Differentiating primary CNS lymphoma from glioblastoma multiforme: assessment using arterial spin labeling, diffusion-weighted imaging, and ¹⁸F-fluorodeoxyglucose positron emission tomography

Comparative evaluation of 11C-methionine and 18F-fluorodeoxyglucose positron emission tomography for distinguishing between primary central nervous system lymphoma and isocitrate dehydrogenase-wildtype glioblastoma

PURPOSE

Distinguishing between primary central nervous system lymphoma (PCNSL) and isocitrate dehydrogenase (IDH)-wildtype glioblastoma is important for therapeutic decision-making. This study aimed to compare the performance of 11C-methionine (MET) and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for distinguishing between these two major malignant brain tumors.

METHODS

We retrospectively conducted qualitative and semiquantitative analyses of pre-treatment MET and FDG PET/computed tomography (CT) images of 22 patients with PCNSL and 64 patients with IDH-wildtype glioblastoma. For semiquantitative analysis, we calculated the tumor-to-normal tissue (T/N) ratio by dividing the maximum standardized uptake value (SUV) for the tumor (T) by the average SUV for the normal tissue (N). For performance evaluation, we employed receiver operating characteristic curve analysis and calculated the areas under the curve (AUC) values.

RESULTS

In the qualitative analysis, all PCNSLs and IDH-wildtype glioblastomas were MET-positive, while 95% and 84% of PCNSLs and IDH-wildtype glioblastomas, respectively, were FDG-positive. Eleven patients were excluded from the FDG PET/CT semiquantitative analysis because of hyperglycemia. There was no difference in MET T/N ratio between PCNSL and IDH-wildtype glioblastoma (p = 0.37). FDG T/N ratio was significantly higher in PCNSL than in IDH-wildtype glioblastoma (p < 0.001). The AUC value for distinguishing PCNSL from IDH-wildtype glioblastoma was significantly higher for the FDG T/N ratio (0.871) than for the MET T/N ratio (0.565) (p = 0.0027).

CONCLUSION

MET PET could detect both PCNSL and IDH-wildtype glioblastoma, but unlike FDG PET, it could not distinguish between these two major malignant brain tumors.

Clinical Value of a Nomogram Model Based on Apparent Diffusion Coefficient Values Within 1 cm of the Tumor Cavity to Predict Postoperative Progression of Glioma

OBJECTIVE

To explore the clinical value of constructing a nomogram model based on apparent diffusion coefficient values within 1 cm of the residual tumor cavity to predict the postoperative progression of gliomas.

METHODS

Clinical data of patients with glioma who underwent surgery were retrospectively retrieved from the First Hospital of Qinhuangdao. The mean apparent diffusion coefficient (mADC) was measured using a picture archiving and communication system. The Kaplan-Meier survival curve was constructed with the optimal mADC threshold determined by the X-tile. A nomogram was developed based on the independent risk factors determined using the Cox proportional hazards model (Cox regression model) to predict the progression of postoperative glioma. A receiver operating characteristic curve was drawn to evaluate the prediction accuracy of the model, and decision curve analysis was performed to assess the clinical value of the nomogram.

RESULTS

There was good agreement between the mADC values of the 2 repeated measurements before and after, with a consistency correlation coefficient of 0.83. Multivariate Cox regression analysis showed that peritumoral mADC values, degree of peritumoral enhancement, age, pathological grading, and degree of tumor resection were independent risk factors for predicting postoperative progression of glioma (all P < 0.05). The receiver operating characteristic curves of the nomogram predicting 1, 2, and 3 years postoperative progression were 0.86, 0.82, and 0.91, respectively. The calibration curve showed good consistency between the observed and predicted values in the model. The curve showed that the nomogram model has a good clinical application value.

CONCLUSIONS

The peritumoral mADC values, degree of peritumoral enhancement, age, pathological grade, and degree of tumor resection were independent factors affecting the postoperative progression of glioma. The nomogram model established for the first time based on mADC values within 1 cm of the tumor can predict the postoperative condition of patients with glioma intuitively and comprehensively. It can provide a relatively accurate prediction tool for neurosurgeons to individualize the evaluation of survival and prognosis, and formulate treatment plans for patients.

Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient

BACKGROUND

This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters.

METHODS

A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices.

RESULTS

In enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs.

CONCLUSIONS

Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.

Differentiation of glioblastoma and primary central nervous system lymphomas using multiparametric diffusion and perfusion magnetic resonance imaging

The present study aimed to determine whether combining diffusion-weighted (DWI) and dynamic susceptibility contrast-enhanced perfusion-weighted (DSC-PWI) magnetic resonance imaging (MRI) could differentiate between primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM). The present retrospective study evaluated 45 patients with histologically confirmed brain tumors, of which 18 had PCNSLs and 27 had GBMs. All patients underwent conventional, DWI, and DSC-PWI MRIs before the surgical removal of the lesion or stereotactic biopsy. The solid tumor component, peritumoral edema, and abnormal white matter were measured in three regions of interest to evaluate relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and DWI. In conventional MRI, there were significant differences in tumor numbers, tumor enhancement type, tumor necrosis, hemorrhage and open-ring sign between GBM and PCNSL. Solid tumor ADC and rCBV values (ADCt and rCBVt, respectively) and their ratios with abnormal white matter amounts were significantly higher in GBM cases than in PCNSL cases (P<0.05). The rCBV value for peritumoral edema (rCBVe) and its ratio with abnormal white matter amount (rCBVe/n) were significantly higher in GBM cases than in PCNSL cases (P<0.05). However, ADC values did not differ significantly for peritumoral edema. DWI values did not differ significantly. Combining rCBVt and rCBVe/n provided a perfect area under the receiver operating characteristic curve of 1.00, with 100% sensitivity and 100% specificity for distinguishing GBM from PCNSL. In the results of the present study, the major criterion in the decision-making process distinguishing PCNSL from GBM was the combined rCBVt and rCBVe/n parameter. A minor criterion was the ADCt value of the lesion.

Atypical primary central nervous system lymphoma and glioblastoma: multiparametric differentiation based on non-enhancing volume, apparent diffusion coefficient, and arterial spin labeling

OBJECTIVES

To evaluate the multiparametric diagnostic performance with non-enhancing tumor volume, apparent diffusion coefficient (ADC), and arterial spin labeling (ASL) to differentiate between atypical primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM).

METHODS

One hundred and fifty-eight patients with pathologically confirmed typical PCNSL (n = 59), atypical PCNSL (hemorrhage, necrosis, or heterogeneous contrast enhancement, n = 29), and GBM (n = 70) were selected. Relative minimum ADC (rADCmin), mean (rADCmean), maximum (rADCmax), and rADCmax-min (rADCdif) were obtained by standardization of the contralateral white matter. Maximum cerebral blood flow (CBFmax) was obtained according to the ASL-CBF map. The regions of interests (ROIs) were manually delineated on the inner side of the tumor to further generate a 3D-ROI and obtain the non-enhancing tumor (nET) volume. The area under the curve (AUC) was used to evaluate the diagnostic performance.

RESULTS

Atypical PCNSLs showed significantly lower rADCmax, rADCmean, and rADCdif than that of GBMs. GBMs showed significantly higher CBFmax and nET volume ratios than that of atypical PCNSLs. Combined three-variable models with rADCmean, CBFmax, and nET volume ratio were superior to one- and two-variable models. The AUC of the three-variable model was 0.96, and the sensitivity and specificity were 90% and 96.55%, respectively.

CONCLUSION

The combined evaluation of rADCmean, CBFmax, and nET volume allowed for reliable differentiation between atypical PCNSL and GBM.

KEY POINTS

• Atypical PCNSL is easily misdiagnosed as glioblastoma, which leads to unnecessary surgical resection. • The nET volume, ADC, and ASL-derived parameter (CBF) were lower for atypical PCNSL than that for glioblastoma. • The combination of multiple parameters performed well (AUC = 0.96) in the discrimination between atypical PCNSL and glioblastoma.

Combining amide proton transfer-weighted and arterial spin labeling imaging to differentiate solitary brain metastases from glioblastomas

PURPOSE

To evaluate the clinical utility of amide proton transfer-weighted imaging (APTw) and arterial spin labeling (ASL) in differentiating solitary brain metastases (SBMs) from glioblastomas (GBMs).

METHODS

Forty-eight patients diagnosed with brain tumors were enrolled. All patients underwent conventional MRI, APTw, and ASL scans on a 3.0 T MRI system. The mean APTw value and mean cerebral blood flow (CBF) value were measured. The differences in various parameters between GBMs and SBMs were assessed using the independent-samples t-test. The quantitative performance of these MRI parameters in distinguishing between GBMs and SBMs was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

GBMs exhibited significantly higher APTw and CBF values in peritumoral regions compared with SBMs (P < 0.05). There was no significant difference between SBMs and GBMs in tumor cores. APTw MRI had a higher diagnostic efficiency in differentiating SBMs from GBMs (area under the curve [AUC]: 0.864; 75.0% sensitivity and 81.8% specificity). Combined use of APTw and CBF value increased the AUC to 0.927.

CONCLUSION

APTw may be superior to ASL for distinguishing between SBMs and GBMs. Combination of APTw and ASL showed better discrimination and a superior diagnostic performance.

Arterial spin labeling clinical applications for brain tumors and tumor treatment complications: A comprehensive case-based review

Arterial spin labeling (ASL) is a noninvasive neuroimaging technique that allows for quantifying cerebral blood flow without intravenous contrast. Various neurovascular disorders and tumors have cerebral blood flow alterations. Identifying these perfusion changes through ASL can aid in the diagnosis, especially in entities with normal structural imaging. In addition, complications of tumor treatment and tumor progression can also be monitored using ASL. In this case-based review, we demonstrate the clinical applications of ASL in diagnosing and monitoring brain tumors and treatment complications.

Contribution of nuclear medicine to the diagnosis and management of primary brain tumours

Positron emission tomography (PET) is a powerful tool that can help physicians manage primary brain tumours at diagnosis and follow-up. In this context, PET imaging is used with three main types of radiotracers: ¹⁸F-FDG, amino acid radiotracers, and ⁶⁸Ga conjugated to somatostatin receptor ligands (SSTRs). At initial diagnosis, ¹⁸F-FDG helps to characterize primary central nervous system (PCNS) lymphomas and high-grade gliomas, amino acid radiotracers are indicated for gliomas, and SSTR PET ligands are indicated for meningiomas. Such radiotracers provide information on tumour grade or type, assist in directing biopsies and help with treatment planning. During follow-up, in the presence of symptoms and/or MRI modifications, the differential diagnosis between tumour recurrence and post-therapeutic changes, in particular radiation necrosis, may be challenging, and there is strong interest in using PET to evaluate therapeutic toxicity. PET may also contribute to identifying specific complications, such as postradiation therapy encephalopathy, encephalitis associated with PCNS lymphoma, and stroke-like migraine after radiation therapy (SMART) syndrome associated with glioma recurrence and temporal epilepsy, originally illustrated in this review. This review summarizes the main contribution of PET to the diagnosis, management, and follow-up of brain tumours, specifically gliomas, meningiomas, and primary central nervous system lymphomas.

Lymphomas of Central Nervous System

Central nervous system (CNS) lymphoma consists of primary central nervous system lymphoma (PCNSL) and secondary CNS involvement by systemic lymphoma. This chapter focuses on the former. PCNSL is a relative rare disease, accounting for approximately 2.4-4.9% of all primary CNS tumors. It is an extra-nodal variant of non-Hodgkin's lymphoma (NHL), confined to the brain, leptomeninges, spinal cord, and eyes, with no systemic involvement. Recently, elderly patients (≥ 60 years) are increasing. Histologically, B cell blasts, which originate from late germinal center exit B cell, are growing and homing in CNS. Immunohistochemically, these cells are positive for PAX5, CD19, CD20, CD22, and CD79a. PCNSL shows relatively characteristic appearances on CT, MR imaging, and PET. Treatment first line of PCNSL is HD-MTX-based chemotherapy with or without rituximab and irradiation. Severe side-effect of this treatment is delayed onset neurotoxicity, which cause of cognitive impairment. Therefore, combined chemotherapy alone or chemotherapy with reduced-dose irradiation is more recommended for elderly patients. There is no established standard care for relapse of the PCNSLs. Temsirolimus, lenalidomide, temozolomide, and Bruton's tyrosine kinase (BTK) inhibitor ibrutinib are candidates for refractory patients. The prognosis of PCNSL has significantly improved over the last decades (median OS: 26 months, 5-year survival: 31%). Younger than 60 age and WHO performance status less than < or = 1 are associated with a significantly better overall survival.

Role of Positron Emission Tomography in Primary Central Nervous System Lymphoma

Simple Summary

Primary central nervous system lymphoma (PCNSL) is a rare but highly aggressive lymphoma with increasing incidence in immunocompetent patients. To date, the only established biomarkers for survival are age and functional status. Currently, the magnetic resonance imaging (MRI) criteria of the International Collaborative Group on Primary Central Nervous System Lymphoma are the only ones recommended for follow-up. However, early occurrence of recurrence after treatment in patients with a complete response on MRI raises the question of its performance in assessing residual disease. While the use of ¹⁸F-fluorodeoxyglucose body positron emission tomography for identification of systemic disease has been established and can be pivotal in patient treatment decisions, the role of brain PET scan is less clear. Here we review the potential role of PET in the management of patients with PCNSL, both at diagnosis and for follow-up under treatment.

Abstract

The incidence of primary central nervous system lymphoma has increased over the past two decades in immunocompetent patients and the prognosis remains poor. A diagnosis and complete evaluation of the patient is needed without delay, but histologic evaluation is not always available and PCNSL can mimic a variety of brain lesions on MRI. In this article, we review the potential role of ¹⁸F-FDG PET for the diagnosis of PCNSL in immunocompetent and immunocompromised patients. Its contribution to systemic assessment at the time of diagnosis has been well established by expert societies over the past decade. In addition, ¹⁸F-FDG provides valuable information for differential diagnosis and outcome prediction. The literature also shows the potential role of ¹⁸F-FDG as a therapeutic evaluation tool during the treatment and the end of the treatment. Finally, we present several new radiotracers that may have a potential role in the management of PCNSL in the future.

Use of 18F-FDG-PET/CT in differential diagnosis of primary central nervous system lymphoma and high-grade gliomas: A meta-analysis

Background

Primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) appear similar under imaging. However, since the two tumors vary in their treatment methods, their differential diagnosis is crucial. The use of 18F-fluorodeoxyglucose positron emission tomography computed tomography (18F-FDG-PET/CT) imaging to effectively distinguish between the two tumors is not clear; therefore, a meta-analysis was carried out to determine its effectiveness.

Materials and methods

The databases PubMed, EMBASE, Cochrane, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, China Science, and Technology Journal Database (CQVIP) were exhaustively searched using stringent inclusion and exclusion criteria to select high-quality literature. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) was used for the qualitative assessment of the included literature. The bivariate effect model was used to combine statistics such as sensitivity (SEN) and specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) [95% confidence intervals (CI)], plot summary receiver operating characteristic (SROC) curve, and calculate the area under the curve (AUC) value. Sensitivity analysis was used to evaluate the stability of the results, and Deek's test was used to assess publication bias. Meta-regression and subgroup analysis was used to determine the sources of heterogeneity.

Results

A total of nine studies were included in this study. For differential diagnosis of PCNSL and HGG, the combined SEN was 0.91 (95% CI: 0.80–0.96; I² = 46.73%), combined SPE was 0.88 (95% CI: 0.82–0.93; I² = 56.30%), the combined PLR was 7.83 (95% CI: 4.96–12.37; I² = 15.57%), combined NLR was 0.10 (95% CI: 0.05–0.23; I² = 31.99%), combined DOR was 77.36 (95% CI: 32.74–182.77; I² = 70.70%). The AUC of SROC was 0.95 (95% CI: 0.93–0.97). No publication bias was found and the sample size and different parameters were the primary reason for heterogeneity.

Conclusion

The 18F-FDG-PET/CT imaging technique has a high diagnostic accuracy in the differential diagnosis of PNCSL and HGG. Patients suspected to have the above two tumors are suggested to be examined by 18F-FDG-PET / CT to help in the clinical distinction and further treatment modalities.

First-in-Man Noninvasive Initial Diagnostic Approach of Primary CNS Lymphoma Versus Glioblastoma Using PET With 18 F-Fludarabine and l -[methyl- 11 C]Methionine

OBJECTIVES

This study sought to assess 18 F-fludarabine ( 18 F-FLUDA) PET/CT's ability in differentiating primary central nervous system lymphomas (PCNSLs) from glioblastoma multiformes (GBMs).

PATIENTS AND METHODS

Patients harboring either PCNSL (n = 8) before any treatment, PCNSL treated using corticosteroids (PCNSLh; n = 10), or GBM (n = 13) were investigated with conventional MRI and PET/CT, using 11 C-MET and 18 F-FLUDA. The main parameters measured with each tracer were SUV T and T/N ratios for the first 30 minutes of 11 C-MET acquisition, as well as at 3 different times after 18 F-FLUDA injection. The early 18 F-FLUDA uptake within the first minute of injection was equally considered, whereas this parameter was combined with the later uptakes to obtain R FLUDA 2 and R FLUDA 3 ratios.

RESULTS

No significant differences in 11 C-MET uptakes were observed among PCNSL, PCNSLh, and GBM. With 18 F-FLUDA, a clear difference in dynamic GBM uptake was observed, which decreased over time after an early maximum, as compared with that of PCNSL, which steadily increased over time, PCNSLh exhibiting intermediate values. The most discriminative parameters consisting of R FLUDA 2 and R FLUDA 3 integrated the early tracer uptake (first 60 seconds), thereby provided 100% specificity and sensitivity.

CONCLUSIONS

18 F-FLUDA was shown to likely be a promising radiopharmaceutical for differentiating PCNSL from other malignancies, although a pretreatment with corticosteroids might compromise this differential diagnostic ability. The diagnostic role of 18 F-FLUDA should be further investigating, along with its potential of defining therapeutic strategies in patients with PCNSL, while assessing the treatments' effectiveness.

Usefulness of dual isotope 123I-IMP and 201Tl SPECT for the diagnosis of primary central nervous system lymphoma and glioblastoma

BACKGROUND

Preoperative differential diagnosis between primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is important because these tumors require different surgical strategies. This study investigated the usefulness of dual isotope, iodine-123-labeled N-isopropyl-p-iodo-amphetamine (¹²³I-IMP) and thallium-201 chloride single-photon emission computed tomography (²⁰¹Tl SPECT) for the differential diagnosis.

METHODS

Twenty-five PCNSL patients and 27 GBM patients who underwent dual isotope imaging, ¹²³I-IMP and ²⁰¹Tl SPECT, are included. Tumor-to-normal (T/N) ratio was calculated from the ratio of maximum tracer counts in the lesion to the mean counts in the contralateral cerebral cortex. The mean and minimum apparent diffusion coefficient values (ADC_mean and ADC_min, respectively) on magnetic resonance imaging were also analyzed.

RESULTS

Delayed phase ¹²³I-IMP SPECT was the most useful imaging examination for the differentiation between PCNSL and GBM compared with early phase ¹²³I-IMP SPECT, early and delayed phase ²⁰¹Tl SPECT, ADC_mean, and ADC_min. However, the median T/N ratios of PCNSL and GBM were 1.32 and 0.83, respectively, in the delayed phase ¹²³I-IMP SPECT. On the other hand, the median T/N ratios of PCNSL and GBM were 3.10 and 2.34, respectively, in the delayed phase ²⁰¹Tl SPECT, with excellent tumor detection.

CONCLUSION

Delayed phase ¹²³I-IMP SPECT could differentiate between PCNSL and GBM with high accuracy, but T/N ratio was low and tumor detection was poor. ²⁰¹Tl SPECT was useful for estimation of the malignancy and localization of the tumors with high T/N ratio. Dual isotope ¹²³I-IMP and ²⁰¹Tl SPECT was useful for the preoperative diagnosis of PCNSL and GBM.

Diagnostic Accuracy of the Diffusion-Weighted Imaging Method Used in Association With the Apparent Diffusion Coefficient for Differentiating Between Primary Central Nervous System Lymphoma and High-Grade Glioma: Systematic Review and Meta-Analysis

Background

It is difficult to differentiate between a few primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) using conventional magnetic resonance imaging techniques. The purpose of this study is to explore whether diffusion-weighted imaging (DWI) can be effectively used to differentiate between these two types of tumors by analyzing the apparent diffusion coefficient (ADC).

Research Design and Methods

Data presented in Pubmed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, and China Science and Technology Journal Database (CQVIP) were analyzed. High-quality literature was included, and the quality was evaluated using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) tool, and the studies were based on the inclusion and exclusion rules. The pooled sensitivity, pooled specificity, pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (DOR), area under the curve (AUC) of the summary operating characteristic curve (SROC), and corresponding 95% confidence interval (CI) were calculated using the bivariate mixed effect model. Meta-regression analysis and subgroup analysis were used to explore the sources of heterogeneity. The publication bias was evaluated by conducting Deek's test.

Results

In total, eighteen high-quality studies were included. The pooled sensitivity was 0.82 (95% CI: 0.75–0.88), the pooled specificity was 0.87 (95% CI: 0.84–0.90), the pooled positive likelihood ratio was 6.49 (95% CI: 5.06–8.32), the pooled NLR was 0.21 (95% CI: 0.14–0.30), the pooled DOR was 31.31 (95% CI: 18.55–52.86), and the pooled AUC was 0.90 (95% CI: 0.87–0.92). Sample size, language and country of publication, magnetic field strength, region of interest (ROI), and cut-off values of different types of ADC can potentially be the sources of heterogeneity. There was no publication bias in this meta-analysis.

Conclusions

The results obtained from the meta-analysis suggest that DWI is characterized by high diagnostic accuracy and thus can be effectively used for differentiating between PCNSL and HGG.

PET-CT in Clinical Adult Oncology-V. Head and Neck and Neuro Oncology

Simple Summary

Positron emission tomography (PET), typically combined with computed tomography (CT) has become a critical advanced imaging technique in oncology. With PET-CT, a radioactive molecule (radiotracer) is injected in the bloodstream and localizes to sites of tumor because of specific cellular features of the tumor that accumulate the targeting radiotracer. The CT scan, performed at the same time, provides information to facilitate attenuation correction, so that radioactivity from deep or dense structures can be better visualized, but with head and neck malignancies it is critical to provide correlating detailed anatomic imaging. PET-CT has a variety of applications in oncology, including staging, therapeutic response assessment, restaging, and surveillance. This series of six review articles provides an overview of the value, applications, and imaging and interpretive strategies of PET-CT in the more common adult malignancies. The fifth report in this series provides a review of PET-CT imaging in head and neck and neuro oncology.

Abstract

PET-CT is an advanced imaging modality with many oncologic applications, including staging, assessment of response to therapy, restaging, and longitudinal surveillance for recurrence. The goal of this series of six review articles is to provide practical information to providers and imaging professionals regarding the best use of PET-CT for specific oncologic indications, and the potential pitfalls and nuances that characterize these applications. In addition, key tumor-specific clinical information and representative PET-CT images are provided to outline the role that PET-CT plays in the management of oncology patients. Hundreds of different types of tumors exist, both pediatric and adult. A discussion of the role of FDG PET for all of these is beyond the scope of this review. Rather, this series of articles focuses on the most common adult malignancies that may be encountered in clinical practice. It also focuses on FDA-approved and clinically available radiopharmaceuticals, rather than research tracers or those requiring a local cyclotron. The fifth review article in this series focuses on PET-CT imaging in head and neck tumors, as well as brain tumors. Common normal variants, key anatomic features, and benign mimics of these tumors are reviewed. The goal of this review article is to provide the imaging professional with guidance in the interpretation of PET-CT for the more common head and neck malignancies and neuro oncology, and to inform the referring providers so that they can have realistic expectations of the value and limitations of PET-CT for the specific type of tumor being addressed.

Diagnostic accuracy of arterial spin labeling in differentiating between primary central nervous system lymphoma and high-grade glioma: a systematic review and meta-analysis

BACKGROUND

Existing studies have confirmed the accuracy of arterial spin labeling (ASL) in differentiating between primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG). We aimed to consolidate the existing evidence with a meta-analysis.

METHODS

Six literature databases were searched for relevant papers. After assessing the quality of studies, bivariate regression was performed, and the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score, diagnostic odds ratio (DOR), and the area under the curve (AUC) of the summary receiver operating characteristic (SROC) curve were calculated, along with the corresponding 95% confidence intervals (CIs). Deeks' test was used to determine risk of publication bias.

RESULTS

Ten high-quality studies, comprising 151 patients with PCNSL and 455 with HGG, were included. The pooled SEN was 0.79 (95% CI: 0.72-0.85), pooled SPE was 0.90 (95% CI: 0.84-0.94), pooled PLR was 8.07 (95% CI: 5.01-13.02), pooled NLR was 0.23 (95% CI: 0.17-0.32), pooled diagnostic score was 3.56 (95% CI: 2.94-4.18), and pooled DOR was 35.10 (95% CI: 18.83-65.45). The AUC of SROC was 0.86 (95% CI: 0.83-0.89). No publication bias was found.

CONCLUSIONS

ASL demonstrated high diagnostic accuracy in differentiating between PCNSL and HGG.

Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment

BACKGROUND

Differentiating gliomas and primary CNS lymphoma represents a diagnostic challenge with important therapeutic ramifications. Biopsy is the preferred method of diagnosis, while MR imaging in conjunction with machine learning has shown promising results in differentiating these tumors.

PURPOSE

Our aim was to evaluate the quality of reporting and risk of bias, assess data bases with which the machine learning classification algorithms were developed, the algorithms themselves, and their performance.

DATA SOURCES

Ovid EMBASE, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and the Web of Science Core Collection were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

STUDY SELECTION

From 11,727 studies, 23 peer-reviewed studies used machine learning to differentiate primary CNS lymphoma from gliomas in 2276 patients.

DATA ANALYSIS

Characteristics of data sets and machine learning algorithms were extracted. A meta-analysis on a subset of studies was performed. Reporting quality and risk of bias were assessed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) and Prediction Model Study Risk Of Bias Assessment Tool.

DATA SYNTHESIS

The highest area under the receiver operating characteristic curve (0.961) and accuracy (91.2%) in external validation were achieved by logistic regression and support vector machines models using conventional radiomic features. Meta-analysis of machine learning classifiers using these features yielded a mean area under the receiver operating characteristic curve of 0.944 (95% CI, 0.898-0.99). The median TRIPOD score was 51.7%. The risk of bias was high for 16 studies.

LIMITATIONS

Exclusion of abstracts decreased the sensitivity in evaluating all published studies. Meta-analysis had high heterogeneity.

CONCLUSIONS

Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.

Distinguishing between primary central nervous system lymphoma and glioblastoma using [18F]fluoromisonidazole and [18F]FDG PET

OBJECTIVE

The purpose of this study was to assess the diagnostic value of [18F]fluoromisonidazole (FMISO) and 2-deoxy-2-[18F]fluoro-D-glucose (FDG) PET to discriminate primary central nervous system lymphoma (PCNSL) from glioblastoma.

METHODS

FMISO and FDG PET/CT scans before therapy obtained in 13 patients with PCNSL and in 62 patients with glioblastoma were retrospectively reviewed. PET results were evaluated by visual and semiquantitative analysis. For semiquantitative analysis, the maximum standardized uptake value (SUV) for tumor (T) and the mean SUV for normal contralateral hemisphere (N) were calculated, and the tumor-to-normal (T/N) ratio was determined. The performance in discriminating PCNSL and glioblastoma was evaluated using a receiver-operating characteristics analysis. Area-under-the-curve (AUC) values for the discrimination were calculated.

RESULTS

On visual analysis, 54% of PCNSL and 89% of glioblastoma showed positive on FMISO PET. All patients with PCNSL and glioblastoma were FDG positive. FMISO T/N ratio in PCNSL (mean ± SD = 1.80 ± 0.59) was significantly lower than that in glioblastoma (mean ± SD = 2.75 ± 0.84) (P < 0.001). FDG T/N ratio in PCNSL (mean ± SD = 3.01 ± 1.11) was significantly higher than that in glioblastoma (mean ± SD = 1.77 ± 0.79) (P < 0.001). For discrimination of patients with PCNSL from glioblastoma, the AUC values for the FMISO T/N ratio, FDG T/N ratio and combination of the two parameters were 0.833, 0.825 and 0.900, respectively.

CONCLUSION

FMISO PET is as helpful for differentiating PCNSL from glioblastoma as FDG PET.

Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas

Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.

3D pseudo-continuous arterial spin labeling-MRI (3D PCASL-MRI) in the differential diagnosis between glioblastomas and primary central nervous system lymphomas

PURPOSE

The aim of the study was to compare the parameters of blood flow in glioblastomas and primary central nervous system lymphomas (PCNSLs), measured by pseudo-continuous arterial spin labeling MRI (3D PCASL), and to determine the informativeness of this method in the differential diagnosis between these lesions.

METHODS

The study included MRI data of 139 patients with PCNSL (n = 21) and glioblastomas (n = 118), performed in the Burdenko Neurosurgical Center. No patients received chemotherapy, hormone therapy, or radiation therapy prior to MRI. On the 3D PCASL perfusion map, the absolute and normalized values of tumor blood flow were calculated in the glioblastoma and PCNSL groups (maxTBFmean and nTBF).

RESULTS

MaxTBFmean and nTBF in the glioblastoma group were significantly higher than those in the PCNSL group: 168.9 ml/100 g/min versus 65.6 and 9.3 versus 3.7, respectively (p < 0.001). Arterial spin labeling perfusion had high sensitivity (86% for maxTBFmean, 95% for nTBF) and specificity (77% for maxTBFmean, 73% for nTBF) in the differential diagnosis between PCNSL and glioblastomas. Blood flow thresholds were 98.9 ml/100 g/min using absolute blood flow values and 6.1 using normalized values, AUC > 0.88.

CONCLUSION

The inclusion of 3D PCASL in the standard MRI protocol can increase the specificity of the differential diagnosis between glioblastomas and PCNSL.

Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions

Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.

Differentiating between Primary Central Nervous System Lymphoma and Glioblastoma: The Diagnostic Value of Combining 18F-fluorodeoxyglucose Positron Emission Tomography with Arterial Spin Labeling

Using conventional magnetic resonance imaging (MRI) methods, the differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is often difficult due to overlapping imaging characteristics. This study aimed to evaluate the diagnostic value of combining ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET) with arterial spin labeling (ASL) for differentiating PCNSL from GBM. In all, 20 patients with PCNSL and 55 with GBM were retrospectively examined. From the FDG-PET data, the maximum standardized uptake values (SUVmax) and the ratio of tumor to normal contralateral gray matter (T/N_SUVmax) were calculated. From the ASL data, the T/N ratio of the maximum tumor blood flow (relative TBFmax: rTBFmax) was obtained. Diagnostic performance of each parameter was analyzed using univariate and multivariate logistic regression analyses and receiver-operating characteristic (ROC) curve analyses. A generalized linear model was applied for comparing the performance of FDG-PET and ASL individually, and in combination. In univariate analysis, SUVmax and T/N_SUVmax were statistically higher in patients with PCNSL and rTBFmax was higher in patients with GBM. In the multivariate analysis, T/N_SUVmax and rTBFmax were statistically independent. The sensitivity, specificity, and area under the curve (AUC) for discriminating PCNSL from GBM were 100%, 87.3%, and 0.950 in T/N_SUVmax; 90%, 72.7%, and 0.824 in rTBFmax; and 95%, 96.4%, and 0.991 in the combined model, respectively. The combined use of T/N_SUVmax and rTBFmax may contribute to better differentiation between PCNSL and GBM.

Diagnostic Performance of Pretreatment 18F-Fluorodeoxyglucose Positron Emission Tomography With or Without Computed Tomography in Patients With Primary Central Nervous System Lymphoma: Updated Systematic Review and Diagnostic Test Accuracy Meta-analyses

This review aimed to assess diagnostic performance of 18F-flouro-deoxy-glucose positron emission tomography (FDG-PET) with or without computed tomography (CT) scan in primary central nervous system lymphoma (PCNSL). Eligible studies reporting diagnostic accuracy of pretreatment FDG-PET(CT) scan in immunocompetent adults with PCNSL were identified through systematic literature search. Data on diagnostic performance from individual studies was summarized in a 2 × 2 table classifying patients as true positives, true negatives, false positives, and false negatives using histopathologic diagnosis as reference standard. Random-effects model was used to calculate weighted-mean pooled sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic odds ratio with 95% confidence intervals (95% CI). Twenty-nine primary studies involving 967 patients were included. Weighted-mean pooled sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic odds ratio was 87% (95% CI, 83%-90%), 85% (95% CI, 81%-88%), 84% (95% CI, 81%-88%), 87% (95% CI, 84%-90%), and 29.78 (95% CI, 18.34-48.35), respectively, demonstrating acceptably high diagnostic accuracy of pretreatment FDG-PET(CT) scan in immunocompetent patients with PCNSL.

Imaging Inflammation - From Whole Body Imaging to Cellular Resolution

Imaging techniques have evolved impressively lately, allowing whole new concepts like multimodal imaging, personal medicine, theranostic therapies, and molecular imaging to increase general awareness of possiblities of imaging to medicine field. Here, we have collected the selected (3D) imaging modalities and evaluated the recent findings on preclinical and clinical inflammation imaging. The focus has been on the feasibility of imaging to aid in inflammation precision medicine, and the key challenges and opportunities of the imaging modalities are presented. Some examples of the current usage in clinics/close to clinics have been brought out as an example. This review evaluates the future prospects of the imaging technologies for clinical applications in precision medicine from the pre-clinical development point of view.

The Correlation Between Apparent Diffusion Coefficient (ADC) and Relative Cerebral Blood Volume (rCBV) with Ki-67 Expression in Central Nervous System Lymphoma

Background: Central nervous system (CNS) lymphoma presents as the dense infiltration of tumor cells in the perivascular space and blood-brain barrier disruption, on histopathological examination. The Ki-67 expression has been significantly correlated with tumor proliferation and is considered to be a prognostic factor. Objectives: This study aimed at analyzing the correlations among the apparent diffusion coefficient (ADC), the relative cerebral blood volume (rCBV), and the Ki-67 proliferation index in CNS lymphoma. Methods: From August 2019 to March 2020, 26 patients (14 men and 12 women) who underwent biopsy or surgery and were histologically confirmed as CNS lymphoma were included in this retrospective study. Diffusion and perfusion acquisitions were performed in 26 and 10 examinations, respectively. The Ki-67 proliferation index was available for all cases. Results: The mean tADC, rADC, and rCBV values were 0.61 ± 0.12 × 10-3 mm2/s, 0.73 ± 0.14, and 1.1 ± 0.32, respectively. Negative correlations were identified between both tADC and rADC and the Ki-67 proliferation index (r = -0.656, P < 0.01 and r = -0.540, P < 0.01, respectively). No significant correlations were found between rCBV values and the Ki-67 proliferation index, between rCBV and rADC, or between rCBV and tADC. Conclusions: tADC and rADC values can be used as noninvasive indicators to predict cell proliferation in CNS lymphoma.

Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas

The preoperative imaging-based differentiation of primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBs) is of high importance since the therapeutic strategies differ substantially between these tumors. In this study, we investigate whether the gamma distribution (GD) model is useful in this differentiation of PNCSLs and GBs. Twenty-seven patients with PCNSLs and 57 patients with GBs were imaged with diffusion-weighted imaging using 13 b-values ranging from 0 to 1000 sec/mm2. The shape parameter (κ) and scale parameter (θ) were obtained with the GD model. Fractions of three different areas under the probability density function curve (f1, f2, f3) were defined as follows: f1, diffusion coefficient (D) <1.0×10-3 mm2/sec; f2, D >1.0×10-3 and <3.0×10-3 mm2/sec; f3, D >3.0 × 10-3 mm2/sec. The GD model-derived parameters were compared between PCNSLs and GBs. Receiver operating characteristic (ROC) curve analyses were performed to assess diagnostic performance. The correlations with intravoxel incoherent motion (IVIM)-derived parameters were evaluated. The PCNSL group's κ (2.26 ± 1.00) was significantly smaller than the GB group's (3.62 ± 2.01, p = 0.0004). The PCNSL group's f1 (0.542 ± 0.107) was significantly larger than the GB group's (0.348 ± 0.132, p<0.0001). The PCNSL group's f2 (0.372 ± 0.098) was significantly smaller than the GB group's (0.508 ± 0.127, p<0.0001). The PCNSL group's f3 (0.086 ± 0.043) was significantly smaller than the GB group's (0.144 ± 0.062, p<0.0001). The combination of κ, f1, and f3 showed excellent diagnostic performance (area under the curve, 0.909). The f1 had an almost perfect inverse correlation with D. The f2 and f3 had very strong positive correlations with D and f, respectively. The GD model is useful for the differentiation of GBs and PCNSLs.

The application of a gamma distribution model to diffusion-weighted images of the orofacial region

OBJECTIVES

This study evaluated the correlation among the diffusion-derived parameters obtained by monoexponential (ME), intravoxel incoherent motion (IVIM) and γ distribution (GD) models and compared these parameters among representative orofacial tumours.

METHODS

Ninety-two patients who underwent 1.5 T MRI including diffusion-weighted imaging were included. The shape parameter (κ), scale parameter (θ), ratio of the intracellular diffusion (ƒ₁), extracellular diffusion (ƒ₂) and perfusion (ƒ₃) were obtained by the GD model; the true diffusion coefficient (D) and perfusion fraction (f) were obtained by the IVIM model; and the apparent diffusion coefficient (ADC) was obtained by the ME model.

RESULTS

ƒ₁ had a strongly negative correlation with the ADC (ρ = -0.993) and D (ρ = -0.926). A strong positive correlation between f and ƒ₃ (ρ = 0.709) was found. Malignant lymphoma (ML) had the highest ƒ₁, followed by squamous cell carcinoma (SCC), malignant salivary gland tumours, pleomorphic adenoma (Pleo) and angioma. Both the IVIM and GD models suggested the highest perfusion in angioma and the lowest perfusion in ML. The GD model demonstrated a high extracellular component in Pleo and revealed that the T_4a+T_4b SCC group had a lower ƒ₂ than the T₂+T₃ SCC group, and poor to moderately differentiated SCC had a higher ƒ₁ than highly differentiated SCC.

CONCLUSIONS

Given the correlation among the diffusion-derived parameters, the GD model might be a good alternative to the IVIM model. Furthermore, the GD model's parameters were useful for characterizing the pathological structure.

PET Imaging of Tumor Perfusion: A Potential Cancer Biomarker?

Perfusion, as measured by imaging, is considered a standard of care biomarker for the evaluation of many tumors. Measurements of tumor perfusion may be used in a number of ways, including improving the visual detection of lesions, differentiating malignant from benign findings, assessing aggressiveness of tumors, identifying ischemia and by extension hypoxia within tumors, and assessing treatment response. While most clinical perfusion imaging is currently performed with CT or MR, a number of methods for PET imaging of tumor perfusion have been described. The inert PET radiotracer ¹⁵O-water PET represents the recognized gold standard for absolute quantification of tissue perfusion in both normal tissue and a variety of pathological conditions including cancer. Other cancer PET perfusion imaging strategies include the use of radiotracers with high first-pass uptake, analogous to those used in cardiac perfusion PET. This strategy produces more visually pleasing high-contrast images that provide relative rather than absolute perfusion quantification. Lastly, multiple timepoint imaging of PET tracers such as ¹⁸F-FDG, are not specifically optimized for perfusion, but have advantages related to availability, convenience, and reimbursement. Multiple obstacles have thus far blocked the routine use of PET imaging for tumor perfusion, including tracer production and distribution, image processing, patient body coverage, clinical validation, regulatory approval and reimbursement, and finally feasible clinical workflows. Fortunately, these obstacles are being overcome, especially within larger imaging centers, opening the door for PET imaging of tumor perfusion to become standard clinical practice. In the foreseeable future, it is possible that whole-body PET perfusion imaging with ¹⁵O-water will be able to be performed in a single imaging session concurrent with standard PET imaging techniques such as ¹⁸F-FDG-PET. This approach could establish an efficient clinical workflow. The resultant ability to measure absolute tumor blood flow in combination with glycolysis will provide important complementary information to inform prognosis and clinical decisions.

Imaging of hemorrhagic primary central nervous system lymphoma: A case report

BACKGROUND

A primary central nervous system lymphoma (PCNSL) presenting with massive hemorrhage is a rare occurrence that is difficult to distinguish from a high-grade glioblastoma. Comprehensive descriptions of the imaging characteristics of such tumors have not yet been reported. Herein, we reported a case of a PCNSL with massive hemorrhage by presenting the imaging features of computed tomography (CT) imaging and structural and perfusion magnetic resonance imaging (MRI).

CASE SUMMARY

A 48-year-old man presented with headache lasting for 10 d. CT of the brain showed a round, heterogeneous, high-density lesion with surrounding edema in the right temporal lobe. For further diagnosis, a series of MRI examinations of the brain were subsequently performed, and a hemorrhagic lesion with ring-like enhancement was determined. The whole lesion was relatively hypoperfused on arterial spin labeling images. Surgical resection of the lesion and histopathological examination confirmed that the lesion was a diffuse large B-cell lymphoma with massive hemorrhage.

CONCLUSION

PCNSLs with hemorrhage occur very rarely, and structural and perfusion MRI examinations are requested exceedingly rarely. This case provided insight into some characteristics of a hemorrhagic lymphoma on CT and MRI examinations. Perfusion MRI examination may be useful for the differential diagnosis of PCNSLs and other brain tumors.

Differentiating glioblastoma multiforme from cerebral lymphoma: application of advanced texture analysis of quantitative apparent diffusion coefficients

PURPOSE

The purpose of this study was to differentiate glioblastoma multiforme from primary central nervous system lymphoma using the customised first and second-order histogram features derived from apparent diffusion coefficients.Methods and materials: A total of 82 patients (57 with glioblastoma multiforme and 25 with primary central nervous system lymphoma) were included in this study. The axial T1 post-contrast and fluid-attenuated inversion recovery magnetic resonance images were used to delineate regions of interest for the tumour and peritumoral oedema. The regions of interest were then co-registered with the apparent diffusion coefficient maps, and the first and second-order histogram features were extracted and compared between glioblastoma multiforme and primary central nervous system lymphoma groups. Receiver operating characteristic curve analysis was performed to calculate a cut-off value and its sensitivity and specificity to differentiate glioblastoma multiforme from primary central nervous system lymphoma.

RESULTS

Based on the tumour regions of interest, apparent diffusion coefficient mean, maximum, median, uniformity and entropy were higher in the glioblastoma multiforme group than the primary central nervous system lymphoma group (P ≤ 0.001). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the maximum of 2.026 or less (95% confidence interval (CI) 75.1-99.9%), and the most specific first and second-order histogram feature was smoothness of 1.28 or greater (84.0% CI 70.9-92.8%). Based on the oedema regions of interest, most of the first and second-order histogram features were higher in the glioblastoma multiforme group compared to the primary central nervous system lymphoma group (P ≤ 0.015). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the 25th percentile of 0.675 or less (100% CI 83.2-100%) and the most specific first and second-order histogram feature was the median of 1.28 or less (85.9% CI 66.3-95.8%).

CONCLUSIONS

Texture analysis using first and second-order histogram features derived from apparent diffusion coefficient maps may be helpful in differentiating glioblastoma multiforme from primary central nervous system lymphoma.

Use of FDG-PET/CT for systemic assessment of suspected primary central nervous system lymphoma: a LOC study

INTRODUCTION

Primary Central Nervous System Lymphoma (PCNSL) is a rare disease with different therapeutic implications than systemic lymphoma. In this study, we evaluated whole-body ¹⁸FDG-PET/CT for pre-chemotherapy imaging of suspected PCNSL.

METHODS

One hundred and thirty consecutive immunocompetent patients were retrospectively included. The results of initial ¹⁸FDG-PET/CT, contrast-enhanced CT (CeCT) and bone marrow biopsy (BMB) when available were compared to a gold standard based on pathological diagnosis or follow-up.

RESULTS

CNS lesion pathology showed large B-cell lymphoma in 95% of patients, including 11 patients with primary vitro-retinal lymphoma. Ten patients (8%) where ultimately diagnosed with systemic lymphoma involvement, including five pathologically confirmed cases, all of which were detected by ¹⁸FDG-PET/CT. ¹⁸FDG-PET/CT showed incidental systemic findings unrelated to lymphoma in 14% of patients. An SUVmax threshold of nine enabled good discrimination between systemic lymphoma and other lesions (sensitivity 92% and specificity 89%). CeCT and BMB performed in 108 and 77 patients respectively revealed systemic lesions in only three patients.

CONCLUSION

¹⁸FDG-PET/CT detected concomitant occult systemic involvement in a non-negligible proportion of suspected PCNSL cases (8%). In this setting its sensitivity is higher than that of CeCT. All of our patients ultimately diagnosed with concomitant systemic involvement had positive ¹⁸FDG-PET/CT. We believe it constitutes a safe one-stop shop evaluation for the systemic pre-treatment imaging of suspected PCNSL.

Utility of flouro-deoxy-glucose positron emission tomography/computed tomography in the diagnostic and staging evaluation of patients with primary CNS lymphoma

Aim: To prospectively assess the clinical utility of pretreatment flouro-deoxy-glucose positron emission tomography/computed tomography (18F-FDG-PET/CT) in patients with primary central nervous system (CNS) lymphoma (PCNSL). Materials & methods: Patients with suspected/proven PCNSL underwent baseline whole-body 18F-FDG-PET/CT. Maximum standardized uptake value and tumor/normal tissue ratios were compared between CNS lymphoma and other histological diagnoses. Results: The mean maximum standardized uptake value (27.5 vs 18.2; p = 0.001) and mean tumor/normal tissue ratio (2.34 vs 1.53; p < 0.001) of CNS lymphoma was significantly higher than other histologic diagnoses. Five of 50 (10%) patients with biopsy-proven CNS lymphomas had pathologically increased FDG-uptake at extraneuraxial sites uncovering systemic lymphoma. Conclusion: Pretreatment whole-body 18F-FDG-PET/CT provides valuable complementary information in the diagnostic and staging evaluation of patients with PCNSL to guide therapeutic decision-making.

Contribution of Different Positron Emission Tomography Tracers in Glioma Management: Focus on Glioblastoma

Although rare, glioblastomas account for the majority of primary brain lesions, with a dreadful prognosis. Magnetic resonance imaging (MRI) is currently the imaging method providing the higher resolution. However, it does not always succeed in distinguishing recurrences from non-specific temozolomide, have been shown to improve -related changes caused by the combination of radiotherapy, chemotherapy, and targeted therapy, also called pseudoprogression. Strenuous attempts to overcome this issue is highly required for these patients with a short life expectancy for both ethical and economic reasons. Additional reliable information may be obtained from positron emission tomography (PET) imaging. The development of this technique, along with the emerging of new classes of tracers, can help in the diagnosis, prognosis, and assessment of therapies. We reviewed the current data about the commonly used tracers, such as 18F-fluorodeoxyglucose (18F-FDG) and radiolabeled amino acids, as well as different PET tracers recently investigated, to report their strengths, limitations, and relevance in glioblastoma management.

Differences between primary central nervous system lymphoma and glioblastoma: topographic analysis using voxel-based morphometry

AIM

To evaluate the diagnostic feasibility of probabilistic analysis using voxel-based morphometry (VBM) in differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM).

MATERIALS AND METHODS

In total, 118 patients with GBM (57 males, 61 females; mean [± standard deviation] age, 56.9±19.3 years; median, 61 years) and 52 patients with PCNSL (37 males, 15 females; mean age, 62±13.3 years, median, 66 years) were studied retrospectively. Each patient underwent preoperative contrast-enhanced T1-weighted imaging (CE-T1WI) using a 1.5 or 3 T magnetic resonance imaging (MRI) system. To assess preferential occurrence sites, images from CE-T1WI were co-registered and spatially normalised using the MNI152 T1 template. Subsequently, a region of interest (ROI) was placed in the centre of the enhancing tumour in normalised images with 1-mm isotropic resolution. The same ROI between normalised and T1 template images was set up using an ROI manager function in ImageJ software. A spherical volume of interest (VOI) with a radius of 10 mm was determined. A probability map was created by overlaying each image with the VOI. Each VOI was removed from T1 template images for VBM analysis. VBM analysis was performed using statistical parametric mapping (SPM) 12 software under default settings.

RESULTS

VBM analysis showed significantly higher frequency in the splenium of the corpus callosum among PCNSL patients than among GBM patients (p<0.05; family-wise error correction).

CONCLUSION

Topographic analysis using VBM provides useful information for differentiating PCNSL from GBM.

Cerebral blood flow abnormalities in neuropsychiatric systemic lupus erythematosus

OBJECTIVE

To investigate the clinical characteristics, imaging changes and early diagnostic methods of neuropsychiatric systemic lupus erythematosus (NPSLE).

METHODS

Thirty-five SLE patients, of which 16 had overt neuropsychiatric symptoms, underwent examination for multiple autoantibodies, including anti-double-stranded DNA (anti-dsDNA) antibody, anti-nucleosome antibody, anti-cardiac-phospholipid antibody (aCL)-IgG, aCL-IgM, anti-β2-glycoprotein I antibody and anti-ribosomal P antibody, and the SLEDAI score of every patient was recorded. All patients further received neuropsychological tests, including the Mini-Mental State Examination, the Self-Rating Anxiety Scale and the Self-Rating Depression Scale. Imaging examination using 3D arterial spin labeling was performed on 3.0 T MRI scanners. After processing the 3D arterial spin labeling image, the cerebral blood flow map was obtained and the cerebral blood flow value was calculated.

RESULTS

The values of anti-dsDNA, anti-nucleosome antibody, aCL-IgG and anti-β2-glycoprotein I antibodies were significantly higher in the NPSLE group than those in the SLE group. The SLEDAI scores of the NPSLE group were significantly higher than those of the SLE group. There were no significant differences between the NPSLE group and the SLE group in the directional ability, memory, attention, numeracy, recall ability or language ability scores on the Mini-Mental State Examination scale. Furthermore, there were no symptoms of anxiety or depression in any of the patients, according to the Self-Rating Anxiety Scale and Self-Rating Depression Scale. In the 35 patients with SLE, decreases in blood perfusion were seen in some areas, and were unilateral and asymmetrically distributed. There was obvious asymmetry between sides in areas including the frontal lobe, temporal lobe, parietal lobe and occipital lobe. The incidence of perfusion decreases in frontal lobe in the NPSLE group was significantly higher than in the SLE group.

CONCLUSION

Neurological lesions in SLE patients can be detected by arterial spin labeling. Cerebral blood flow abnormalities may be helpful for the early diagnosis of neurological lesions in NPSLE.

Accuracy of apparent diffusion coefficients and enhancement ratios on magnetic resonance imaging in differentiating primary cerebral lymphomas from glioblastoma

BACKGROUND AND PURPOSE

This study aimed to determine the accuracy of apparent diffusion coefficient (ADC) and enhancement ratio (ER) in discriminating primary cerebral lymphomas (PCL) and glioblastomas.

MATERIALS AND METHODS

Circular regions of interest were randomly placed centrally within the largest solid-enhancing area of all lymphomas and glioblastomas on both post-contrast T1-weighted images and corresponding ADC maps. Regions of interest were also drawn in the contralateral hemisphere to obtain enhancement and ADC values of normal-appearing white matter. This helped us to calculate the ER and ADC ratio.

RESULTS

Mean enhancement and ADC (mm²/s) values for PCL were 2220.56 ± 2948.30 and 712.00 ± 137.87, respectively. Mean enhancement and ADC values for glioblastoma were 1537.07 ± 1668.33 and 1037.93 ± 280.52, respectively. Differences in ADC values, ratios and ERs were all statistically significant between the two groups (p < 0.05). ADC values correctly predicted 71.4% of the lesions as glioblastoma and 83.3% as PCL (area under the curve (AUC) = 0.86 on receiver operating characteristic curve analysis). ADC ratios correctly predicted 85.7% of the lesions as glioblastoma and 100% as PCL (AUC = 0.93). ERs correctly predicted 71.4% of the lesions as glioblastoma and 88.9% as PCL (AUC = 0.92). The combination of ADC ratio and ER correctly predicted 100% tumour type in both patient subgroups.

CONCLUSIONS

ADC values, ADC ratios and ERs may serve as useful variables to distinguish PCL from glioblastoma. The combination of ADC ratio and ER yielded the best results in identification of both patient subgroups.

Diagnostic performance of DWI for differentiating primary central nervous system lymphoma from glioblastoma: a systematic review and meta-analysis

OBJECTIVE

The purpose of this meta-analysis was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM).

MATERIALS AND METHODS

A thorough search of the databases including PubMed, EMBASE, and Cochrane Library was carried out and the data acquired were up to November 1, 2017. The quality of the studies involved was evaluated using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies, revised version). Multiple analytic values including sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC) curve were calculated and pooled for the statistical analysis. The subgroup analysis was also performed to explore the heterogeneity.

RESULTS

Eight retrospective studies (461 patients with 461 lesions) were included. The pooled SEN, SPE, PLR, NLR, and DOR with 95% confidence interval (CI) were 0.82 [95% CI 0.70-0.90], 0.84 [95% CI 0.75-0.90], 4.96 [95% CI 3.20-7.69], 0.22 [95% CI 0.13-0.37], and 22.85 [95% CI 10.42-50.11], respectively. The area under the curve (AUC) given by SROC curve was 0.90 [95% CI 0.87-0.92]. The subgroup analysis indicated the slice thickness of the images (> 3 mm versus ≤ 3 mm) was a significant factor affecting the heterogeneity. No existence of significant publication bias was confirmed with Deeks' test.

CONCLUSIONS

DWI showed moderate diagnostic performance for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). Moreover, it is of clinical significance using DWI combined with conventional MRI to differentiate PCNSL from GBM.

MRI as a diagnostic biomarker for differentiating primary central nervous system lymphoma from glioblastoma: A systematic review and meta-analysis

BACKGROUND

Accurate preoperative differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma is clinically crucial because the treatment strategies differ substantially.

PURPOSE

To evaluate the diagnostic performance of MRI for differentiating PCNSL from glioblastoma.

STUDY TYPE

Systematic review and meta-analysis.

SUBJECTS

Ovid-MEDLINE and EMBASE databases were searched to find relevant original articles up to November 25, 2018. The search term combined synonyms for "lymphoma," "glioblastoma," and "MRI."

FIELD STRENGTH/SEQUENCE

Patients underwent at least one MRI sequence including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced imaging (DSC), dynamic contrast-enhanced imaging (DCE), arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), intravoxel incoherent motion (IVIM), and magnetic resonance spectroscopy (MRS) using 1.5 or 3 T.

ASSESSMENT

Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

STATISTICAL TESTS

Hierarchical logistic regression modeling was used to obtain pooled sensitivity and specificity. Meta-regression was performed.

RESULTS

Twenty-two studies with 1182 patients were included. MRI sequences demonstrated high overall diagnostic performance with pooled sensitivity of 91% (95% confidence interval [CI], 87-93%) and specificity of 89% (95% CI, 85-93%). The area under the hierarchical summary receiver operating characteristic curve was 0.92 (95% CI, 0.90-0.94). Studies using DSC or ASL showed high diagnostic performance (sensitivity of 93% [95% CI, 89-97%] and specificity of 91% [95% CI, 86-96%]). Heterogeneity was only detected in specificity (I² = 66.84%) and magnetic field strength was revealed to be a significant factor affecting study heterogeneity.

DATA CONCLUSION

MRI showed overall high diagnostic performance for differentiating PCNSL from glioblastoma, with studies using DSC or ASL showing high diagnostic performance. Therefore, MRI sequences including DSC or ASL is a potential diagnostic tool for differentiating PCNSL from glioblastoma.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:560-572.

Differentiation of Primary Central Nervous System Lymphoma From Glioblastoma: Quantitative Analysis Using Arterial Spin Labeling and Diffusion Tensor Imaging

OBJECTIVE

Differentiation of primary central nervous system lymphoma (PCNSL) from glioblastoma using arterial spin labeling perfusion and diffusion tensor imaging (DTI).

METHODS

We performed a prospective study of 31 patients with a provisional diagnosis of PCNSL and glioblastoma who underwent conventional magnetic resonance imaging, DTI, and arterial spin labeling of the brain. The tumor blood flow (TBF), mean diffusivity (MD) plus fractional anisotropy (FA) of the mass were measured. The final diagnosis was confirmed by pathological examination.

RESULTS

The TBF of PCNSL (26.41 ± 4.03 mL/100 g/minute) was significantly lower than that of glioblastoma (51.08 ± 3.9 mL/100 g/minute; P = 0.001). The TBF cutoff (35.73 mL/100 g/minute) used for differentiation showed area under the curve (AUC) of 0.93, accuracy of 95.2%, sensitivity of 91.7%, and specificity of 100%. The MD of PCNSL (0.87 ± 0.2X 10^-3 mm²/second) was significantly lower than that of glioblastoma (0.87 ± 0.2 × 10^-3 mm²/second; P = 0.01). The MD cutoff (0.935 × 10^-3 mm²/second) used for differentiation showed an AUC of 0.73 and accuracy of 66.7% and a sensitivity of 75% and specificity of 55.6%. The FA of PCNSL (0.253 ± 0.05) was significantly greater than that of glioblastoma (0.135 ± 0.06; P = 0.001). The FA cutoff (0.185) used for differentiation revealed an AUC of 0.944 and accuracy of 85.7% and a sensitivity of 83.3% and specificity of 88.9%. The combined TBF, MD, and FA cutoffs revealed an AUC of 0.96 and accuracy of 95.5% and a sensitivity of 83.3% and specificity of 100%.

CONCLUSION

The noninvasive imaging parameters using TBF and DTI might help in differentiating PCNSL from glioblastoma.

PET imaging in glioma: techniques and current evidence

PET holds potential to provide additional information about tumour metabolic processes, which could aid brain tumour differential diagnosis, grading, molecular subtyping and/or the distinction of therapy effects from disease recurrence. This review discusses PET techniques currently in use for untreated and treated glioma characterization and aims to critically assess the evidence for different tracers ([F]Fluorodeoxyglucose, choline and amino acid tracers) in this context.

Utility of arterial spin labelling MRI for discriminating atypical high-grade glioma from primary central nervous system lymphoma

AIM

To evaluate the ability of arterial spin labelling (ASL) magnetic resonance imaging (MRI) in differentiating primary central nervous system lymphoma (PCNSL) from atypical high-grade glioma (HGG), as well as exploring the underlying pathological mechanisms.

METHODS AND MATERIALS

Twenty-three patients with PCNSL and 17 patients with atypical HGG who underwent ASL-MRI were identified retrospectively. Absolute cerebral blood flow (aCBF) and normalised cerebral blood flow (nCBF) values were obtained, and were compared between PCNSL and atypical HGG using the Mann-Whitney U-test. The performance in discriminating between PCNSL and atypical HGG was evaluated using receiver-operating characteristics analysis and area-under-the-curve (AUC) values for aCBF and nCBF. The correlation between microvessel density (MVD) and aCBF was determined by Spearman's correlation analysis.

RESULTS

Atypical HGG demonstrated significantly higher aCBF, nCBF, and MVD values than PCNSL (p<0.05). The diagnostic accuracy of discriminating PCNSL from atypical HGG showed AUC=0.877 (95% confidence interval [CI] 0.735-0.959) for aCBF, and AUC=0.836 (95% confidence interval [CI] 0.685-0.934) for nCBF. There was a moderate positive correlation between aCBF values of region of interest (ROI >30 mm²) in the enhanced area and MVD values (rho=0.579, p=0.0001), and a strong positive correlation between aCBF values MVD based on "point-to-point biopsy" (rho=0.83, p=0.0029). Interobserver agreements for aCBF and nCBF were excellent (ICC >0.75).

CONCLUSIONS

ASL perfusion MRI is a useful imaging technique for the discrimination between atypical HGG and PCNSL, which may be determined by the difference of MVD between them.

Role of contrast-free MR-perfusion in the diagnosis of potential epileptogenic foci in children with focal epilepsia

ASL (Arterial Spin Labeling) – a novel modality of MR angiography – is based on radio-frequency labeling of aqueous protons in the arterial blood; the method is used to monitor blood supply to  organs, including the brain. So far there has been little information on the use of ASL in children with focal epilepsy, especially in the pre-surgery period.

Aim:to evaluate the perfusion patterns in seizure-free children with drug resistant focal epilepsy (FE) using the ASL mode of MRI.

Materials and methods.We studied the ASL data of 54 (23-boys/31 girls) patients with FE  treated in the Dpt. of Neurology at the Russian State Children Hospital from 2015 to 2018. The  patients’ age varied from 4 months to 17 years. All images were produced with a 3T GE Discovery  750W system.

Results. We found several brain perfusion patterns in children with FE; among other factors, those patterns depended on the clinical status of the patient, i. e. the interictal period or the early post- seizure period. The main pattern of the interictal period was characterized by a focal decrease in  perfusion located around a structural focus identified on MRI scans. In the early post-seizure  period, there was an increase in the arterial perfusion in the area of a structural epileptogenic lesion.

Conclusion.ASL-MRI is an effective diagnostic method providing more information on children  with FE during their pre-surgery phase. The ASL modality needs further research to rationalize its wider use as a preferred diagnostic tool or as a combination with the more complex PET and SPECT.