Percentage signal intensity recovery: A step ahead of rCBV in DSC MR perfusion imaging for the differentiation of common neoplasms of brain

The Utility of Multiparametric Magnetic Resonance Imaging in Reducing Diagnostic Uncertainty for Primary Central Nervous System Lymphoma

BACKGROUND

A key limitation in treatment initiation in primary central nervous system lymphoma (PCNSL) is the diagnostic delay caused by lack of recognition of a lesion as a possible lymphoma, steroid initiation, and lesion involution, often resulting in an inconclusive biopsy result. We highlight the importance of multiparametric magnetic resonance imaging (MRI), which incorporates diffusion-weighted imaging, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and proton magnetic resonance spectroscopy in addition to standard MRI sequences in resolving diagnostic uncertainty for PCNSL.

METHODS

At our center, a consecutive series of 10 patients with histology-proven PCNSL (specifically, diffuse large B-cell lymphoma of the central nervous system) underwent multiparametric MRI. We retrospectively analyzed qualitative and semiquantitative parameters and assessed their radiological concordance for this diagnosis.

RESULTS

We noted overall low apparent diffusion coefficient on diffusion-weighted imaging (mean minimum apparent diffusion coefficient of 0.74), high percentage signal recovery on perfusion-weighted imaging (mean 170%), a high choline-to-creatine ratio, and a high-grade lipid peak on proton magnetic resonance spectroscopy giving an appearance of twin towers. Of 10 patients, 9 had MRI findings concordant for PCNSL, defined as at least 3 of 4 parameters being consistent for PCNSL.

CONCLUSIONS

Concordance between these imaging multiparametric modalities could be used as a radiological predictor of PCNSL, reducing diagnostic delays, providing a more accurate biopsy target, and resulting in quicker treatment initiation.

Differentiation Between High-Grade Glioma and Brain Metastasis Using Cerebral Perfusion-Related Parameters (Cerebral Blood Volume and Cerebral Blood Flow): A Systematic Review and Meta-Analysis of Perfusion-weighted MRI Techniques

BACKGROUND

Distinguishing high-grade gliomas (HGGs) from brain metastases (BMs) using perfusion-weighted imaging (PWI) remains challenging. PWI offers quantitative measurements of cerebral blood flow (CBF) and cerebral blood volume (CBV), but optimal PWI parameters for differentiation are unclear.

PURPOSE

To compare CBF and CBV derived from PWIs in HGGs and BMs, and to identify the most effective PWI parameters and techniques for differentiation.

STUDY TYPE

Systematic review and meta-analysis.

POPULATION

Twenty-four studies compared CBF and CBV between HGGs (n = 704) and BMs (n = 488).

FIELD STRENGTH/SEQUENCE

Arterial spin labeling (ASL), dynamic susceptibility contrast (DSC), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast-enhanced (DSCE) sequences at 1.5 T and 3.0 T.

ASSESSMENT

Following the PRISMA guidelines, four major databases were searched from 2000 to 2024 for studies evaluating CBF or CBV using PWI in HGGs and BMs.

STATISTICAL TESTS

Standardized mean difference (SMD) with 95% CIs was used. Risk of bias (ROB) and publication bias were assessed, and I2 statistic was used to assess statistical heterogeneity. A P-value<0.05 was considered significant.

RESULTS

HGGs showed a significant modest increase in CBF (SMD = 0.37, 95% CI: 0.05-0.69) and CBV (SMD = 0.26, 95% CI: 0.01-0.51) compared with BMs. Subgroup analysis based on region, sequence, ROB, and field strength for CBF (HGGs: 375 and BMs: 222) and CBV (HGGs: 493 and BMs: 378) values were conducted. ASL showed a considerable moderate increase (50% overlapping CI) in CBF for HGGs compared with BMs. However, no significant difference was found between ASL and DSC (P = 0.08).

DATA CONCLUSION

ASL-derived CBF may be more useful than DSC-derived CBF in differentiating HGGs from BMs. This suggests that ASL may be used as an alternative to DSC when contrast medium is contraindicated or when intravenous injection is not feasible.

LEVEL OF EVIDENCE: 1

TECHNICAL EFFICACY

Stage 2.

Primary central nervous system lymphoma: Imaging features and differential diagnosis

Primary central nervous system lymphoma (PCNSL) represents 5% of malignant primary brain tumors. The clinical presentation typically includes focal neurological symptoms, increased intracranial pressure, seizures, and psychiatric symptoms. Although histological examination remains the gold standard for diagnostic confirmation, non-invasive imaging plays a crucial role for the diagnosis. In immunocompetent individuals, PCNSL usually appears as a single, well-defined, supratentorial lesion with a predilection for periventricular areas, iso- or hypointense on T1- and T2-weighted magnetic resonance imaging, with restricted diffusion, slightly increased perfusion, and homogenous gadolinium-enhancement. Differential diagnoses include high-grade glioma and pseudotumoral demyelinating disease. In immunocompromised patients, PCNSL may present as multiple lesions, with a higher likelihood of hemorrhage and necrosis and less restricted diffusion than immunocompetent individuals. Differential diagnoses include neurotoxoplasmosis, progressive multifocal leukoencephalopathy, and cerebral abscess. Atypical forms of lymphoma are characterized by extra-axial lymphoma, lymphomatosis cerebri, and intravascular lymphoma. Extra-axial lymphoma presents as single or multiple extra-axial dural lesions with diffuse leptomeningeal contrast-enhancement. Lymphomatosis cerebri appears as an infiltrative and symmetric lesion, primarily affecting deep white matter and basal ganglia, appearing hyperintense on T2-weighted imaging, without significant contrast-enhancement or perfusion changes. Intravascular lymphoma presents as multiple rounded or oval-shaped "infarct-like" lesions, located cortically or subcortically. This study aims to highlight the imaging characteristics of PCNSL, focusing on magnetic resonance imaging and its differential diagnosis.

An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI

Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, a definitive diagnosis often requires neurosurgical interventions that compromise patients' quality of life. We apply deep learning on DSC images from histology-confirmed patients with glioblastoma, metastasis, or lymphoma. The convolutional neural network trained on ∼50,000 voxels from 40 patients provides intratumor probability maps that yield clinical-grade diagnosis. Performance is tested in 400 additional cases and an external validation cohort of 128 patients. The tool reaches a three-way accuracy of 0.78, superior to the conventional MRI metrics cerebral blood volume (0.55) and percentage of signal recovery (0.59), showing high value as a support diagnostic tool. Our open-access software, Diagnosis In Susceptibility Contrast Enhancing Regions for Neuro-oncology (DISCERN), demonstrates its potential in aiding medical decisions for brain tumor diagnosis using standard-of-care MRI.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences

Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.