Molecular diagnosis of primary CNS lymphoma in 2024 using MYD88Leu265Pro and IL-10.

Early diagnosis is crucial for the successful treatment of primary CNS lymphoma (PCNSL), a rapidly progressing tumour. Suspicion raised on brain MRI must be confirmed by a histopathological diagnosis of a tumour specimen collected by stereotactic biopsy. In rare cases, cerebrospinal fluid (CSF) or vitreous humour might aid in providing a cytological diagnosis. Several disease-related, patient-related, and treatment-related factors affect the timing and accuracy of diagnosis and patient outcome. Some molecules detected in CSF, aqueous and vitreous humour, and peripheral blood were proposed as diagnostic biomarkers for PCNSL; however, detection methods for most of these molecules are not yet standardised, have a long turnaround time, are expensive, and have little reproducibility among labs. By contrast, the MYD88Leu265Pro somatic hotspot mutation, revealed by PCR-based assay, is currently and reliably used during the diagnosis of some lymphomas, and IL-10, measured by enzyme-linked immunosorbent assay, is routinely used to diagnose and monitor different common metabolic and immunological diseases. Several independent studies have shown that MYD88Leu265Pro and IL-10 can be easily assessed in peripheral blood, plasma, aqueous and vitreous humour, and CSF of patients with PCNSL with substantial sensitivity and specificity, especially when evaluated in combination. In this Viewpoint, evidence supporting the routine use of MYD88Leu265Pro and IL-10 in diagnosing PCNSL is considered, and some examples of the frequent difficulties found in the diagnosis of PCNSL are provided, highlighting the role and indications of these two biomarkers to improve the timely recognition of this aggressive tumour.

Deep learning-based overall survival prediction model in patients with rare cancer: a case study for primary central nervous system lymphoma.

PURPOSE: Primary central nervous system lymphoma (PCNSL) is a rare, aggressive form of extranodal non-Hodgkin lymphoma. To predict the overall survival (OS) in advance is of utmost importance as it has the potential to aid clinical decision-making. Though radiomics-based machine learning (ML) has demonstrated the promising performance in PCNSL, it demands large amounts of manual feature extraction efforts from magnetic resonance images beforehand. deep learning (DL) overcomes this limitation. METHODS: In this paper, we tailored the 3D ResNet to predict the OS of patients with PCNSL. To overcome the limitation of data sparsity, we introduced data augmentation and transfer learning, and we evaluated the results using r stratified k-fold cross-validation. To explain the results of our model, gradient-weighted class activation mapping was applied. RESULTS: We obtained the best performance (the standard error) on post-contrast T1-weighted (T1Gd)-area under curve [Formula: see text], accuracy [Formula: see text], precision [Formula: see text], recall [Formula: see text] and F1-score [Formula: see text], while compared with ML-based models on clinical data and radiomics data, respectively, further confirming the stability of our model. Also, we observed that PCNSL is a whole-brain disease and in the cases where the OS is less than 1 year, it is more difficult to distinguish the tumor boundary from the normal part of the brain, which is consistent with the clinical outcome. CONCLUSIONS: All these findings indicate that T1Gd can improve prognosis predictions of patients with PCNSL. To the best of our knowledge, this is the first time to use DL to explain model patterns in OS classification of patients with PCNSL. Future work would involve collecting more data of patients with PCNSL, or additional retrospective studies on different patient populations with rare diseases, to further promote the clinical role of our model.

CSF-based liquid biopsy pointing to a diagnosis of diffuse glioma in a patient with supposed neurodegenerative disorder.

INTRODUCTION: The differential diagnosis of brain diseases becomes challenging in cases where imaging is not sufficiently informative, and surgical biopsy is impossible or unacceptable to the patient. METHODS: An elderly patient with progressive short-term memory loss and cognitive impairment presented with a normal brain CT scan, a brain FDG-PET that indicated symmetrical deterioration of the white matter in the frontal lobes, and inconclusive results of a molecular marker analysis of suspected dementia in cerebrospinal fluid (CSF). Brain MRI suggested the diagnosis of lower grade glioma. The patient refused surgical biopsy. In order to investigate whether somatic mutations associated with gliomas existed, we performed a "liquid biopsy" by the targeted sequencing of cell-free DNA (cfDNA) from his CSF. RESULTS: Deep sequencing of the cfDNA from CSF revealed somatic mutations characteristically found in gliomas, including mutations of the TP53 (Arg282Trp), BRAF (Val600Glu), and IDH1 (Arg132His) genes. The patient is currently treated with temozolomide, and his clinical and MRI findings suggest the stabilization of his disease. CONCLUSION: Neurological patients may benefit from liquid biopsy diagnostic work-up as it can reveal therapeutically targetable mutations.

Radiomics-Based Machine Learning Model for Predicting Overall and Progression-Free Survival in Rare Cancer: A Case Study for Primary CNS Lymphoma Patients.

Primary Central Nervous System Lymphoma (PCNSL) is an aggressive neoplasm with a poor prognosis. Although therapeutic progresses have significantly improved Overall Survival (OS), a number of patients do not respond to HD-MTX-based chemotherapy (15-25%) or experience relapse (25-50%) after an initial response. The reasons underlying this poor response to therapy are unknown. Thus, there is an urgent need to develop improved predictive models for PCNSL. In this study, we investigated whether radiomics features can improve outcome prediction in patients with PCNSL. A total of 80 patients diagnosed with PCNSL were enrolled. A patient sub-group, with complete Magnetic Resonance Imaging (MRI) series, were selected for the stratification analysis. Following radiomics feature extraction and selection, different Machine Learning (ML) models were tested for OS and Progression-free Survival (PFS) prediction. To assess the stability of the selected features, images from 23 patients scanned at three different time points were used to compute the Interclass Correlation Coefficient (ICC) and to evaluate the reproducibility of each feature for both original and normalized images. Features extracted from Z-score normalized images were significantly more stable than those extracted from non-normalized images with an improvement of about 38% on average (p-value < 10-12). The area under the ROC curve (AUC) showed that radiomics-based prediction overcame prediction based on current clinical prognostic factors with an improvement of 23% for OS and 50% for PFS, respectively. These results indicate that radiomics features extracted from normalized MR images can improve prognosis stratification of PCNSL patients and pave the way for further study on its potential role to drive treatment choice.

Imaging characterization of an adult H3 K27M-altered diffuse midline glioma of the medulla oblongata with a confounding steroid response.

We report an uncommon, infratentorial localization of adult H3 K27M-altered diffuse midline glioma arising in a particularly rare site (medulla oblongata). In addition to this unusual presentation, the lesion exhibited a substantial contrast enhancement and size decrease after dexamethasone, generating diagnostic dilemmas. Histology, molecular details, advanced Magnetic Resonance imaging features and differential diagnoses are here described and discussed, as well as common misconceptions about steroid-sensitive mass lesions, and practical difficulties for clinicians involved in the process of making diagnosis.

Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study.

Background: Tumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging. Objectives: This study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity. Materials and Methods: Seventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats' spatial distribution, quantitative features and histopathological characteristics were analyzed. Results: A highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed. Conclusion: Preliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.

A narrative review of consolidation strategies for young and fit patients with newly-diagnosed primary central nervous system lymphoma.

INTRODUCTION: The modern treatment of patients with primary central nervous system lymphoma (PCNSL) consists of two phases: induction, currently represented by a high-dose-methotrexate-based polychemotherapy, and consolidation. The optimal consolidation therapy has not been defined yet, but several strategies, such as whole-brain radiotherapy (WBRT), high-dose chemotherapy supported by autologous stem cell transplantation (HDC/ASCT) or nonmyeloablative chemotherapy, have been addressed in important randomized trials. AREAS COVERED: This review provides an overview of the current role of consolidation strategies in young and fit patients with newly diagnosed PCNSL. Publications in English language, peer-reviewed, from high-quality international journals, edited from 2003 to 2021 were identified on PubMed. EXPERT OPINION: Consolidation treatment significantly improved outcomes of PCNSL. Radiotherapy had represented for years the only choice in the consolidation therapy, but large randomized trials have demonstrated that HDC/ASCT is equally effective and associated with lower neurotoxicity risk in patients younger than 65-70 years. Encouraging results have been obtained using reduced-dose WBRT, while a recent randomized trial failed to demonstrate that consolidation with nonmyeloablative chemotherapy is more effective than HDC/ASCT in PCNSL patients. A personalized consolidation treatment, driven also by a response prediction model based on radiological and molecular details, may improve the management of PCNSL patients.

Diagnostic efficacy and safety of gadoteridol compared to gadobutrol and gadoteric acid in a large sample of CNS MRI studies at 1.5T.

PURPOSE: To evaluate safety and diagnostic accuracy of gadoteridol vs. other macrocyclic gadolinium-based contrast agents (GBCAs) in a large cohort of consecutive and non-selected patients referred for CE-MRI of the CNS. MATERIAL AND METHODS: Between November 2017 and March 2018, we prospectively enrolled a consecutive cohort of patients referred for neuroradiological CE-MRI (1.5T MRI). Image quality and adverse events were assessed. Diagnostic performance was determined for a subgroup of patients with truth standard findings available. Comparison was made between patients receiving gadoteridol and patients receiving other macrocyclic GBCAs. Inter-reader agreement (kappa) between two expert neuroradiologists was calculated for the diagnosis of malignancy. RESULTS: Overall, 460 patients (220M/240F; mean age 54±16 years) were enrolled of which 230 received gadoteridol (Group 1) and 230 either gadoteric acid or gadobutrol [n=83 (36.1%) and n=147 (63.9%), respectively; Group 2]. Image quality was rated as good or excellent in both groups. The sensitivity, specificity and diagnostic accuracy for determination of malignancy was 88.2%, 96.5% and 95.4%, respectively, for Group 1 and 93.7%, 97.4% and 96.9%, respectively, for Group 2, with no significant differences between groups (P>0.75) for any determination. Inter-reader agreement for the identification of malignancy was excellent [K=0.877 (95%CI: 0.758-0.995) and K=0.818 (95%CI: 0.663-0.972) for groups 1 and 2, respectively; P=0.0913]. Adverse events occurred in 5 of 460 (1.09%) patients overall, with no significant difference (P=0.972) between groups. CONCLUSION: Gadoteridol was safe and guaranteed good image quality without significant differences when compared to gadobutrol and gadoteric acid in a wide range of CNS pathologies.

18F-FAZA PET/CT in pretreatment assessment of hypoxic status in high-grade glioma: correlation with hypoxia immunohistochemical biomarkers.

BACKGROUND: To investigate the correlation between 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET data and hypoxia immunohistochemical markers in patients with high-grade glioma (HGG). PATIENTS AND METHODS: Prospective study including 20 patients with brain MRI suggestive for HGG and undergoing 18F-FAZA PET/CT before treatment for hypoxia assessment. For each 18F-FAZA PET scan SUVmax, SUVmean and 18F-FAZA tumour volume (FTV) at 40, 50 and 60% threshold of SUVmax were calculated; hypoxic volume was estimated by applying different thresholds (1.2, 1.3 and 1.4) to tumour/blood ratio. Seventeen patients were analysed. The immunohistochemical analysis assessed the following parameters: hypoxia-inducible factor 1α, carbonic anhydrase IX (CA-IX), glucose transporter-1, tumour vascularity and Ki-67. RESULTS: 18F-FAZA PET showed a single lesion in 15/17 patients and multiple lesions in 2/17 patients. Twelve/17 patients had grade IV glioma and 5/17 with grade III glioma. Bioptic and surgical samples have been analysed separately. In the surgical subgroup (n = 7) a positive correlation was observed between CA-IX and SUVmax (P = 0.0002), SUVmean40 (P = 0.0058), SUVmean50 (P = 0.009), SUVmean60 (P = 0.0153), FTV-40-50-60 (P = 0.0424) and hypoxic volume1.2-1.3-1.4 (P = 0.0058). In the bioptic group (n = 10) tumour vascularisation was inversely correlated with SUVmax (P = 0.0094), SUVmean40 (P = 0.0107), SUVmean50 (P = 0.0094) and SUVmean60 (P = 0.0154). CONCLUSIONS: The correlation of 18F-FAZA PET parameters with CD31 and CA-IX represents a reliable method for assessing tumour hypoxia in HGG. The inverse correlation between tumour vascularisation, SUVmax and SUVmean suggest that highly vascularized tumours might present more oxygen supply than hypoxia.

MYD88 L265P mutation and interleukin-10 detection in cerebrospinal fluid are highly specific discriminating markers in patients with primary central nervous system lymphoma: results from a prospective study.

Reliable biomarkers are needed to avoid diagnostic delay and its devastating effects in patients with primary central nervous system (CNS) lymphoma (PCNSL). We analysed the discriminating sensitivity and specificity of myeloid differentiation primary response (88) (MYD88) L265P mutation (mut-MYD88) and interleukin-10 (IL-10) in cerebrospinal fluid (CSF) of both patients with newly diagnosed (n = 36) and relapsed (n = 27) PCNSL and 162 controls (118 CNS disorders and 44 extra-CNS lymphomas). The concordance of MYD88 mutational status between tumour tissue and CSF sample and the source of ILs in PCNSL tissues were also investigated. Mut-MYD88 was assessed by TaqMan-based polymerase chain reaction. IL-6 and IL-10 messenger RNA (mRNA) was assessed on PCNSL biopsies using RNAscope technology. IL levels in CSF were assessed by enzyme-linked immunosorbent assay. Mut-MYD88 was detected in 15/17 (88%) PCNSL biopsies, with an 82% concordance in paired tissue-CSF samples. IL-10 mRNA was detected in lymphomatous B cells in most PCNSL; expression of IL-6 transcripts was negligible. In CSF samples, mut-MYD88 and high IL-10 levels were detected, respectively, in 72% and 88% of patients with newly diagnosed PCNSL and in 1% of controls; conversely, IL-6 showed a low discriminating sensitivity and specificity. Combined analysis of MYD88 and IL-10 exhibits a sensitivity and specificity to distinguish PCNSL of 94% and 98% respectively. Similar figures were recorded in patients with relapsed PCNSL. In conclusion, high detection rates of mut-MYD88 and IL-10 in CSF reflect, respectively, the MYD88 mutational status and synthesis of this IL in PCNSL tissue. These biomarkers exhibit a very high sensitivity and specificity in detecting PCNSL both at initial diagnosis and relapse. Implications of these findings in patients with lesions unsuitable for biopsy deserve to be investigated.

Consensus recommendations for MRI and PET imaging of primary central nervous system lymphoma: guideline statement from the International Primary CNS Lymphoma Collaborative Group (IPCG).

Advanced molecular and pathophysiologic characterization of primary central nervous system lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: (1) critically review the use of advanced positron emission tomography (PET) and magnetic resonance imaging (MRI) in the setting of PCNSL; (2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and (3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both "ideal" and "minimum standard" protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.

Primary central nervous system lymphoma: advances in MRI and PET imaging.

Contrast enhanced magnetic resonance imaging (CE-MRI) remains the imaging modality of choice for initial workup, staging, and response assessment after therapy in patients with primary central nervous system lymphoma (PCNSL). While CE-MRI is a sensitive test to detect blood brain barrier (BBB) dysfunction, it does not biologically represent the true tumor burden. Current response assessment criteria relies heavily on two dimensional anatomical measurements on post contrast T1-weighted (T1W) images, as well as pre-contrast T2-weighted (T2W) imaging. Additional MRI features, such as diffusion-weighted imaging (DWI) and perfusion weighted imaging, can be routinely obtained at most centers with MRI capabilities. Emerging evidence supports the incorporation of these data to better define tumor physiology and provide additional valuable clinical tools capable of identifying high risk subgroups as well as early predictors of response to therapies. Further, novel advanced molecular and pathophysiologic characterization of PCNSL provides insights into promising targeted therapeutic approaches. However, significant institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability, reproducibility and eventual translation in day to day management of patients with PCNSL. Here we review established neuroimaging concepts and provide an overview of published literature about novel imaging techniques that may improve diagnosis and response assessments. Finally, we highlight the need for standardization of image acquisition, post-processing, and incorporation of novel imaging biomarkers in early phase PCNSL clinical trials.

Improving the antitumor activity of R-CHOP with NGR-hTNF in primary CNS lymphoma: final results of a phase 2 trial.

Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) is the standard treatment of diffuse large B-cell lymphoma (DLBCL). Primary DLBCL of the central nervous system (CNS) (primary central nervous system lymphoma [PCNSL]) is an exception because of the low CNS bioavailability of related drugs. NGR-human tumor necrosis factor (NGR-hTNF) targets CD13+ vessels, enhances vascular permeability and CNS access of anticancer drugs, and provides the rationale for the treatment of PCNSL with R-CHOP. Herein, we report activity and safety of R-CHOP preceded by NGR-hTNF in patients with PCNSL relapsed/refractory to high-dose methotrexate-based chemotherapy enrolled in a phase 2 trial. Overall response rate (ORR) was the primary endpoint. A sample size of 28 patients was considered necessary to demonstrate improvement from 30% to 50% ORR. NGR-hTNF/R-CHOP would be declared active if ≥12 responses were recorded. Treatment was well tolerated; there were no cases of unexpected toxicities, dose reductions or interruptions. NGR-hTNF/R-CHOP was active, with confirmed tumor response in 21 patients (75%; 95% confidence interval, 59%-91%), which was complete in 11. Seventeen of the 21 patients with response to treatment received consolidation (ASCT, WBRT, and/or lenalidomide maintenance). At a median follow-up of 21 (range, 14-31) months, 5 patients remained relapse-free and 6 were alive. The activity of NGR-hTNF/R-CHOP is in line with the expression of CD13 in both pericytes and endothelial cells of tumor vessels. High plasma levels of chromogranin A, an NGR-hTNF inhibitor, were associated with proton pump inhibitor use and a lower remission rate, suggesting that these drugs should be avoided during TNF-based therapy. Further research on this innovative approach to CNS lymphomas is warranted. The trial was registered as EudraCT: 2014-001532-11.

Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status.

BACKGROUND: Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied to dynamic susceptibility contrast (DSC)-MRI in classifying treatment-naïve gliomas from a multi-center patients into WHO grades II-IV and across their isocitrate dehydrogenase (IDH) mutation status. METHODS: Three hundred thirty-three patients from 6 tertiary centres, diagnosed histologically and molecularly with primary gliomas (IDH-mutant = 151 or IDH-wildtype = 182) were retrospectively identified. Raw DSC-MRI data was post-processed for normalised leakage-corrected relative cerebral blood volume (rCBV) maps. Shape, intensity distribution (histogram) and rotational invariant Haralick texture features over the tumour mask were extracted. Differences in extracted features across glioma grades and mutation status were tested using the Wilcoxon two-sample test. A random-forest algorithm was employed (2-fold cross-validation, 250 repeats) to predict grades or mutation status using the extracted features. RESULTS: Shape, distribution and texture features showed significant differences across mutation status. WHO grade II-III differentiation was mostly driven by shape features while texture and intensity feature were more relevant for the III-IV separation. Increased number of features became significant when differentiating grades further apart from one another. Gliomas were correctly stratified by mutation status in 71% and by grade in 53% of the cases (87% of the gliomas grades predicted with distance less than 1). CONCLUSIONS: Despite large heterogeneity in the multi-center dataset, machine learning assisted DSC-MRI radiomics hold potential to address the inherent variability and presents a promising approach for non-invasive glioma molecular subtyping and grading.

Hypoxia and Amino Acid Imaging of High-Grade Glioma: 18F-FAZA PET/CT and 11C-Methionine PET/MRI.

In the present case, we report the first experience of a patient with high-grade glioma who underwent dual F-FAZA PET/CT imaging for intratumoral hypoxia assessment, before treatment, and for therapy monitoring in the suspicious of recurrence, as part of a clinical research protocol. In addition, despite the diagnosis of glioblastoma, the patient at 3 years from diagnosis was alive and underwent C-methionine simultaneous PET/MRI for disease monitoring after treatment, showing stability of disease. The multitracer capability of PET in assessing different and complementary metabolic features along with the use of a last-generation scanner as PET/MRI in brain oncology are here enlighten.

Dose Finding Study of Gadopiclenol, a New Macrocyclic Contrast Agent, in MRI of Central Nervous System.

OBJECTIVES: The aim of this study was to determine a safe and effective dose of gadopiclenol, a new high relaxivity macrocyclic gadolinium-based contrast agent. Based on the contrast-to-noise ratio (CNR) as primary criterion, this new agent was compared with gadobenate dimeglumine in patients with contrast-enhancing central nervous system lesions. METHODS AND MATERIALS: This phase IIb international, multicenter, double-blind, randomized, controlled, parallel dose groups, and cross-over study included adult patients with known or highly suspected lesions with disrupted blood-brain barrier. Patients were randomized to 1 of 4 doses of gadopiclenol (0.025, 0.05, 0.1, 0.2 mmol/kg) and to 1 series of 2 magnetic resonance imaging scans: gadopiclenol then gadobenate dimeglumine at 0.1 mmol/kg or vice versa. The qualitative and quantitative efficacy evaluations were performed by 3 independent off-site blinded readers. Adverse events were monitored up to 1 day after second magnetic resonance imaging. RESULTS: The study population included 272 patients (58.5% females) with a mean (SD) age of 53.8 (13.6) years. The superiority of gadopiclenol over gadobenate dimeglumine was statistically demonstrated at 0.2 and 0.1 mmol/kg for all readers with an increase in CNR of more than 30% (P ≤ 0.0007). At 0.05 mmol/kg, gadopiclenol showed a CNR of similar magnitude as gadobenate dimeglumine at 0.1 mmol/kg, with no statistically significant difference. Similar results were obtained for lesion-to-brain ratio and contrast enhancement percentage, as secondary criteria. The relationship between CNR and dose of gadopiclenol was linear for all readers. Mean scores for lesion visualization variables, particularly lesion contrast enhancement, tended to be higher with gadopiclenol at 0.1 and 0.2 mmol/kg compared with gadobenate dimeglumine. All 3 readers mainly expressed an overall diagnostic preference for images with gadopiclenol at 0.1 mmol/kg (45.3%, 50.9%, or 86.8% of images) or expressed no preference (49.1%, 49.1%, or 9.4%, respectively), whereas preference for images with gadobenate dimeglumine was reported by 2 readers for 3.8% and 5.7% of the images. Predominantly, no preference was expressed when comparing images with gadopiclenol at 0.05 mmol/kg to those with gadobenate dimeglumine.Rates of adverse reactions were comparable for gadopiclenol (11.7%) and gadobenate dimeglumine (12.1%). Changes from baseline of more than 25% in serum creatinine and estimated glomerular filtration rate occurred in less than 2% of patients equally for gadopiclenol and gadobenate dimeglumine. Changes from baseline for the values of blood urea nitrogen and cystatin C were also similar between gadopiclenol and gadobenate dimeglumine. No safety concerns were detected on centralized electrocardiography readings. CONCLUSIONS: Between the doses of 0.025 and 0.2 mmol/kg of gadopiclenol, the increase in CNR is linear. Compared with gadobenate dimeglumine at 0.1 mmol/kg, the doses of 0.05 and 0.1 mmol/kg of gadopiclenol gave similar or significantly greater contrast enhancement, respectively, and thus both doses can be considered for future phase III studies.