Integrating standard epilepsy protocol, ASL-perfusion, MP2RAGE/EDGE and the MELD-FCD classifier in the detection of subtle epileptogenic lesions: a 3 Tesla MRI pilot study.

BACKGROUND: Malformations of cortical development (MCDs) in children with focal epilepsy pose significant diagnostic challenges, and a precise radiological diagnosis is crucial for surgical planning. New MRI sequences and the use of artificial intelligence (AI) algorithms are considered very promising in this regard, yet studies evaluating the relative contribution of each diagnostic technique are lacking. METHODS: The study was conducted using a dedicated "EPI-MCD MR protocol" with a 3 Tesla MRI scanner in patients with focal epilepsy and previously negative MRI. MRI sequences evaluated included 3D FLAIR, 3D T1 MPRAGE, T2 Turbo Spin Echo (TSE), 3D T1 MP2RAGE, and Arterial Spin Labelling (ASL). Two paediatric neuroradiologists scored each sequence for localisation and extension of the lesion. The MELD-FCD AI classifier's performance in identifying pathological findings was also assessed. We only included patients where a diagnosis of MCD was subsequently confirmed on histology and/or sEEG. RESULTS: The 3D FLAIR sequence showed the highest yield in detecting epileptogenic lesions, with 3D T1 MPRAGE, T2 TSE, and 3D T1 MP2RAGE sequences showing moderate to low yield. ASL was the least useful. The MELD-FCD classifier achieved a 69.2% true positive rate. In one case, MELD identified a subtle area of cortical dysplasia overlooked by the neuroradiologists, changing the management of the patient. CONCLUSIONS: The 3D FLAIR sequence is the most effective in the MRI-based diagnosis of subtle epileptogenic lesions, outperforming other sequences in localisation and extension. This pilot study emphasizes the importance of careful assessment of the value of additional sequences.

Evaluation of epilepsy lesion visualisation enhancement in low-field MRI using image quality transfer: a preliminary investigation of clinical potential for applications in developing countries.

PURPOSE: Low-field (LF) MRI scanners are common in many Low- and middle-Income countries, but they provide images with worse spatial resolution and contrast than high-field (HF) scanners. Image Quality Transfer (IQT) is a machine learning framework to enhance images based on high-quality references that has recently adapted to LF MRI. In this study we aim to assess if it can improve lesion visualisation compared to LF MRI scans in children with epilepsy. METHODS: T1-weighted, T2-weighted and FLAIR were acquired from 12 patients (5 to 18 years old, 7 males) with clinical diagnosis of intractable epilepsy on a 0.36T (LF) and a 1.5T scanner (HF). LF images were enhanced with IQT. Seven radiologists blindly evaluated the differentiation between normal grey matter (GM) and white matter (WM) and the extension and definition of epileptogenic lesions in LF, HF and IQT-enhanced images. RESULTS: When images were evaluated independently, GM-WM differentiation scores of IQT outputs were 26% higher, 17% higher and 12% lower than LF for T1, T2 and FLAIR. Lesion definition scores were 8-34% lower than LF, but became 3% higher than LF for FLAIR and T1 when images were seen side by side. Radiologists with expertise at HF scored IQT images higher than those with expertise at LF. CONCLUSION: IQT generally improved the image quality assessments. Evaluation of pathology on IQT-enhanced images was affected by familiarity with HF/IQT image appearance. These preliminary results show that IQT could have an important impact on neuroradiology practice where HF MRI is not available.

Comprehensive Brain Tumour Characterisation with VERDICT-MRI: Evaluation of Cellular and Vascular Measures Validated by Histology.

The aim of this work was to extend the VERDICT-MRI framework for modelling brain tumours, enabling comprehensive characterisation of both intra- and peritumoural areas with a particular focus on cellular and vascular features. Diffusion MRI data were acquired with multiple b-values (ranging from 50 to 3500 s/mm2), diffusion times, and echo times in 21 patients with brain tumours of different types and with a wide range of cellular and vascular features. We fitted a selection of diffusion models that resulted from the combination of different types of intracellular, extracellular, and vascular compartments to the signal. We compared the models using criteria for parsimony while aiming at good characterisation of all of the key histological brain tumour components. Finally, we evaluated the parameters of the best-performing model in the differentiation of tumour histotypes, using ADC (Apparent Diffusion Coefficient) as a clinical standard reference, and compared them to histopathology and relevant perfusion MRI metrics. The best-performing model for VERDICT in brain tumours was a three-compartment model accounting for anisotropically hindered and isotropically restricted diffusion and isotropic pseudo-diffusion. VERDICT metrics were compatible with the histological appearance of low-grade gliomas and metastases and reflected differences found by histopathology between multiple biopsy samples within tumours. The comparison between histotypes showed that both the intracellular and vascular fractions tended to be higher in tumours with high cellularity (glioblastoma and metastasis), and quantitative analysis showed a trend toward higher values of the intracellular fraction (fic) within the tumour core with increasing glioma grade. We also observed a trend towards a higher free water fraction in vasogenic oedemas around metastases compared to infiltrative oedemas around glioblastomas and WHO 3 gliomas as well as the periphery of low-grade gliomas. In conclusion, we developed and evaluated a multi-compartment diffusion MRI model for brain tumours based on the VERDICT framework, which showed agreement between non-invasive microstructural estimates and histology and encouraging trends for the differentiation of tumour types and sub-regions.

Low-field magnetic resonance image enhancement via stochastic image quality transfer.

Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher income countries e.g. for small child patients with obesity, claustrophobia, implants, or tattoos. However, low-field MR images commonly have lower resolution and poorer contrast than images from high field (1.5T, 3T, and above). Here, we present Image Quality Transfer (IQT) to enhance low-field structural MRI by estimating from a low-field image the image we would have obtained from the same subject at high field. Our approach uses (i) a stochastic low-field image simulator as the forward model to capture uncertainty and variation in the contrast of low-field images corresponding to a particular high-field image, and (ii) an anisotropic U-Net variant specifically designed for the IQT inverse problem. We evaluate the proposed algorithm both in simulation and using multi-contrast (T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR)) clinical low-field MRI data from an LMIC hospital. We show the efficacy of IQT in improving contrast and resolution of low-field MR images. We demonstrate that IQT-enhanced images have potential for enhancing visualisation of anatomical structures and pathological lesions of clinical relevance from the perspective of radiologists. IQT is proved to have capability of boosting the diagnostic value of low-field MRI, especially in low-resource settings.

Combining Multi-Shell Diffusion with Conventional MRI Improves Molecular Diagnosis of Diffuse Gliomas with Deep Learning.

The WHO classification since 2016 confirms the importance of integrating molecular diagnosis for prognosis and treatment decisions of adult-type diffuse gliomas. This motivates the development of non-invasive diagnostic methods, in particular MRI, to predict molecular subtypes of gliomas before surgery. At present, this development has been focused on deep-learning (DL)-based predictive models, mainly with conventional MRI (cMRI), despite recent studies suggesting multi-shell diffusion MRI (dMRI) offers complementary information to cMRI for molecular subtyping. The aim of this work is to evaluate the potential benefit of combining cMRI and multi-shell dMRI in DL-based models. A model implemented with deep residual neural networks was chosen as an illustrative example. Using a dataset of 146 patients with gliomas (from grade 2 to 4), the model was trained and evaluated, with nested cross-validation, on pre-operative cMRI, multi-shell dMRI, and a combination of the two for the following classification tasks: (i) IDH-mutation; (ii) 1p/19q-codeletion; and (iii) three molecular subtypes according to WHO 2021. The results from a subset of 100 patients with lower grades gliomas (2 and 3 according to WHO 2016) demonstrated that combining cMRI and multi-shell dMRI enabled the best performance in predicting IDH mutation and 1p/19q codeletion, achieving an accuracy of 75 ± 9% in predicting the IDH-mutation status, higher than using cMRI and multi-shell dMRI separately (both 70 ± 7%). Similar findings were observed for predicting the 1p/19q-codeletion status, with the accuracy from combining cMRI and multi-shell dMRI (72 ± 4%) higher than from each modality used alone (cMRI: 65 ± 6%; multi-shell dMRI: 66 ± 9%). These findings remain when we considered all 146 patients for predicting the IDH status (combined: 81 ± 5% accuracy; cMRI: 74 ± 5%; multi-shell dMRI: 73 ± 6%) and for the diagnosis of the three molecular subtypes according to WHO 2021 (combined: 60 ± 5%; cMRI: 57 ± 8%; multi-shell dMRI: 56 ± 7%). Together, these findings suggest that combining cMRI and multi-shell dMRI can offer higher accuracy than using each modality alone for predicting the IDH and 1p/19q status and in diagnosing the three molecular subtypes with DL-based models.

A framework for advancing sustainable magnetic resonance imaging access in Africa.

Magnetic resonance imaging (MRI) technology has profoundly transformed current healthcare systems globally, owing to advances in hardware and software research innovations. Despite these advances, MRI remains largely inaccessible to clinicians, patients, and researchers in low-resource areas, such as Africa. The rapidly growing burden of noncommunicable diseases in Africa underscores the importance of improving access to MRI equipment as well as training and research opportunities on the continent. The Consortium for Advancement of MRI Education and Research in Africa (CAMERA) is a network of African biomedical imaging experts and global partners, implementing novel strategies to advance MRI access and research in Africa. Upon its inception in 2019, CAMERA sets out to identify challenges to MRI usage and provide a framework for addressing MRI needs in the region. To this end, CAMERA conducted a needs assessment survey (NAS) and a series of symposia at international MRI society meetings over a 2-year period. The 68-question NAS was distributed to MRI users in Africa and was completed by 157 clinicians and scientists from across Sub-Saharan Africa (SSA). On average, the number of MRI scanners per million people remained at less than one, of which 39% were obsolete low-field systems but still in use to meet daily clinical needs. The feasibility of coupling stable energy supplies from various sources has contributed to the growing number of higher-field (1.5 T) MRI scanners in the region. However, these systems are underutilized, with only 8% of facilities reporting clinical scans of 15 or more patients per day, per scanner. The most frequently reported MRI scans were neurological and musculoskeletal. The CAMERA NAS combined with the World Health Organization and International Atomic Energy Agency data provides the most up-to-date data on MRI density in Africa and offers a unique insight into Africa's MRI needs. Reported gaps in training, maintenance, and research capacity indicate ongoing challenges in providing sustainable high-value MRI access in SSA. Findings from the NAS and focused discussions at international MRI society meetings provided the basis for the framework presented here for advancing MRI capacity in SSA. While these findings pertain to SSA, the framework provides a model for advancing imaging needs in other low-resource settings.

Erratum: Magnetic resonance imaging monitoring therapeutic response to dendritic cell vaccine in murine orthotopic pancreatic cancer models.

[This corrects the article on p. 562 in vol. 9, PMID: 30949410.].

Transcatheter Intraarterial Perfusion MRI Approaches to Differentiate Reversibly Electroporated Penumbra From Irreversibly Electroporated Zones in Rabbit Liver.

RATIONALE AND OBJECTIVES: To investigate whether transcatheter intraarterial perfusion (TRIP) magnetic resonance imaging (MRI) can differentiate reversible electroporation (RE) zones from irreversible electroporation (IRE) zones immediately after IRE procedure in the rabbit liver. MATERIALS AND METHODS: All studies were approved by the institutional animal care and use committee and performed in accordance with institutional guidelines. A total of 13 healthy New Zealand White rabbits were used. After selective catheterization of the hepatic artery under X-ray fluoroscopy, we acquired TRIP-MRI at 20 minutes post-IRE using 3 mL of 5% intraarterial gadopentetate dimeglumine. Semi-quantitative (peak enhancement, PE; time to peak, TTP; wash-in slope, WIS; areas under the time-intensity curve, AUT, over 30, 60, 90, 120, 150, and 180 seconds after the initiation of enhancement) and quantitative (Ktrans, ve, and vp) TRIP-MRI parameters were calculated. The relationships between TRIP-MRI parameters and histological measurements and the differential ability of TRIP-MRI parameters was assessed. RESULTS: PE, AUT60, AUT90, AUT120, AUT150, AUT180, Ktrans, and ve were significantly higher in RE zones than in IRE zones (all P < 0.05), and AUC for these parameters ranged from 0.91(95% CI, 0.80, 1.00) to 0.99 (95% CI, 0.98, 1.00). There was no significant difference in AUC between any two parameters (Z, 0-1.47; P, 0.14-1.00). Hepatocyte apoptosis strongly correlated with PE, AUT60, AUT90, AUT120, AUT150, AUT180, Ktrans, and vp (the absolute value r, 0.6-0.7, all P < 0.0001). CONCLUSION: AUT150 or AUT180 could be a potential imaging biomarker to differentiate RE from IRE zones, and TRIP-MRI permits to differentiate RE from IRE zones immediately after IRE procedure in the rabbit liver.

Prophylactic dendritic cell vaccination controls pancreatic cancer growth in a mouse model.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths with high recurrence after surgery due to a paucity of effective post-surgical adjuvant treatments. DC vaccines can activate multiple anti-tumor immune responses but have not been explored for post-surgery PDAC recurrence. Intraperitoneal (IP) delivery may allow increased DC vaccine dosage and migration to lymph nodes. Here, we investigated the role of prophylactic DC vaccination controlling PDAC tumor growth with IP delivery as an administration route for DC vaccination. METHODS: DC vaccines were generated using ex vivo differentiation and maturation of bone marrow-derived precursors. Twenty mice were divided into four groups (n = 5) and treated with DC vaccines, unpulsed mature DCs, Panc02 lysates or no treatment. After tumor induction, mice underwent three magnetic resonance imaging scans to track tumor growth. Apparent diffusion coefficient (ADC), a quantitative magnetic resonance imaging measurement of tumor microstructure, was calculated. Survival was tracked. Tumor tissue was collected after death and stained with hematoxylin and eosin, Masson's trichrome, terminal deoxynucleotidyl transferase dUTP nick end labeling and anti-CD8 stains for histology. RESULTS: DC-vaccinated mice demonstrated stronger anti-tumor cytotoxicity compared with control groups on lactate dehydrogenase assay. DC vaccine mice also demonstrated decreased tumor volume, prolonged survival and increased ΔADC compared with control groups. On histology, the DC vaccine group had increased apoptosis, increased CD8+ T cells and decreased collagen. ΔADC negatively correlated with % collagen in tumor tissues. DISCUSSION: Prophylactic DC vaccination may inhibit PDAC tumor growth during recurrence and prolong survival. ΔADC may be a potential imaging biomarker that correlates with tumor histological features.

Transcatheter intra-arterial perfusion (TRIP)-MRI biomarkers help detect immediate response to irreversible electroporation of rabbit VX2 liver tumor.

PURPOSE: Irreversible electroporation (IRE) is a nonthermal tissue ablation technique that represents a promising treatment option for unresectable liver tumors, but the effectively treated zone cannot be reliably predicted. We investigate the potential benefit of transcatheter intra-arterial perfusion (TRIP) -MRI for the early noninvasive differentiation of IRE zone from surrounding reversibly electroporated (RE) zone. METHODS: Seventeen rabbits with VX2 liver tumors were scanned with morphological and contrast-enhanced MRI sequences approximately 30 min after IRE tumor ablation. Quantitative TRIP-MRI perfusion parameters were evaluated in IRE zone and RE zone, defined according to histology. MRI and histology results were compared among zones using Wilcoxon rank-sum tests and correlations were evaluated by Pearson's correlation coefficient. RESULTS: There were significant differences in area under the curve, time to peak, maximum and late enhancement, wash-in and wash-out rates in the tumor IRE zones compared with the boundary tumor RE zones and untreated tumors. Histology showed significantly fewer tumor cells, microvessels and significantly more apoptosis in tumor IRE zones compared with tumor RE zones (-51%, -66% and +185%, respectively) and untreated tumors (-60%, -67%, and +228%, respectively). A strong correlation was observed between MRI and histology measurements of IRE zones (r = 0.948) and RE zones (r = 0.951). CONCLUSION: TRIP-MRI demonstrated the potential to detect immediate perfusion changes following IRE liver tumor ablation and effectively differentiate the IRE zone from the surrounding tumor RE zone.

Diffusion-Weighted MR Imaging to Evaluate Immediate Response to Irreversible Electroporation in a Rabbit VX2 Liver Tumor Model.

PURPOSE: To evaluate the feasibility of diffusion-weighted imaging (DWI) in magnetic resonance imaging for quantitative measurement of responses following irreversible electroporation (IRE) in a rabbit liver tumor model. MATERIALS AND METHODS: Twelve rabbits underwent ultrasound-guided VX2 tumor implantation in the left medial and left lateral liver lobes. The tumors in the left medial lobe were treated with IRE, whereas those in the left lateral lobe served as internal controls. DWI was performed before and immediately after IRE. Tumors were then harvested for histopathologic staining. The apparent diffusion coefficient (ADC) and change in ADC (ΔADC) were calculated based on DWI. Tumor apoptosis index (AI) was assessed by terminal deoxynucleotidyl transferase dUTP nick-end labeling. These measurements from DWI and histopathology were compared between untreated and treated tumors. RESULTS: The ADC values, ΔADC, and AI showed statistically significant differences between treated and untreated tumors (P < .05 for all). ADC values were higher in treated tumors than in untreated tumors (1.08 × 10-3 mm2/s ± 0.15 vs 0.88 × 10-3 mm2/s ± 0.19; P = .042). CONCLUSIONS: DWI can be used to quantitatively evaluate treatment response in liver tumors immediately after IRE.

Microstructural characterization of corticospinal tract in subacute and chronic stroke patients with distal lesions by means of advanced diffusion MRI.

PURPOSE: The aim of the paper is to evaluate if advanced dMRI techniques, including diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI), could provide novel insights into the subtle microarchitectural modifications occurring in the corticospinal tract (CST) of stroke patients in subacute and chronic phases. METHODS: Seventeen subjects (age 68 ± 11 years) in the subacute phase (14 ± 3 days post-stroke), 10 of whom rescanned in the chronic phase (231 ± 36 days post-stroke), were enrolled. Images were acquired using a 3-T MRI scanner with a two-shell EPI protocol (20 gradient directions, b = 700 s/mm2, 3 b = 0; 64 gradient directions, b = 2000 s/mm2, 9 b = 0). DTI-, DKI-, and NODDI-derived parameters were calculated in the posterior limb of the internal capsule (PLIC) and in the cerebral peduncle (CP). RESULTS: In the subacute phase, a reduction of FA, AD, and KA values was correlated with an increase of ODI, RD, and AK parameters, in both the ipsilesional PLIC and CP, suggesting that increased fiber dispersion can be the main structural factor. In the chronic phase, a reduction of FA and an increase of ODI persisted in the ipsilesional areas. This was associated with reduced Fic and increased MD, with a concomitant reduction of MK and increase of RD, suggesting that fiber reduction, possibly due to nerve degeneration, could play an important role. CONCLUSIONS: This study shows that advanced dMRI approaches can help elucidate the underpinning architectural modifications occurring in the CST after stroke. Further follow-up studies on bigger cohorts are needed to evaluate if DKI- and NODDI-derived parameters might be proposed as complementary biomarkers of brain microstructural alterations.

Epileptiform activity contralateral to unilateral hippocampal sclerosis does not cause the expression of brain damage markers.

OBJECTIVE: Patients with epilepsy often ask if recurrent seizures harm their brain and aggravate their epileptic condition. This crucial question has not been specifically addressed by dedicated experiments. We analyze here if intense bilateral seizure activity induced by local injection of kainic acid (KA) in the right hippocampus produces brain damage in the left hippocampus. METHODS: Adult guinea pigs were bilaterally implanted with hippocampal electrodes for continuous video-electroencephalography (EEG) monitoring. Unilateral injection of 1 µg KA in the dorsal CA1 area induced nonconvulsive status epilepticus (ncSE) characterized by bilateral hippocampal seizure discharges. This treatment resulted in selective unilateral sclerosis of the KA-injected hippocampus. Three days after KA injection, the animals were killed, and the brains were submitted to ex vivo magnetic resonance imaging (MRI) and were processed for immunohistochemical analysis. RESULTS: During ncSE, epileptiform activity was recorded for 27.6 ± 19.1 hours in both the KA-injected and contralateral hippocampi. Enhanced T1-weighted MR signal due to gadolinium deposition, mean diffusivity reduction, neuronal loss, gliosis, and blood-brain barrier permeability changes was observed exclusively in the KA-injected hippocampus. Despite the presence of a clear unilateral hippocampal sclerosis at the site of KA injection, no structural alterations were detected by MR and immunostaining analysis performed in the hippocampus contralateral to KA injection 3 days and 2 months after ncSE induction. Fluoro-Jade and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining at the same time points confirmed the absence of degenerating cells in the hippocampi contralateral to KA injection. SIGNIFICANCE: We demonstrate that intense epileptiform activity during ncSE does not cause obvious brain damage in the hippocampus contralateral to unilateral hippocampal KA injection. These findings argue against the hypothesis that epileptiform activity per se contributes to focal brain injury in previously undamaged cortical regions.

Magnetic resonance imaging monitoring therapeutic response to dendritic cell vaccine in murine orthotopic pancreatic cancer models.

Pancreatic ductal adenocarcinoma (PDAC) carries the worst prognosis and caused one of the highest cancer-related mortalities. Dendritic cell (DC) vaccination is a promising cancer immunotherapy; however, the clinical outcomes are often poor. The administration route of DC vaccine can significantly alter the anti-tumor immune response. Here we report on the cytotoxic T lymphocyte (CTL) responses induced by DC vaccination administered via intraperitoneal (IP) for murine PDAC, and the longitudinal assessment of tumor growth and therapeutic responses using magnetic resonance imaging (MRI). In this study, we established murine orthotopic Panc02 models of PDAC and delivered apoptotic Panc02 cell-pulsed DCs via IP injection. The migration of Panc02-pulsed DCs into spleens significantly increased from 6 h to 12 h after initiation of treatment (P = 0.002), and Panc02-pulsed DCs injected via IP induced a significantly higher level of CTL responses against Panc02 cells compared to unpulsed DCs. Tumor size and tumor apparent diffusion coefficient (ADC) were measured on MR images. Tumor sizes were significantly smaller in the treated mice than in the untreated mice (P < 0.05). The reduction of tumor ADC was less in the treated mice than in the untreated mice (P < 0.05), and the changes in tumor ADC showed significant negative correlation with the changes in tumor volume (r = -0.882, 95% confidence interval, -0.967 to -0.701, P < 0.0001). These results demonstrated the efficacy of DC vaccination administered via IP injection in murine PDAC, and the feasibility of ADC measurement as an imaging biomarker for assessment of therapeutic responses in immunotherapy.

Non-invasive dynamic monitoring initiation and growth of pancreatic tumor in the LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) transgenic mouse model.

The LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) mouse is one of the most widely used transgenic models to evaluate tumor characteristics and to develop novel therapies for pancreatic ductal adenocarcinoma (PDAC). There is no report of the effective systemic evaluation of longitudinal KPC tumor imitation and growth. Therefore, we aimed to characterize the initiation and progression of pancreatic cancer in KPC mice using longitudinal multiparametric magnetic resonance imaging (MRI) approaches and overall survival. Ten KPC mice were used to develop spontaneous PDAC and monitored by MRI. Tumor growth was evaluated using weekly acquired MRI data. The relationship between diffusion-weighted MRI (DW-MRI) imaging biomarkers (apparent diffusion coefficient - ADC) and tumor fibrosis measurement by pathological methods was assessed by Pearson correlation coefficient. Six KPC mice developed spontaneously pancreatic tumors at the age of 20.0 ±â€¯2.9 weeks with a relatively short life span (6.8 ±â€¯1.8 weeks). The tumors could be detected by MRI with a minimum diameter of 3.88 ±â€¯1.18 mm (range, 2.18-5.20 mm), showing a rapid growth curve according to both the longest diameter (1.63 ±â€¯0.52 mm/week) and tumor volume (148.77 ±â€¯80.87 mm3)/week. Pathological results confirmed that the tumors display histopathological features of human pancreatic cancer. A strong correlation between ADC values and fibrosis measurements was observed (R = -0.825, P = .043). Our results show that the initiation and progression of pancreatic tumor in KPC mice can be evaluated by longitudinally non-invasive dynamic MRI approaches. The findings will be the fundamental KPC background data for developing novel therapeutic approaches, in particular for evaluation of response to novel treatments.

Prediction of Isocitrate Dehydrogenase Genotype in Brain Gliomas with MRI: Single-Shell versus Multishell Diffusion Models.

Purpose The primary aim of this prospective observational study was to assess whether diffusion MRI metrics correlate with isocitrate dehydrogenase (IDH) status in grade II and III gliomas. A secondary aim was to investigate whether multishell acquisitions with advanced models such as neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging offer greater diagnostic accuracy than diffusion-tensor imaging (DTI). Materials and Methods Diffusion MRI (b = 700 and 2000 sec/mm2) was performed preoperatively in 192 consecutive participants (113 male and 79 female participants; mean age, 46.18 years; age range, 14-77 years) with grade II (n = 62), grade III (n = 58), or grade IV (n = 72) gliomas. DTI, diffusion kurtosis imaging, and NODDI metrics were measured in regions with or without hyperintensity on diffusion MR images and compared among groups defined according to IDH genotype, 1p/19q codeletion status, and tumor grade by using Mann-Whitney tests. Results In grade II and III IDH wild-type gliomas, the maximum fractional anisotropy, kurtosis anisotropy, and restriction fraction were significantly higher and the minimum mean diffusivity was significantly lower than in IDH-mutant gliomas (P = .011, P = .002, P = .044, and P = .027, respectively); areas under the receiver operating characteristic curve ranged from 0.72 to 0.76. In IDH wild-type gliomas, no difference among grades II, III, and IV was found. In IDH-mutant gliomas, no difference between those with and those without 1p/19q loss was found. Conclusion Diffusion MRI metrics showed correlation with isocitrate dehydrogenase status in grade II and III gliomas. Advanced diffusion MRI models did not add diagnostic accuracy, supporting the inclusion of a single-shell diffusion-tensor imaging acquisition in brain tumor imaging protocols. Published under a CC BY 4.0 license. Online supplemental material is available for this article.