Background And Purpose: Dynamic susceptibility contrast-enhanced (DSC) MR perfusion is a valuable technique for distinguishing brain tumors. Diagnostic potential of measurable parameters derived from preload leakage-corrected-DSC-MRI remains somewhat underexplored. This study aimed to evaluate these parameters for differentiating primary CNS lymphoma (PCNSL), glioblastoma, and metastasis.
Methods: Thirty-nine patients with pathologically proven PCNSL (n = 14), glioblastoma (n = 14), and metastasis (n = 11) were analyzed. Five DSC parameters-relative CBV (rCBV), percentage of signal recovery (PSR), downward slope (DS), upward slope (US), and first-pass slope ratio-were derived from tumor-enhancing areas. Diagnostic performance was assessed using receiver operating characteristic curve analysis.
Results: RCBV was higher in metastasis (4.58; interquartile range [IQR]: 2.54) and glioblastoma (3.98; IQR: 1.87), compared with PCNSL (1.46; IQR: 0.29; p = .00006 for both). rCBV better distinguished metastasis and glioblastoma from PCNSL, with an area under the curve (AUC) of 0.97 and 0.99, respectively. PSR was higher in PCNSL (88.11; IQR: 21.21) than metastases (58.30; IQR: 22.28; p = .0002), while glioblastoma (74.54; IQR: 21.23) presented almost significant trend-level differences compared to the others (p≈.05). AUCs were 0.79 (PCNSL vs. glioblastoma), 0.91 (PCNSL vs. metastasis), and 0.78 (glioblastoma vs. metastasis). DS and US parameters were statistically significant between glioblastoma (-109.92; IQR: 152.71 and 59.06; IQR: 52.87) and PCNSL (-47.36; IQR: 44.30 and 21.68; IQR: 16.85), presenting AUCs of 0.86 and 0.87.
Conclusion: Metastasis and glioblastoma can be better differentiated from PCNSL through rCBV. PSR demonstrated higher differential performance compared to the other parameters and seemed useful, allowing a proper distinction among all, particularly between metastasis and glioblastoma, where rCBV failed. Finally, DS and US were only helpful in differentiating glioblastoma from PCNSL.
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http://dx.doi.org/10.1111/jon.13183 | DOI Listing |
Cureus
October 2024
Internal Medicine, Upstate University Hospital, Syracuse, USA.
The rare diffuse B-cell lymphoma subtype of primary central nervous system lymphomas (PCNSL) typically presents with nonspecific symptoms. Many of these symptoms overlap with those reported in cases of glioblastoma multiforme (GBM). However, despite the overlap in symptomatology, the two CNS tumors exhibit distinctly different imaging findings on MRI, which aids in diagnosis.
View Article and Find Full Text PDFActa Neurol Belg
September 2024
Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan.
Indian J Nucl Med
August 2024
Department of Nuclear Medicine, Sri Venkateswara Institute of Medical Sciences, Tirupati, Andhra Pradesh, India.
Primary central nervous system lymphoma (PCNSL) is a rare, aggressive variant of extranodal non-Hodgkin's lymphoma. Although gadolinium-enhanced magnetic resonance imaging remains the initial imaging modality of choice, a whole-body F-18 fluorodeoxyglucose (FDG) positron emission tomography-computed tomography is imperative to exclude systemic lymphomatous involvement. Furthermore, the metabolic parameter, maximum standardized uptake value (SUV) of the lesion, tumor-to-normal cerebral tissue SUV ratio, and FDG uptake patterns help in differentiating intracranial lymphomas from High-grade Glioblastoma Multiforme (HGM) and infectious lesions, and hence, consolidating the diagnosis.
View Article and Find Full Text PDFAJNR Am J Neuroradiol
September 2024
From the UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, and Department of Radiological Sciences, (F.S., J.Y., N.S.C., C.R., B.M.E.), Department of Neurosurgery (R.G.E., B.M.E.), Department of Neurology (T.F.C.), Department of Radiological Sciences (W.B.P., N.S.), Department of Psychiatry and Biobehavioral Sciences (B.M.E.), Medical Scientist Training Program (N.S.C.), David Geffen School of Medicine, Department of Bioengineering, Henry Samueli School of Engineering and Applied Science (N.S.C., B.M.E.), Department of Biostatistics (D.T.), University of California Los Angeles, Los Angeles, CA, USA; from the Department of Diagnostic Imaging (J.L.B.), Warren Alpert Medical School, Brown University, Providence, RI, USA.
Background And Purpose: Normalized relative cerebral blood volume (nrCBV) and percentage of signal recovery (PSR) computed from dynamic susceptibility contrast (DSC) perfusion imaging are useful biomarkers for differential diagnosis and treatment response assessment in brain tumors. However, their measurements are dependent on DSC acquisition factors, and CBV-optimized protocols technically differ from PSR-optimized protocols. This study aimed to generate "synthetic" DSC data with adjustable synthetic acquisition parameters using dual-echo gradient-echo (GE) DSC datasets extracted from dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI).
View Article and Find Full Text PDFNeuroradiology
November 2024
Laboratory for Medical Imaging Informatics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, 200083, China.
Objective: Research into the effectiveness and applicability of deep learning, radiomics, and their integrated models based on Magnetic Resonance Imaging (MRI) for preoperative differentiation between Primary Central Nervous System Lymphoma (PCNSL) and Glioblastoma (GBM), along with an exploration of the interpretability of these models.
Materials And Methods: A retrospective analysis was performed on MRI images and clinical data from 261 patients across two medical centers. The data were split into a training set (n = 153, medical center 1) and an external test set (n = 108, medical center 2).
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