Differentiation of residual/recurrent gliomas from postradiation necrosis with arterial spin labeling and diffusion tensor magnetic resonance imaging-derived metrics

Velocity-Selective Arterial Spin Labeling Perfusion in Monitoring High Grade Gliomas Following Therapy: Clinical Feasibility at 1.5T and Comparison with Dynamic Susceptibility Contrast Perfusion

MR perfusion imaging is important in the clinical evaluation of primary brain tumors, particularly in differentiating between true progression and treatment-induced change. The utility of velocity-selective ASL (VSASL) compared to the more commonly utilized DSC perfusion technique was assessed in routine clinical surveillance MR exams of 28 patients with high-grade gliomas at 1.5T. Using RANO criteria, patients were assigned to two groups, one with detectable residual/recurrent tumor ("RT", n = 9), and the other with no detectable residual/recurrent tumor ("NRT", n = 19). An ROI was drawn to encompass the largest dimension of the lesion with measures normalized against normal gray matter to yield rCBF and tSNR from VSASL, as well as rCBF and leakage-corrected relative CBV (lc-rCBV) from DSC. VSASL (rCBF and tSNR) and DSC (rCBF and lc-rCBV) metrics were significantly higher in the RT group than the NRT group allowing adequate discrimination (p < 0.05, Mann-Whitney test). Lin's concordance analyses showed moderate to excellent concordance between the two methods, with a stronger, moderate correlation between VSASL rCBF and DSC lc-rCBV (r = 0.57, p = 0.002; Pearson's correlation). These results suggest that VSASL is clinically feasible at 1.5T and has the potential to offer a noninvasive alternative to DSC perfusion in monitoring high-grade gliomas following therapy.

Clinical applications of skeletal muscle diffusion tensor imaging

Diffusion tensor imaging (DTI) may allow the determination of new threshold values, based on water anisotropy, to differentiate between healthy muscle and various pathological processes. Additionally, it may quantify treatment monitoring or training effects. Most current studies have evaluated the potential of DTI of skeletal muscle to assess sports-related injuries or therapy, and training monitoring. Another critical area of application of this technique is the characterization and monitoring of primary and secondary myopathies. In this manuscript, we review the application of DTI in the evaluation of skeletal muscle in these and other novel clinical scenarios, with emphasis on the use of quantitative imaging-derived biomarkers. Finally, the main limitations of the introduction of DTI in the clinical setting and potential areas of future use are discussed.

Advanced Magnetic Resonance Imaging in the Evaluation of Treated Glioblastoma: A Pictorial Essay

MRI plays a key role in the evaluation of post-treatment changes, both in the immediate post-operative period and during follow-up. There are many different treatment's lines and many different neuroradiological findings according to the treatment chosen and the clinical timepoint at which MRI is performed. Structural MRI is often insufficient to correctly interpret and define treatment-related changes. For that, advanced MRI modalities, including perfusion and permeability imaging, diffusion tensor imaging, and magnetic resonance spectroscopy, are increasingly utilized in clinical practice to characterize treatment effects more comprehensively. This article aims to provide an overview of the role of advanced MRI modalities in the evaluation of treated glioblastomas. For a didactic purpose, we choose to divide the treatment history in three main timepoints: post-surgery, during Stupp (first-line treatment) and at recurrence (second-line treatment). For each, a brief introduction, a temporal subdivision (when useful) or a specific drug-related paragraph were provided. Finally, the current trends and application of radiomics and artificial intelligence (AI) in the evaluation of treated GB have been outlined.

The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review

Background and purpose

Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning.

Materials and methods

PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution.

Results

Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps.

Conclusions

Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.

Multi-parametric arterial spin labeling and diffusion-weighted imaging of paranasal sinuses masses

PURPOSE

To evaluate arterial spin labeling (ASL) and diffusion-weighted imaging (DWI) in discrimination of benign from malignant paranasal sinus (PNS) tumors.

MATERIAL AND METHODS

A prospective study was done upon 42 cases of PNS masses that underwent magnetic resonance ASL and DWI of the head. Tumor blood flow (TBF) and apparent diffusion coefficient (ADC) of the masses were calculated by two observers. The pathological diagnosis was malignant (n = 28) and benign (n = 14) cases.

RESULTS

For both observers, the malignant PNS masses had significantly higher TBF (P < 0.001, 0.001) and lower ADC (P < 0.001, 0.001) than in benign masses. The ROC curve analysis of TBF, The threshed TBF was (121.45, 122.68 mL/100 g/min) used for differentiation between benign and malignant PNS masses, revealed sensitivity (92.9%, 89.3%), specificity (85.7%, 85.7%), accuracy (90.5%, 88.1%) and the AUC was 0.87 and 0.86 by both observers. the ROC curve analysis of ADC, The threshold ADC (1.215, 1.205 X10^-3mm2/s) was used for differentiation between benign and malignant PNS masses, revealed sensitivity (96.4%, 89.3%), specificity (78.6%, 78.6%), accuracy of (90.5%, 85.7%) and the AUC was 0.93 and 0.92 by both observers. Combined analysis of TBF and ADC used for differentiation between benign and malignant PNS masses had revealed sensitivity (96.4%, 89.3%), specificity (92.9%, 85.7%) accuracy of (95.2%, 88.1%) and AUC. (0.995, 0.985) for both observers.

CONCLUSION

Combined using of TBF and ADC have a role in differentiation malignant from benign PNS masses.

White matter tracts alterations underpinning reward and conflict processing

BACKGROUND

Reinforcement sensitivity theory (RST) is proposed as a neurobiological system that eventually led to emotion and motivation-based constructs of personality. Traditionally segmented into the behavioral activation system (BAS) and the behavioral inhibition system (BIS), RST is commonly used to describe personality and behavior. Although there have been studies linking gray matter alterations with BIS/BAS subscales, the role of white matter (WM) alterations is yet controversial. We aimed to investigate the specific WM tracts associated with BIS/BAS scores.

METHODS

220 healthy participants (mean age = 39.14 ± 20.23, 80 (35.7 %) females) were evaluated using the BIS/BAS questionnaire from the LEMON database. Diffusion MRI connectometry (DMRI) was used to investigate the WM correlates of BIS/BAS subscales in each gender group. Multiple regression models with the covariates of age, handedness, and education were fitted to address the correlation of local connectomes with BIS/BAS components.

RESULTS

DMRI connectometry revealed that the quantitative anisotropy (QA) value of the splenium of the corpus callosum, right cerebellum, middle cerebellar peduncle, and superior cerebellar peduncle, had a significant negative correlation with each BIS/BAS subscale. In contrast, the QA value in the body of the corpus callosum and bilateral cingulum showed a positive correlation with BIS/BAS subscales.

CONCLUSION

The connectivity of WM in certain tracts may contribute to behavioral activation and inhibition. This finding expands the findings on the neural networks associated with risk-taking and reward-seeking behaviors.

The value of arterial spin labelling (ASL) perfusion MRI in the assessment of post-treatment progression in adult glioma: A systematic review and meta-analysis

Background

The distinction between viable tumor and therapy-induced changes is crucial for the clinical management of patients with gliomas. This study aims to quantitatively assess the efficacy of arterial spin labeling (ASL) biomarkers, including relative cerebral blood flow (rCBF) and absolute cerebral blood flow (CBF), for the discrimination of progressive disease (PD) and treatment-related effects.

Methods

Eight articles were included in the synthesis after searching the literature systematically. Data have been extracted and a meta-analysis using the random-effect model was subsequently carried out. Diagnostic accuracy assessment was also performed.

Results

This study revealed that there is a significant difference in perfusion measurements between groups with PD and therapy-induced changes. The rCBF yielded a standardized mean difference (SMD) of 1.25 [95% CI 0.75, 1.75] (p < .00001). The maximum perfusion indices (rCBFmax and CBFmax) both showed equivalent discriminatory ability, with SMD of 1.35 [95% CI 0.78, 1.91] (p < .00001) and 1.56 [95% CI 0.79, 2.33] (p < .0001), respectively. Similarly, accuracy estimates were comparable among ASL-derived metrices. Pooled sensitivities [95% CI] were 0.85 [0.67, 0.94], 0.88 [0.71, 0.96], and 0.93 [0.73, 0.98], and pooled specificities [95% CI] were 0.83 [0.71, 0.91], 0.83 [0.67, 0.92], 0.84 [0.67, 0.93], for rCBF, rCBFmax and CBFmax, respectively. Corresponding HSROC area under curve (AUC) [95% CI] were 0.90 [0.87, 0.92], 0.92 [0.89, 0.94], and 0.93 [0.90, 0.95].

Conclusion

These results suggest that ASL quantitative biomarkers, particularly rCBFmax and CBFmax, have the potential to discriminate between glioma progression and therapy-induced changes.

Challenges and opportunities for advanced neuroimaging of glioblastoma

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Diffusion-weighted imaging and arterial spin labeling radiomics features may improve differentiation between radiation-induced brain injury and glioma recurrence

OBJECTIVES

To determine whether radiomics features derived from diffusion-weighted imaging (DWI) and arterial spin labeling (ASL) can improve the differentiation between radiation-induced brain injury (RIBI) and tumor recurrence (TR) in glioma patients.

METHODS

A total of 4199 radiomics features were extracted from conventional MRI, apparent diffusion coefficient (ADC), and cerebral blood flow (CBF) maps, obtained from 96 pathologically confirmed WHO grade 2~4 gliomas with enhancement after standard treatment. The intraclass correlation coefficient (ICC) was used to test segmentation stability between two doctors. Radiomics features were selected using the Mann-Whitney U test, LASSO regression, and RFE algorithms. Four machine learning classifiers were adopted to establish radiomics models. The diagnostic performance of multiparameter, conventional, and single-parameter MRI radiomics models was compared using the area under the curve (AUC). The models were evaluated in the subsequent independent validation set (n = 30).

RESULTS

Eight important radiomics features (3 from conventional MRI, 1 from ADC, and 4 from CBF) were selected. Support vector machine (SVM) was chosen as the optimal classifier. The diagnostic performance of the multiparameter MRI radiomics model (AUC 0.96) was higher than that of the conventional MRI (AUC 0.88), ADC (AUC 0.91), and CBF (AUC 0.95) radiomics models. For subgroup analysis, the multiparameter MRI radiomics model showed similar performance, with AUCs of 0.98 in WHO grade 2~3 and 0.96 in WHO grade 4.

CONCLUSION

The incorporation of noninvasive DWI and ASL into the MRI radiomics model improved the diagnostic performance in differentiating RIBI from TR; ASL, especially, played a significant role.

KEY POINTS

• The multiparameter MRI radiomics model was superior to the conventional MRI radiomics model in differentiating glioma recurrence from radiation-induced brain injury. • Diffusion and perfusion MRI could improve the ability of the radiomics model in predicting the progression in patients with glioma. • Arterial spin labeling played an important role in predicting glioma progression using radiomics models.

Diffusion tensor imaging of dorsal stream language areas in patients with post-stroke aphasia

Background

Aphasia complicating stroke occurs due to language deficits that decrease communication abilities and functional independence. Our study aims to assess fractional anisotropy (FA) and mean diffusivity (MD) parameters of diffusion tensor imaging (DTI) of the dorsal stream language areas in patients with post-stroke aphasia. It was conducted on 27 patients with post-stroke aphasia and 27 age- and sex-matched controls who underwent DTI of the brain. FA and MD values of Broca's area (BA), Wernick's area (WA), superior longitudinal fasciculus (SLF), and arcuate fasciculus (AF), and number of tract fibers (TF) of AF and SLF were calculated. Results were correlated with National Institutes of Health Stroke Scale (NIHSS), Arabic version of Comprehensive Aphasia Test (Arabic CAT), and Mansoura Arabic Screening Aphasia Test (MASAT).

Results

FA of AF and SLF in patients was significantly lower (P = 0.001) than controls. MD of AF and SLF in patients was significantly higher (P = 0.001) than controls. The mean volume TF of AF and SLF in patients was significantly (P = 0.001) lower than the mean volume in controls for AF and SLF. FA cutoff for AF was 0.34 and for SLF, it was 0.35 with sensitivity, specificity, and accuracy (85.2%, 62.1%, 73.2%) for AF, (74.1%, 69%, 71.4%) for SLF, respectively. MD cutoff value for AF was 0.87, and 0.84 for SLF with sensitivity, specificity, and accuracy (63%, 72.4%, 67.8%) for AF, (81.5%, 79.3%, 80.4%) for SLF, respectively. Cutoff TF of AF was 1728 and for SLF it was 601 with sensitivity, specificity, and accuracy (88.9%, 72.4%, 80.4%) for AF and (85.2%, 85.2%, 78.6%) for SLF, respectively.

Conclusions

DTI is a non-invasive promising method that can be used to assess language areas in patients with post-stroke aphasia.

Diffusion imaging could aid to differentiate between glioma progression and treatment-related abnormalities: a meta-analysis

Background

In a considerable subgroup of glioma patients treated with (chemo) radiation new lesions develop either representing tumor progression (TP) or treatment-related abnormalities (TRA). Quantitative diffusion imaging metrics such as the Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy (FA) have been reported as potential metrics to noninvasively differentiate between these two phenomena. Variability in performance scores of these metrics and absence of a critical overview of the literature contribute to the lack of clinical implementation. This meta-analysis therefore critically reviewed the literature and meta-analyzed the performance scores.

Methods

Systematic searching was carried out in PubMed, EMBASE and The Cochrane Library. Using predefined criteria, papers were reviewed. Diagnostic accuracy values of suitable papers were meta-analyzed quantitatively.

Results

Of 1252 identified papers, 10 ADC papers, totaling 414 patients, and 4 FA papers, with 154 patients were eligible for meta-analysis. Mean ADC values of the patients in the TP/TRA groups were 1.13 × 10⁻³mm²/s (95% CI 0.912 × 10^–3–1.32 × 10⁻³mm²/s) and 1.38 × 10⁻³mm²/s (95% CI 1.33 × 10^–3–1.45 × 10⁻³mm²/s, respectively. Mean FA values of TP/TRA was 0.19 (95% CI 0.189–0.194) and 0.14 (95% CI 0.137–0.143) respectively. A significant mean difference between ADC and FA values in TP versus TRA was observed (p = 0.005).

Conclusions

Quantitative ADC and FA values could be useful for distinguishing TP from TRA on a meta-level. Further studies using serial imaging of individual patients are warranted to determine the role of diffusion imaging in glioma patients.

Tumor Progression and Treatment-Related Changes: Radiological Diagnosis Challenges for the Evaluation of Post Treated Glioma

Simple Summary

Glioma is the most common primary malignant tumor of the adult central nervous system. Despite aggressive multimodal treatment, its prognosis remains poor. During follow-up, it remains challenging to distinguish treatment-related changes from tumor progression in treated patients with gliomas due to both share clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions). The early effective identification of tumor progression and treatment-related changes is of great significance for the prognosis and treatment of gliomas. We believe that advanced neuroimaging techniques can provide additional information for distinguishing both at an early stage. In this article, we focus on the research of magnetic resonance imaging technology and artificial intelligence in tumor progression and treatment-related changes. Finally, it provides new ideas and insights for clinical diagnosis.

Abstract

As the most common neuro-epithelial tumors of the central nervous system in adults, gliomas are highly malignant and easy to recurrence, with a dismal prognosis. Imaging studies are indispensable for tracking tumor progression (TP) or treatment-related changes (TRCs). During follow-up, distinguishing TRCs from TP in treated patients with gliomas remains challenging as both share similar clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions) and fulfill criteria for progression. Thus, the early identification of TP and TRCs is of great significance for determining the prognosis and treatment. Histopathological biopsy is currently the gold standard for TP and TRC diagnosis. However, the invasive nature of this technique limits its clinical application. Advanced imaging methods (e.g., diffusion magnetic resonance imaging (MRI), perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), amide proton transfer (APT) and artificial intelligence (AI)) provide a non-invasive and feasible technical means for identifying of TP and TRCs at an early stage, which have recently become research hotspots. This paper reviews the current research on using the abovementioned advanced imaging methods to identify TP and TRCs of gliomas. First, the review focuses on the pathological changes of the two entities to establish a theoretical basis for imaging identification. Then, it elaborates on the application of different imaging techniques and AI in identifying the two entities. Finally, the current challenges and future prospects of these techniques and methods are discussed.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Diffusion Tensor Imaging Technology to Quantitatively Assess Abnormal Changes in Patients With Thyroid-Associated Ophthalmopathy

Objective

We aim to investigate the feasibility of using diffusion tensor imaging (DTI) to evaluate changes in extraocular muscles (EOMs) and lacrimal gland (LG) in patients with thyroid-associated ophthalmopathy (TAO) and to evaluate disease severity.

Materials and Methods

A total of 74 participants, including 17 healthy controls (HCs), 22 patients with mild TAO, and 35 patients with moderate-severe TAO, underwent 3-Tesla DTI to measure fractional anisotropy (FA) and mean diffusivity (MD) of the EOMs and LG. Ophthalmological examinations, including visual acuity, exophthalmos, intraocular pressure, and fundoscopy, were performed. FA and MD values were compared among patients with different disease severity. Multiple linear regression was adopted to predict the impact of clinical variables on DTI parameters of orbital soft tissue.

Results

TAO patients’ EOMs and LG showed significantly lower FA values and higher MD compared to HCs’ (P < 0.05). Moderate-severe TAO patients’ EOMs and LG had dramatically lower FA and higher MD compared with HCs (P < 0.05). In addition, only the DTI parameters of the medial rectus were considerably different between mild and moderate-severe TAO patients (P = 0.017, P = 0.021). Multiple linear regression showed that disease severity had a significant impact on the DTI parameters of orbital soft tissue.

Conclusion

DTI is a useful tool for detecting microstructural changes in TAO patients’ orbital soft tissue. DTI findings, especially medial rectus DTI parameters, can help to indicate the disease severity in TAO patients.

Diffusion Tensor Imaging of Auditory Pathway in Patients With Crigler-Najjar Syndrome Type I: Correlation With Auditory Brainstem Response

AIM

To evaluate the role of diffusion tensor imaging of the auditory pathway in patients with Crigler Najjar syndrome type I and its relation to auditory brainstem response.

METHODS

Prospective study was done including 12 patients with Crigler Najjar syndrome type I and 10 age- and sex-matched controls that underwent diffusion tensor imaging of brain. Mean diffusivity and fractional anisotropy at 4 regions of the brain and brainstem on each side were measured and correlated with the results of auditory brainstem response for patients.

RESULTS

There was significantly higher mean diffusivity of cochlear nucleus, superior olivary nucleus, inferior colliculus, and auditory cortex of patients versus controls on both sides for all regions (P = .001). The fractional anisotropy of cochlear nucleus, superior olivary nucleus, inferior colliculus, and auditory cortex of patients versus controls was significantly lower, with P values of, respectively, .001, .001, .003, and .001 on the right side and .001, .001, .003, and .001 on left side, respectively. Also, a negative correlation was found between the maximum bilirubin level and fractional anisotropy of the left superior olivary nucleus and inferior colliculus of both sides. A positive correlation was found between the mean diffusivity and auditory brainstem response wave latency of the right inferior colliculus and left cochlear nucleus. The fractional anisotropy and auditory brainstem response wave latency of the right superior olivary nucleus, left cochlear nucleus, and inferior colliculus of both sides were negatively correlated.

CONCLUSION

Diffusion tensor imaging can detect microstructural changes in the auditory pathway in Crigler Najjar syndrome type I that can be correlated with auditory brainstem response.

Is Diffusion Tensor Imaging-Guided Radiotherapy the New State-of-the-Art? A Review of the Current Literature and Technical Insights

Despite the increasing precision of radiotherapy delivery, it is still frequently associated with neurological complications. This is in part due to damage to eloquent white matter (WM) tracts, which is made more likely by the fact they cannot be visualised on standard structural imaging. WM is additionally more vulnerable than grey matter to radiation damage. Primary brain malignancies also are known to spread along the WM. Diffusion tensor imaging (DTI) is the only in vivo method of delineating WM tracts. DTI is an imaging technique that models the direction of diffusion and therefore can infer the orientation of WM fibres. This review article evaluates the current evidence for using DTI to guide intracranial radiotherapy and whether it constitutes a new state-of-the-art technique. We provide a basic overview of DTI and its known applications in radiotherapy, which include using tractography to reduce the radiation dose to eloquent WM tracts and using DTI to detect or predict tumoural spread. We evaluate the evidence for DTI-guided radiotherapy in gliomas, metastatic disease, and benign conditions, finding that the strongest evidence is for its use in arteriovenous malformations. However, the evidence is weak in other conditions due to a lack of case-controlled trials.

Distinguishing Tumor Recurrence From Radiation Necrosis in Treated Glioblastoma Using Multiparametric MRI

PURPOSE

The purpose of this study was to evaluate the diagnostic performance of single-parameter, unimodal and bimodal magnetic resonance imaging (MRI) in differentiating tumor recurrence (TR) from radiation necrosis (RN) in patients with glioblastoma (GBM) after treatment using diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), dynamic susceptibility contrast enhancement-perfusion weighted imaging (DSC-PWI), and proton magnetic resonance spectroscopy (¹H-MRS).

MATERIALS AND METHODS

Patients with histologically proven GBM who underwent surgical intervention followed by chemoradiotherapy and developed a new, progressively enhanced lesion on follow-up MRI were included in our study. Subsequently, DWI, DTI, DSC-PWI, and ¹H-MRS were performed. Then, these patients underwent a second surgical operation or follow-up MRI to prove TR or RN. MRI metrics include apparent diffusion coefficient (ADC) and relative ADC (rADC) values derived from DWI; fractional anisotropy (FA), axial diffusion coefficient (DA) and radial diffusion coefficient (DR) values derived from DTI; and relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) derived from DSC-PWI. Spectral metabolites such as choline (Cho), creatine (Cr), N-acetylaspartate (NAA), lactate (Lac), and lipids (Lip) were derived from MRS, and the ratios of these metabolites were calculated, including Cho/NAA, Cho/Cr, NAA/Cr, Lac/Cr, and Lip/Cr. These indices were compared between the TR group and RN group, and the receiver operating characteristic (ROC) curve was used to evaluate the performance in distinguishing TR from RN by using single-parameter, unimodal and bimodal MRI.

RESULTS

There were significant differences between the TR and RN groups in terms of ADC (p = 0.001), rADC (p < 0.001), FA (p = 0.001), DA (p = 0.003), DR (p = 0.003), rCBV (p < 0.001), rCBF (p < 0.001), Cho/NAA (p < 0.001), Lac/Cr (p < 0.001) and Lip/Cr (p < 0.001). ROC analysis suggested that rCBV, MRS, and DSC + MRS were the optimal single-parameter, unimodal, and bimodal MRI classifiers for distinguishing TR from RN, with AUC values of 0.909, 0.940, and 0.994, respectively.

CONCLUSION

The combination of parameters based on multiparametric MRI in the region of enhanced lesions is a valuable noninvasive tool for discriminating TR from RN.

Diffusion tensor magnetic resonance imaging: is it valuable in the detection of brain microstructural changes in patients having migraine without aura?

Purpose

The aim of this study is to assess the diagnostic value of diffusion tensor magnetic resonance imaging (MRI) in the detection of brain microstructural changes in patients having migraine without aura.

Material and methods

Our prospective study included 33 patients having migraine without aura and 15 volunteers with matched age and sex, who underwent brain MRI with diffusion tensor imaging (DTI). The fractional anisotropy (FA) and mean diffusivity (MD) of selected grey and white matter regions on both sides were measured and correlated with the neurological clinical examination.

Results

Significant differences were detected in MD values in the thalamus, globus pallidus, and hippocampus head on the right side of patients versus controls. Also, significant differences of the FA values were detected in the thalamus, globus pallidus, and hippocampus head on the right side of patients versus controls. Regarding the FA values of the same regions on the left side, a significant difference in the FA value was detected only in the hippocampus head. There was a statistically significant difference in the FA values on both sides of the white matter of the frontal lobes, posterior limbs of the internal capsules, and cerebellar hemispheres in patients compared to controls. There was a statistically significant difference in MD values in the white matter of both frontal lobes, posterior limb of the right internal capsule, and both cerebellar hemispheres in patients compared to controls.

Conclusions

DTI can detect microstructural changes of the grey and white matter in patients having migraine without aura that could not be detected by conventional MRI.

Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging

This article is a comprehensive review of the basic background, technique, and clinical applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A variety of AI and radiomics utilized conventional and advanced techniques to differentiate brain tumors from non-neoplastic lesions such as inflammatory and demyelinating brain lesions. It is used in the diagnosis of gliomas and discrimination of gliomas from lymphomas and metastasis. Also, semiautomated and automated tumor segmentation has been developed for radiotherapy planning and follow-up. It has a role in the grading, prediction of treatment response, and prognosis of gliomas. Radiogenomics allowed the connection of the imaging phenotype of the tumor to its molecular environment. In addition, AI is applied for the assessment of extra-axial brain tumors and pediatric tumors with high performance in tumor detection, classification, and stratification of patient's prognoses.

[Consistency analysis between 3D arterial spin labeling and dynamic susceptibility contrast perfusion magnetic resonance imaging in perfusion imaging of brain tumor]

OBJECTIVE

To analyze the consistency between cerebral blood flow (CBF) of 3D arterial spin labeling (3D ASL) and dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-PWI) in the measurement of brain tumors.

METHODS

Nineteen patients with pathologically confirmed brain tumors were enrolled in this study.The brain tumors included glioma (n=9), meningioma (n=5), hemangioblastoma (n=2), cerebral metastasis (n=2) and cavernous hemangioma (n=1).Both ASL and DSC MRI were performed in all the 19 patients (57 regions of interest), and CBF was quantitatively determined.

RESULTS

A significant consistency was found between CBF measured by 3D ASL and the relative CBF (rCBF) determined by DSC (P=0.005).

CONCLUSION

3D ASL and DSC PWI are consistent in evaluating blood flow in brain tumors and can accurately evaluate brain tumors perfusion.

Hypervascular vestibular schwannoma: A case report and review of the literature

Vestibular schwannomas, also known as acoustic neuromas, are benign tumors that arise from Schwann cells near the transition from glial cells to Schwann cells. While most vestibular schwannomas are hypovascular tumors, a small percentage constitute the hemorrhagic and/or hypervascular vestibular schwannomas (HVS) subtype. We describe a case of a 36-year-old female who presented with nausea, vomiting, and an acute decrease in vision in her right eye. Computed tomography of the head demonstrated a hemorrhagic lesion in the right hemisphere with evidence of ventricular effacement. Follow-up magnetic resonance imaging revealed a mass in the right cerebellopontine angle that was hypointense on T1-weighted imaging and mild hyperintense heterogeneous signal on T2-weighted imaging, suggestive of a hemorrhagic vestibular schwannoma. It is important for radiologists to recognize the unique clinical and radiological features of HVS in the initial diagnostic assessment of cerebellopontine angle tumors and to distinguish it from common (hypovascular) vestibular schwannomas and other related pathologies. A preoperative diagnosis of HVS allows clinicians to become familiar with the unique characteristics of the tumor and to devise a feasible operative strategy prior to surgical resection.

Starlike polymer brush-based ultrasmall nanoparticles with simultaneously improved NIR-II fluorescence and blood circulation for efficient orthotopic glioblastoma imaging

Fluorescence imaging (FI) in the second near-infrared region (NIR-II, 1000-1700 nm) has attracted great attention for brain tumor imaging due to its deep penetration and high resolution. However, traditional NIR-II organic fluorescent nanoparticles (NPs) are usually hindered by uncontrolled large size (~30-100 nm), marked aggregation-caused quenching (ACQ) effect, and limited blood circulation (~1-3 h), which have great impact on efficient NIR-II FI of deep brain tumors. Herein, starlike polymer brush-based ultrasmall TQFP-10 NPs, with bright NIR-II fluorescence, prolonged blood circulation, and enhanced tumor accumulation, are facilely prepared for efficient orthotopic glioblastoma (GBM) imaging. Compared with traditional method prepared NPs (physically coated TQF@NPs and PEG modified TQF-PEG_5K NPs), the ultrasmall (~8 nm) TQFP-10 NPs display a higher NIR-II fluorescence QY (1.9%), which is 2.1- and 3.8-fold higher than TQF@NPs (0.9%) and TQF-PEG_5K NPs (0.5%), respectively. In addition, TQFP-10 NPs present a 10.6-fold higher blood circulation half-life (t_1/2 = 8.5 h) than that of TQF-PEG_5K NPs. Consequently, TQFP-10 NPs exhibit 4.2- and 33-fold higher maximal tumor to normal tissue ratio in subcutaneous and in situ NIR-II FI of GBM, respectively, than TQF@NPs and TQF-PEG_5K NPs, attractively realizing GBM imaging. This work provides a general strategy for constructing ultrasmall NIR-II fluorescent NPs with simultaneously improved NIR-II fluorescence and blood circulation for efficient brain tumor imaging.

Assessment of diffusion tensor imaging in differentiation between pyogenic and tuberculous spondylitis

PURPOSE

to assess diffusion tensor imaging (DTI); an emerging technique for differentiation between pyogenic and tuberculous spondylitis.

PATIENTS AND METHODS

The study was carried out on 33 patients with infective spondylitis performing conventional MRI and DTI. The mean diffusivity (MD) and fractional anisotropy (FA) of the affected vertebral body were calculated by two readers.

RESULTS

The MD of pyogenic spondylitis of both readers (1.48 ± 0.09 and 1.47 ± 0.08 × 10^-3 mm²/s) were significantly higher values (P = 0.001) than tuberculous spondylitis (1.11 ± 0.15 and 1.18 ± 0.08 × 10^-3 mm²/s). The FA of pyogenic spondylitis of both readers (0.18 ± 0.09 and 0.20 ± 0.08) were significantly lower values (P = 0.001) than tuberculous spondylitis (0.30 ± 0.05 and 0.32 ± 0.03). There was a strong inter-reader agreement between both readers using MD (K = 0.963) and FA (K = 0.858). The thresholds MD and FA used for differentiating pyogenic and tuberculous spondylitis of both readers were 1.37 and 1.33 × 10^-3 mm²/s and 0.21 and 0.25 with the area under the curve (AUC) of 0.927 and 0.831 respectively. Combined MD and FA revealed increased AUC to 0.97 and 0.98 of both readers respectively.

CONCLUSION

DTI with its parameters can be considered a noninvasive beneficial quantitative method that can help in differentiation between pyogenic and tuberculous spondylitis.

Bone-related disorders of the jaw: A clinico-radiological diagnostic algorithm

Bone-related disorders of the jaw (BRDJ) include a spectrum of non-neoplastic and neoplastic lesions of the maxillofacial region that have been recently classified into fibro-osseous lesions, giant cell lesions and osseous tumours. The histopathological features of BRDJ can be similar and overlie each other. Imaging is important in order to reach a specific diagnosis. However, the appearance of BRDJ on imaging is non-specific in some cases. Computed tomography (CT) and magnetic resonance imaging (MRI) are used for accurate localisation, characterisation of the tumour matrix, delineation of the lesion extension and establishment of the relation of BRDJ to the surrounding structures. Imaging is usually done to detect the relationship with the adjacent surrounding vital structures and to diagnose aggressive forms, malignant transformation and associated syndromes. The correlation of the demographic findings, the location and the clinical presentations with the imaging features are important for the diagnosis of BRDJ. The proposed clinico-radiological diagnostic algorithm with CT and MRI helps a specific diagnosis to be reached in some cases.

Diffusion Tensor Imaging of Brain Metastases in Patients with Breast Cancer According to Molecular Subtypes

BACKGROUND AND PURPOSE

Recent studies have shown that diffusion tensor imaging (DTI) parameters are used to follow the patients with breast cancer and correlate well as a prognostic parameter of breast cancer. However, as far as we know, there is no data to compare the DTI features of breast cancer brain metastases according to molecular subtypes in the literature. Our aim is to evaluate whether there are any differences in DTI parameters of brain metastases in patients with breast cancer according to molecular subtypes.

METHODS

Twenty-seven patients with breast cancer and 82 metastatic brain lesions were included. We classified subjects into three subgroups according to their hormone expression; Group 0, triple- negative (n; 6, 19 lesions), group 1, HER2-positive (n;16, 54 lesions) and group 2, hormone-- positive group (n; 5, 9 lesions). The apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) values in DTI were measured and compared between three groups.

RESULTS

ADC, AD and RD values of group 2 were significantly lower compared to group 0. No significant differences were found in FA, ADC, AD and RD values between the group 0 and 1 and the group 1 and 2.

CONCLUSION

Metastasis of aggressive triple-negative breast cancer showed higher ADC values compared to the less aggressive hormone-positive group. Higher ADC values in brain metastases of breast cancer may indicate a poor prognosis, so DTI findings could play a role in planning appropriate treatment.

Imaging of vascular cognitive impairment

Vascular cognitive impairment (VCI) is a major health challenge and represents the second most common cause of dementia. We review the updated imaging classification and imaging findings of different subtypes of VCI. We will focus on the magnetic resonance imaging (MRI) markers of each subtype and highlight the role of advanced MR imaging sequences in the evaluation of these patients. Small vessel dementia appears as white matter hyperintensity, lacunae, microinfarcts, and microbleeds. Large vessel dementia includes strategic infarction and multi-infarction dementias. Hypoperfusion dementia can be seen as watershed infarcts and cortical laminar necrosis. Hemorrhagic dementia results from cerebral amyloid angiopathy and cortical superficial siderosis. Hereditary forms of VCI, caused by gene mutations such as CADASIL, should be suspected when dementia presents in young patients. Mixed dementia is seen in patients with Alzheimer's disease and the coexistence of cerebrovascular disease.

Intracranial long-term complications of radiation therapy: an image-based review

BACKGROUND AND PURPOSE

Radiation therapy is commonly utilized in the majority of solid cancers and many hematologic malignancies and other disorders. While it has an undeniably major role in improving cancer survival, radiation therapy has long been recognized to have various negative effects, ranging from mild to severe. In this manuscript, we review several intracranial manifestations of therapeutic radiation, with particular attention to those that may be encountered by radiologists.

METHODS

We conducted an extensive literature review of known complications of intracranial radiation therapy. Based on this review, we selected complications that had salient, recognizable imaging findings. We searched our imaging database for illustrative examples of these complications, focusing only on patients who had a history of intracranial radiation therapy. We then selected cases that best exemplified expected imaging findings in these entities.

RESULTS

Based on our initial literature search and imaging database review, we selected cases of radiation-induced meningioma, radiation-induced glioma, cavernous malformation, enlarging perivascular spaces, leukoencephalopathy, stroke-like migraine after radiation therapy, Moyamoya syndrome, radiation necrosis, radiation-induced labyrinthitis, optic neuropathy, and retinopathy. Although retinopathy is not typically apparent on imaging, it has been included given its clinical overlap with optic neuropathy.

CONCLUSIONS

We describe the clinical and imaging features of selected sequelae of intracranial radiation therapy, with a focus on those most relevant to practicing radiologists. Knowledge of these complications and their imaging findings is important, because radiologists play a key role in early detection of these entities.

Arterial spin labeling and diffusion-weighted MR imaging: Utility in differentiating idiopathic orbital inflammatory pseudotumor from orbital lymphoma

PURPOSE

To assess arterial spin-labeling (ASL) and diffusion-weighted imaging (DWI) and in combination for differentiating between idiopathic orbital inflammatory pseudotumor (IOIP) and orbital lymphoma.

MATERIAL AND METHODS

A retrospective study was done on 37 untreated patients with orbital masses, suspected to be IOIP or orbital lymphoma that underwent ASL and DWI of the orbit. Quantitative measurement of tumor blood flow (TBF) and apparent diffusion coefficient (ADC) of the orbital lesion was done.

RESULTS

There was a significant difference (P = 0.001) in TBF between patients with IOIP (n = 21) (38.1 ± 6.2, 40.3 ± 7.1 ml/100 g/min) and orbital lymphoma (n = 16) (55.5 ± 7.1, 56.8 ± 7.9 ml/100 g/min) for both observers respectively. Thresholds of TBF used for differentiating IOIP from orbital lymphoma were 48, 46 ml/100 g/min revealed area under the curve (AUC) of (0.958 and 0.921), and accuracy of (86% and 83%) for both observers respectively. There was a significant difference (P = 0.001) in ADC between patients with IOIP (1.04 ± 0.19, 1.12 ± 0.23 × 10^-3 mm²/s) and orbital lymphoma (0.69 ± 0.10, 0.72 ± 0.11 × 10^-3 mm²/s) for both observers respectively. Thresholds of ADC used for differentiating IOIP from orbital lymphoma were 0.84 and 0.86 × 10^-3 mm²/s with AUC of (0.933 and 0.920), and accuracy of 89% and 90% for both observers respectively. The combined TBF and ADC used for differentiating IOIP from orbital lymphoma had AUC of (0.973 and 0.970) and accuracy of (91% and 89%) for both observers respectively.

CONCLUSION

TBF and ADC alone and in combination are useful for differentiating IOIP from orbital lymphoma.

Metabolic Imaging of Brain Tumor Recurrence

OBJECTIVE. Diagnosing brain tumor recurrence, especially with changes that occur after treatment, is a challenge. MRI has an exceptional structural resolution, which is important from the perspective of treatment planning. However, its reliability in diagnosing recurrence is relatively lower, when compared to metabolic imaging. The latter is more sensitive to the early changes associated with recurrence and relatively immune to confounding by treatment related changes. CONCLUSION. There is no one-stop shop for the diagnosis of recurrence in brain tumors. The sensitivity of metabolic imaging is not a substitute for the resolution of the MRI, making a multi-modal approach the only way forward.

Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature

Tumor resection followed by chemoradiation remains the current criterion standard treatment for high-grade gliomas. Regardless of aggressive treatment, tumor recurrence and radiation necrosis are 2 different outcomes. Differentiation of tumor recurrence from radiation necrosis remains a critical problem in these patients because of considerable overlap in clinical and imaging presentations. Contrast-enhanced MR imaging is the universal imaging technique for diagnosis, treatment evaluation, and detection of recurrence of high-grade gliomas. PWI and PET with novel radiotracers have an evolving role for monitoring treatment response in high-grade gliomas. In the literature, there is no clear consensus on the superiority of either technique or their complementary information. This review aims to elucidate the diagnostic performance of individual and combined use of functional (PWI) and metabolic (PET) imaging modalities to distinguish recurrence from posttreatment changes in gliomas.

The Utility of Diffusion and Perfusion Magnetic Resonance Imaging in Target Delineation of High-Grade Gliomas

Background

The tumor volume of high-grade glioma (HGG) after surgery is usually determined by contrast-enhanced MRI (CE-MRI), but the clinical target volume remains controversial. Functional magnetic resonance imaging (multimodality MRI) techniques such as magnetic resonance perfusion-weighted imaging (PWI) and diffusion-tensor imaging (DTI) can make up for CE-MRI. This study explored the survival outcomes and failure patterns of patients with HGG by comparing the combination of multimodality MRI and CE-MRI imaging with CE-MRI alone.

Methods

102 patients with postoperative HGG between 2012 and 2016 were included. 50 were delineated based on multimodality MRI (PWI, DTI) and CE-MRI (enhanced T1), and the other 52 were delineated based on CE-MRI as control.

Results

The median survival benefit was 6 months. The 2-year overall survival, progression-free survival, and local-regional control rates were 48% vs. 25%, 42% vs. 13.46%, and 40% vs. 13.46% for the multimodality MRI and CE-MRI cohorts, respectively. The two cohorts had similar rates of disease progression and recurrence but different proportions of failure patterns. The univariate analysis shows that characteristics of patients such as combined with epilepsy, the dose of radiotherapy, the selection of MRI were significant influence factors for 2-year overall survival. However, in multivariate analyses, only the selection of MRI was an independent significant predictor of overall survival.

Conclusions

This study was the first to explore the clinical value of multimodality MRI in the delineation of radiotherapy target volume for HGG. The conclusions of the study have positive reference significance to the combination of multimodality MRI and CE-MRI in guiding the delineation of the radiotherapy target area for HGG patients.

Assessment of Tamoxifen-Related Endometrial Changes in Premenopausal Female Patients With Diffusion-Weighted Magnetic Resonance Imaging

PURPOSE

To evaluate tamoxifen-related endometrial changes in premenopausal female patients with diffusion-weighted magnetic resonance imaging (DWI).

METHODS

This prospective study was performed on 71 premenopausal female patients (mean age, 41 years) who were receiving tamoxifen therapy. All patients underwent magnetic resonance imaging with DWI of the pelvis and hysteroscopic-guided endometrial biopsy. The apparent diffusion coefficient (ADC) values of the endometrial plate were calculated and correlated with pathological results.

RESULTS

The mean ADCs of tamoxifen-related benign endometrial lesions (1.35 ± 0.19 and 1.32 ± 0.13 × 10 mm/s) were significantly higher (P = 0.001) than those of normal endometrial plate (0.95 ± 0.11 and 0.93 ± 0.11 × 10 mm/s) by both reviewers, respectively. The cutoff ADC values used to differentiate tamoxifen-related benign endometrial lesions from normal endometrium were 1.07 and 1.02 × 10 mm/s with areas under the curve of 0.94 and 0.93 and accuracy of 94.4 and 95.8 by both reviewers, respectively. The mean ADC values of endometrial polyp (EP) (1.44 ± 0.19 and 1.42 ± 0.22 × 10 mm/s) were significantly higher (P = 0.001) than those of endometrial hyperplasia (EH) (1.25 ± 0.19 and 1.23 ± 0.19 × 10 mm/s) by both reviewers, respectively. The cutoff ADC values used to differentiate EP from EH were 1.38 × 10 and 1.36 × 10 mm/s with areas under the curve of 0.81 and 0.77 and accuracy of 80% and 70% by both reviewers, respectively. There was an insignificant difference in ADC value between typical and atypical EH. The ADC values of endometrial cancer (0.80 and 0.78 × 10 mm/s) were lower than those of tamoxifen-related benign endometrial lesions. The final diagnosis was normal endometrium (n = 36), benign endometrial lesions either EH (n = 17), or EP (n = 16), and endometrial cancer in only 2 patients.

CONCLUSIONS

We concluded that DWI helps in detection and characterization of different tamoxifen-related endometrial changes in the premenopausal female patients.

Diffusion tensor imaging and electrophysiology as robust assays to evaluate the severity of acute spinal cord injury in rats

Background

Diffusion tensor imaging (DTI) is an effective method to identify subtle changes to normal-appearing white matter (WM). Here we analyzed the DTI data with other examinations, including motor evoked potentials (MEPs), histopathological images, and behavioral results, to reflect the lesion development in different degrees of spinal cord injury (SCI) in acute and subacute stages.

Method

Except for 2 Sprague -Dawley rats which died from the anesthesia accident, the rest 42 female rats were randomized into 3 groups: control group (n = 6), moderate group (n = 18), and severe group (n = 18). Moderate (a 50-g aneurysm clip with 0.4-mm thickness spacer) or severe (a 50-g aneurysm clip with no spacer) contusion SCI at T8 vertebrae was induced. Then the electrophysiological assessments via MEPs, behavioral deterioration via the Basso, Beattie, and Bresnaha (BBB) scores, DTI data, and histopathology examination were analyzed.

Results

In this study, we found that the damage of WM myelin, MEPs amplitude, BBB scores and the decreases in the values of fractional anisotropy (FA) and axial diffusivity (AD) were more obvious in the severe injury group than those of the moderate group. Additionally, the FA and AD values could identify the extent of SCI in subacute and early acute SCI respectively, which was reflected in a robust correlations with MEPs and BBB scores. While the values of radial diffusivity (RD) showed no significant changes.

Conclusions

Our data confirmed that DTI was a valuable in ex vivo imaging tool to identify damaged white matter tracts after graded SCI in rat, which may provide useful information for the early identification of the severity of SCI.

Association of dynamic susceptibility magnetic resonance imaging at initial tumor diagnosis with the prognosis of different molecular glioma subtypes

Purpose

The updated 2016 CNS World Health Organization classification differentiates three main groups of diffuse glioma according to their molecular characteristics: astrocytic tumors with and without isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deleted oligodendrogliomas. The present study aimed to determine whether dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is an independent prognostic marker within the molecular subgroups of diffuse glioma.

Methods

Fifty-six patients with treatment-naive gliomas and advanced preoperative MRI examination were assessed retrospectively. The mean and maximal normalized cerebral blood volume values from DSC-MRI within the tumors were measured. Optimal cutoff values for the 1-year progression-free survival (PFS) were defined, and Kaplan-Meier analyses were performed separately for the three glioma subgroups.

Results

IDH wild-type astrocytic tumors had a higher mean and maximal perfusion than IDH-mutant astrocytic tumors and oligodendrogliomas. Patients with IDH wild-type astrocytic tumors and a low mean or maximal perfusion had a significantly shorter PFS than patients of the same group with high perfusion (p = 0.0159/0.0112). Furthermore, they had a significantly higher risk for early progression (hazard ratio = 5.6/5.1). This finding was independent of the methylation status of O6-methylguanin-DNA-methyltransferase and variations of the therapy. Within the groups of IDH-mutant astrocytic tumors and oligodendrogliomas, the PFS of low and highly perfused tumors did not differ.

Conclusion

High perfusion upon initial diagnosis is not compellingly associated with worse short-term prognosis within the different molecular subgroups of diffuse glioma. Particularly, the overall highly perfused group of IDH wild-type astrocytic tumors contains tumors with low perfusion but unfavorable prognosis.

Diffusion Tensor Imaging of Microstructural Changes in the Gray and White Matter in Patients With Crigler-Najjar Syndrome Type I

PURPOSE

This study aimed to evaluate the role of diffusion tensor imaging of microstructural changes in gray and white matter in Crigler-Najjar syndrome type I.

PATIENT AND METHODS

A prospective study was conducted on 10 patients with Crigler-Najjar syndrome type I and 10 age- and sex-matched children who underwent diffusion tensor imaging of the brain. Mean diffusivity (MD) and fractional anisotropy (FA) of gray and white matter were measured.

RESULTS

There was a significantly higher MD of the gray matter regions including the globus pallidus, thalamus, caudate head, substantia nigra, and dentate nucleus in patients versus controls (P = 0.007, 0.001, 0.014, 0.003, and 0.002), respectively. The areas under the curve (AUC) of MD of the globus pallidus and thalamus used to differentiate patients from controls were 0.93 and 0.925, respectively. There was a significant difference in MD of the frontal white matter and posterior limb of the internal capsule in patients versus controls (P = 0.001 and 0.02), respectively. The AUCs of MD of these regions used to differentiate patients from controls were 0.82 and 0.8. There was a significant difference in FA of the frontal white matter and posterior limb of the internal capsule in patients versus controls (P = 0.006 and 0.006), respectively. The AUCs of FA of these regions were 0.83 and 0.85, respectively. The MD of the globus pallidus correlated with serum bilirubin (r = 0.87 and P = 0.001).

CONCLUSION

Diffusion tensor imaging can detect microstructural changes of deep gray matter and some regions of white matter in Crigler-Najjar syndrome type I.

Imaging of Neuronal and Mixed Glioneuronal Tumors

Neuronal and mixed glioneuronal tumors represent a group of neoplasms with varying degrees of neural and glial elements. Their age of presentation varies, but they are most commonly seen in children and young adults. With the exception of anaplastic ganglioglioma and other atypical variants, most lesions are low grade; however, they can have significant morbidity because of seizures, mass effect, or difficult to treat hydrocephalus. Although many tumors show overlapping clinical and imaging features, some have relatively distinctive imaging characteristics that may aid in narrowing the differential diagnosis. In this review, we discuss relevant clinical and pathologic characteristics of these tumors and provide an overview of conventional and advanced imaging features that provide clues as to the diagnosis.

Differentiation of Treatment-Related Effects from Glioma Recurrence Using Machine Learning Classifiers Based Upon Pre-and Post-Contrast T1WI and T2 FLAIR Subtraction Features: A Two-Center Study

Purpose

We propose three support vector machine (SVM) classifiers, using pre-and post-contrast T2 fluid-attenuated inversion recovery (FLAIR) subtraction and/or pre-and post-contrast T1WI subtraction, to differentiate treatment-related effects (TRE) from glioma recurrence.

Materials and Methods

Fifty-six postoperative high-grade glioma patients with suspicious progression after radiotherapy and chemotherapy from two centers were studied. Pre-and post-contrast T1WI and T2 FLAIR were collected. Each pre-contrast image was voxel-wise subtracted from the co-registered post-contrast image. Dataset was randomly split into training, and testing on a 7:3 ratio, accordingly subjected to a five fold cross validation. Best feature subsets were selected by Pearson correlation coefficient and recursive feature elimination, whereupon a radiomics classifier was built with SVM. The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV).

Results

In all, 186 features were extracted on each subtraction map. Top nine T1WI subtraction features, top thirteen T2 FLAIR subtraction features and top thirteen combination features were selected to build optimal SVM classifiers accordingly. The accuracies/AUCs/sensitivity/specificity/PPV/NPV of SVM based on sole T1WI subtraction were 80.00%/80.00% (CI: 0.5370–1.0000)/100%/70.00%/62.50%/100%. Those results of SVM based on sole T2 FLAIR subtraction were 86.67%/84.00% (CI: 0.5962–1.0000)/100%/80%/71.43%/100%. Those results of SVM based on both T1WI subtraction and T2 FLAIR subtraction were 93.33%/94.00% (CI: 0.7778–1.0000)/100%/90%/83.33%/100%, respectively.

Conclusion

Pre- and post-contrast T2 FLAIR subtraction provided added value for diagnosis between recurrence and TRE. SVM based on a combination of T1WI and T2 FLAIR subtraction maps was superior to the sole use of T1WI or T2 FLAIR for differentiating TRE from recurrence. The SVM classifier based on combination of pre-and post-contrast subtraction T2 FLAIR and T1WI imaging allowed for the accurate differential diagnosis of TRE from recurrence, which is of paramount importance for treatment management of postoperative glioma patients after radiation therapy.

Imaging of Fulminant Demyelinating Disorders of the Central Nervous System

We aim to review the imaging appearance of fulminant demyelinating disorders of central nervous system that have different pathological features, clinical course, clinical features, and imaging findings different from classic multiple sclerosis. Routine magnetic resonance imaging (MRI) can help in accurate localization of the lesions, detection of associated lesions, and monitoring of these patients. Advanced MRI combined with routine MRI can aid in differentiation fulminant demyelinating lesions from simulating malignancy. Tumefactive demyelination lesions are located in supratentorial white matter mainly frontal and parietal regions with incomplete rim enhancement. Baló concentric sclerosis shows characteristic concentric onion skin appearance. Schilder disease is subacute or acute demyelinating disorders with one or more lesions commonly involving the centrum semiovale. Marburg disease is the most severe demyelinating disorder with diffuse infiltrative lesions and massive edema involving both the cerebral hemisphere and brain stem.

Liver Imaging Reporting and Data System Version 2018: What Radiologists Need to Know. J Comput Assist Tomogr. 2020;44:168-177. [PMID: 32195795 DOI: 10.1097/rct.0000000000000995]

In this article, we aim to review Liver Imaging Reporting and Data System version 18 (LI-RADS v2018). Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. Liver Imaging Reporting and Data System developed for standardizing interpreting, reporting, and data collection of HCC describes 5 major features for accurate HCC diagnosis and several ancillary features, some favoring HCC in particular or malignancy in general and others favoring benignity. Untreated hepatic lesions LI-RADS affords 8 unique categories based on imaging appearance on computed tomography and magnetic resonance imaging, which indicate the possibility of HCC or malignancy with or without tumor in vein. Furthermore, LI-RADS defines 4 treatment response categories for treated HCCs after different locoregional therapy. These continuous recent updates on LI-RADS improve the communication between the radiologists and the clinicians for better management and patient outcome.

Accuracy of apparent diffusion coefficient values and magnetic resonance imaging in differentiating suprasellar germinomas from chiasmatic/hypothalamic gliomas

OBJECTIVE

The aim of this study was to differentiate suprasellar germinomas from chiasmatic/hypothalamic gliomas (CHGs) using apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI) characteristics.

MATERIALS AND METHODS

A cross-sectional study was conducted on 11 patients with suprasellar germinomas and 11 patients with CHGs who underwent pretreatment MRI. The ADC values (minimum and average ADC values) of the tumors were measured and the MRI characteristics were evaluated.

RESULTS

The average and minimum ADC values of suprasellar germinomas were significantly lower than those of CHGs (p = 0.016 and 0.004 respectively). The selection of 941.15 × 10^-6 mm²/s as a cutoff value of the minimum ADC value was used to differentiate suprasellar germinomas and CHGs; the best results were obtained with area under the curve of 0.889, sensitivity of 87.5%, specificity of 77.8% and accuracy of 82.4%. MRI characteristics suggested the diagnosis of suprasellar germinomas were T2W hypointensity and involvement of pituitary gland and/or stalk. MRI characteristics suggested the diagnosis of CHGs was higher degree of contrast enhancement and presence of macrocysts.

CONCLUSION

ADC values have a role in differentiating suprasellar germinomas and CHGs, especially when imaging findings on conventional MRI are inconclusive. Furthermore, some MRI features are in favor of differentiation between these tumor entities including tumor location, cyst pattern, T2W hypointensity, degree of contrast enhancement, stalk and pituitary gland involvement.

Brain metastases treated with radiosurgery or hypofractionated stereotactic radiotherapy: outcomes and predictors of survival

INTRODUCTION

To assess treatment outcome and prognostic factors associated with prolonged survival in patients with brain metastases (BM) treated with stereotactic radiosurgery (SRS) or hypofractionated stereotactic radiotherapy (HFSRT).

METHODS/PATIENTS

This study retrospectively reviewed 200 patients with 324 BM treated with one fraction (15-21 Gy) or 5-10 fractions (25-40 Gy) between January 2010 and August 2016. 26.5% of patients received whole brain radiotherapy (WBRT) and 25% initial surgery. Demographics, prognostic scales, systemic and local controls, patterns of relapse and rescue, toxicity, and cause of death were analyzed. A stratified analysis by primary tumor was done.

RESULTS

Median overall survival (OS) was 8 months from SRS/HFSRT. Breast cancer patients had a median OS of 17 months, followed by renal (11 months), lung (8 months), colorectal (5 months), and melanoma (4 months). The univariate analysis showed improved OS in females (p 0.004), RPA I-II (p < 0.001) initial surgery (p < 0.001), absence of extracranial disease (p 0.023), and good disease control (p 0.002). There were no differences in OS or local control between SRS and HFSRT or in patients receiving WBRT. Among 44% of brain recurrences, 11% were in field. 174 patients died, 10% from confirmed intracranial progression.

CONCLUSIONS

SRS and HSFRT are equally effective and safe for the treatment of BM, with no exceptions among different primary tumors. Disease control, surgery, age, and prognostic scales correlated with OS. However, the lack of survival benefit regarding WBRT might become logical evidence for its omission in a subset of patients.

Multi-parametric arterial spin labelling and diffusion-weighted magnetic resonance imaging in differentiation of grade II and grade III gliomas

Purpose

To assess arterial spin labelling (ASL) perfusion and diffusion MR imaging (DWI) in the differentiation of grade II from grade III gliomas.

Material and methods

A prospective cohort study was done on 36 patients (20 male and 16 female) with diffuse gliomas, who underwent ASL and DWI. Diffuse gliomas were classified into grade II and grade III. Calculation of tumoural blood flow (TBF) and apparent diffusion coefficient (ADC) of the tumoral and peritumoural regions was made. The ROC curve was drawn to differentiate grade II from grade III gliomas.

Results

There was a significant difference in TBF of tumoural and peritumoural regions of grade II and III gliomas (p = 0.02 and p =0.001, respectively). Selection of 26.1 and 14.8 ml/100 g/min as the cut-off for TBF of tumoural and peritumoural regions differentiated between both groups with area under curve (AUC) of 0.69 and 0.957, and accuracy of 77.8% and 88.9%, respectively. There was small but significant difference in the ADC of tumoural and peritumoural regions between grade II and III gliomas (p = 0.02 for both). The selection of 1.06 and 1.36 × 10^-3 mm²/s as the cut-off of ADC of tumoural and peritumoural regions was made, to differentiate grade II from III with AUC of 0.701 and 0.748, and accuracy of 80.6% and 80.6%, respectively. Combined TBF and ADC of tumoural regions revealed an AUC of 0.808 and accuracy of 72.7%. Combined TBF and ADC for peritumoural regions revealed an AUC of 0.96 and accuracy of 94.4%.

Conclusion

TBF and ADC of tumoural and peritumoural regions are accurate non-invasive methods of differentiation of grade II from grade III gliomas.

Interobserver Agreement of Magnetic Resonance Imaging of Liver Imaging Reporting and Data System Version 2018. J Comput Assist Tomogr. 2020;44:118-123. [PMID: 31939892 DOI: 10.1097/rct.0000000000000945]

AIM

This study aimed to assess the interobserver agreement of magnetic resonance (MR) imaging of Liver Imaging Reporting and Data System version 2018 (LI-RADS v2018).

SUBJECTS AND METHODS

Retrospective analysis was done for 119 consecutive patients (77 male and 42 female) at risk of hepatocellular carcinoma who underwent dynamic contrast MR imaging. Image analysis was done by 2 independent and blinded readers for arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, and size. Hepatic lesions were classified into 7 groups according to LI-RADS v2018.

RESULTS

There was excellent interobserver agreement of both reviewers for LR version 4 (κ = 0.887, P = 0.001) with 90.76% agreement. There was excellent interobserver agreement for nonrim arterial phase hyperenhancement (κ = 0.948; 95% confidence interval [CI], 0.89-0.99; P = 0.001), washout appearance (κ = 0.949; 95% CI, 0.89-1.0; P = 0.001); and enhancing capsule (κ = 0.848; 95% CI, 0.73-0.97; P = 0.001) and excellent reliability of size (interclass correlation, 0.99; P = 0.001). There was excellent interobserver agreement for LR-1 (κ = 1.00, P = 0.001), LR-2 (κ = 0.94, P = 0.001), LR-5 (κ = 0.839, P = 0.001), LR-M (κ = 1.00, P = 0.001), and LR-TIV (κ = 1.00; 95% CI, 1.0-1.0; P = 0.001), and good agreement for LR-3 (κ = 0.61, P = 0.001) and LR-4 (κ = 0.61, P = 0.001).

CONCLUSION

MR imaging of LI-RADS v2018 is a reliable imaging modality and reporting system that may be used for standard interpretation of hepatic focal lesions.

Arterial spin labeling imaging correlates with the angiographic and clinical vascularity of vestibular schwannomas

PURPOSE

Hypervascular vestibular schwannomas (HVSs) are a type of the vestibular schwannomas (VSs) that are extremely difficult to remove. We examined whether HVSs can be predicted by using arterial spin labeling (ASL) imaging.

METHODS

A total of 103 patients with VSs underwent ASL imaging and digital subtraction angiography (DSA) before surgery. Regional cerebral blood flow (CBF) of gray matter and regional tumor blood flow (TBF) were calculated from ASL imaging, and we defined the ratio of TBF to CBF as the relative TBF (rTBF = TBF/CBF). Angiographic vascularity was evaluated by DSA, and clinical vascularity was evaluated by the degree of intraoperative tumor bleeding. Based on the angiographic and clinical vascularity, the VSs were divided into two categories: HVS and non-HVS. We compared rTBF with angiographic and clinical vascularities, retrospectively.

RESULTS

The mean rTBFs of angiographic non-HVSs and HVSs were 1.29 and 2.58, respectively (p < 0.0001). At a cutoff value of 1.55, the sensitivity and specificity were 93.9% and 72.9%, respectively. The mean rTBFs of clinical non-HVS and HVSs were 1.45 and 2.22, respectively (p = 0.0002). At a cutoff value of 1.55, the sensitivity and specificity were 79.4% and 66.7%, respectively.

CONCLUSION

The rTBF calculated from ASL imaging correlates well with tumor vascularity and may be useful for predicting HVSs before surgery.

Differentiation of Recurrence from Radiation Necrosis in Gliomas Based on the Radiomics of Combinational Features and Multimodality MRI Images

Purpose

To classify radiation necrosis versus recurrence in glioma patients using a radiomics model based on combinational features and multimodality MRI images.

Methods

Fifty-one glioma patients who underwent radiation treatments after surgery were enrolled in this study. Sixteen patients revealed radiation necrosis while 35 patients showed tumor recurrence during the follow-up period. After treatment, all patients underwent T1-weighted, T1-weighted postcontrast, T2-weighted, and fluid-attenuated inversion recovery scans. A total of 41,284 handcrafted and 24,576 deep features were extracted for each patient. The 0.623 + bootstrap method and the area under the curve (denoted as 0.632 + bootstrap AUC) metric were used to select the features. The stepwise forward method was applied to construct 10 logistic regression models based on different combinations of image features.

Results

For handcrafted features on multimodality MRI, model 7 with seven features yielded the highest AUC of 0.9624, sensitivity of 0.8497, and specificity of 0.9083 in the validation set. These values were higher than the accuracy of using handcrafted features on single-modality MRI (paired t-test, p < 0.05, except sensitivity). For combined handcrafted and AlexNet features on multimodality MRI, model 6 with six features achieved the highest AUC of 0.9982, sensitivity of 0.9941, and specificity of 0.9755 in the validation set. These values were higher than the accuracy of using handcrafted features on multimodality MRI (paired t-test, p < 0.05).

Conclusions

Handcrafted and deep features extracted from multimodality MRI images reflecting the heterogeneity of gliomas can provide useful information for glioma necrosis/recurrence classification.

Diffusion tensor imaging of white matter integrity in relation to smoking index and exacerbations in severe chronic obstructive pulmonary disease

Background

Diffusion tensor imaging (DTI) is a non-invasive MR modality that provides an evaluation of brain tissue microstructure and architecture in vivo. We aimed to assess the diagnostic value of DTI parameters in evaluating cerebral white matter integrity in patients of severe chronic obstructive pulmonary disease (COPD) and correlate these parameters with smoking index (SI) and the number of exacerbations in the last year.

This prospective study included 30 COPD male past smoker patients and 15 age- and sex-matched nonsmoker controls. Staging of COPD, SI and number of exacerbations in the last year were obtained. Routine brain MRI and DTI were done in all subjects. The selected white matter tracts’ fractional anisotropy (FA), and mean diffusivity (MD) were calculated in the region of interest in axial slices.

Results

The mean FA and MD values of all selected white matter tracts showed a high significant difference (p < 0.001) between patients and control group. The correlation between FA, SI and exacerbation frequency was not significant in the majority of white matter tracts (p > 0.05). The correlation between MD, SI and exacerbation frequency was significant for the majority of tracts (p < 0.05).

Conclusion

DTI metrics are valuable non-invasive tools in evaluating the white matter abnormalities in COPD patients. Smoking index and frequency of exacerbations have possible relation to extra-pulmonary cerebral manifestations of COPD.