Age and performance status remain the most consistent clinical prognostic factors. The current literature suggests that neurocognitive dysfunction is an independent predictor of poor outcome. Cumulating data support the prognostic value of increased interleukin-10 level in the cerebrospinal fluid (CSF), in addition to its interest as a diagnostic biomarker. Advances in neuroimaging and in omics have identified several semi-quantitative radiological features (apparent diffusion restriction measures, dynamic contrast-enhanced perfusion MRI (pMRI) pattern and 18F-fluorodeoxyglucose metabolism) and molecular genetic alterations with prognostic impact in PCNSL.

SUMMARY

Validation of new biologic and neuroimaging markers in prospective studies is required before integrating future prognostic scoring systems. In the era of radiomic, large clinicoradiological and molecular databases are needed to develop multimodal artificial intelligence algorithms for the prediction of accurate outcome.

Branch-like enhancement on contrast enhanced MRI is a specific finding of cerebellar lymphoma compared with other pathologies

Branch-like enhancement (BLE) on contrast-enhanced (CE) magnetic resonance imaging (MRI) was found to be effective in differentiating primary central nervous system lymphoma (PCNSL) from high-grade glioma (HGG) in the cerebellum. However, whether it can be applied to assessments of secondary central nervous system lymphoma (SCNSL), or other cerebellar lesions is unknown. Hence, we retrospectively reviewed cerebellar masses to investigate the use of BLE in differentiating cerebellar lymphoma (CL), both primary and secondary, from other lesions. Two reviewers qualitatively evaluated the presence and degree of BLE on CE-T1 weighted imaging (T1WI). If multiple views were available, we determined the view in which BLE was the most visible. Seventy-five patients with the following pathologies were identified:17 patients with CL, 30 patients with metastasis, 12 patients with hemangioblastoma, 9 patients with HGG, and 7 patients with others. Twelve patients presented with PCNSL and five with SCNSL. Of 17 patients with CL, 15 (88%) had BLE, whereas three (5%) out of 58 patients in the non-CL group showed BLE. In patients who underwent three-dimensional-CE-T1WI, BLE was the most visible on the sagittal image. In conclusion, BLE is a highly specific finding for CL and the sagittal image is important in evaluating this finding.

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

Blood-Brain Barrier Repair of Bevacizumab and Corticosteroid as Prediction of Clinical Improvement and Relapse Risk in Radiation-Induced Brain Necrosis: A Retrospective Observational Study

Background

Blood-brain barrier (BBB) disruption after endothelial damage is a crucial part of radiation-induced brain necrosis (RN), but little is known of BBB disruption quantification and its role in the evaluation of therapeutic effect and prognosis for drug treatment. In this retrospective study, BBB repair by bevacizumab and corticosteroid and the correlation between BBB permeability and treatment response and relapse were evaluated by dynamic contrast-enhanced MRI (DCE-MRI).

Methods

Forty-one patients with RN after radiotherapy for nasopharyngeal carcinoma (NPC) (28 treated with bevacizumab and 13 with corticosteroid), 12 patients with no RN after NPC radiotherapy, and 12 patients with no radiotherapy history were included as RN, non-RN, and normal groups, respectively. DCE-MRI assessed BBB permeability in white matter of bilateral temporal lobe. DCE parameters were compared at baseline among the three groups. DCE parameters after treatment were compared and correlated with RN volume decrease, neurological improvement, and relapse.

Results

The extent of BBB leakage at baseline increased from the normal group and non-RN group and to RN necrosis lesions, especially K ^trans (Kruskal-Wallis test, P < 0.001). In the RN group, bevacizumab-induced K ^trans and v _e decrease in radiation necrosis lesions (both P < 0.001), while corticosteroid showed no obvious effect on BBB. The treatment response rate of bevacizumab was significantly higher than that of corticosteroid [30/34 (88.2%) vs. 10/22 (45.4%), P < 0.001]. Spearman analysis showed baseline K ^trans, K _ep, and v _p positively correlated with RN volume decrease and improvement of cognition and quality of life in bevacizumab treatment. After a 6-month follow-up for treatment response cases, the relapse rate of bevacizumab and corticosteroid was 10/30 (33.3%) and 2/9 (22.2%), respectively, with no statistical difference. Post-bevacizumab K ^trans level predicted relapse in 6 months with AUC 0.745 (P < 0.05, 95% CI 0.546-0.943, sensitivity = 0.800, specificity = 0.631).

Conclusions

Bevacizumab improved BBB leakage in RN necrosis. DCE parameters may be useful to predict therapeutic effect and relapse after bevacizumab.