First-in-human assessment of the novel LAT1 targeting PET probe 18F-FIMP.

In the first-in-human PET study, we evaluated the biodistribution and tumor accumulation of the novel PET probe, (S)-2-amino-3-[3-(2-18F-fluoroethoxy)-4-iodophenyl]-2-methylpropanoic acid (18F-FIMP), which targets the tumor-related L-type amino acid transporter 1 (LAT1), and compared it with L-[methyl-11C]methionine (11C-MET) and 2-Deoxy-2-18F-fluoro-D-glucose (18F-FDG). 18F-FIMP biodistribution was revealed by whole-body and brain scans in 13 healthy controls. Tumor accumulation of 18F-FIMP was evaluated in 7 patients with a brain tumor, and compared with those of 11C-MET and 18F-FDG. None of the subjects had significant problems due to probe administration, such as adverse effects or abnormal vital signs. 18F-FIMP was rapidly excreted from the kidneys to the urinary bladder. There was no characteristic physiological accumulation in healthy controls. 18F-FIMP PET resulted in extremely clear images in patients with suspected glioblastoma compared with 11C-MET and 18F-FDG. 18F-FIMP could be a useful novel PET probe for LAT1-positive tumor imaging including glioblastoma.

Characteristics and outcomes of elderly patients with diffuse gliomas: a multi-institutional cohort study by Kansai Molecular Diagnosis Network for CNS Tumors.

INTRODUCTION: This study investigates the current state of clinical practice and molecular analysis for elderly patients with diffuse gliomas and aims to elucidate treatment outcomes and prognostic factors of patients with glioblastomas. METHODS: We collected elderly cases (≥ 70 years) diagnosed with primary diffuse gliomas and enrolled in Kansai Molecular Diagnosis Network for CNS Tumors. Clinical and pathological characteristics were analyzed retrospectively. Various factors were evaluated in univariate and multivariate models to examine their effects on overall survival. RESULTS: Included in the study were 140 elderly patients (WHO grade II: 7, III: 19, IV: 114), median age was 75 years. Sixty-seven patients (47.9%) had preoperative Karnofsky Performance Status score of ≥ 80. All patients underwent resection (gross-total: 20.0%, subtotal: 14.3%, partial: 39.3%, biopsy: 26.4%). Ninety-six of the patients (68.6%) received adjuvant treatment consisting of radiotherapy (RT) with temozolomide (TMZ). Seventy-eight of the patients (75.0%) received radiation dose of ≥ 50 Gy. MGMT promoter was methylated in 68 tumors (48.6%), IDH1/2 was wild-type in 129 tumors (92.1%), and TERT promoter was mutated in 78 of 128 tumors (60.9%). Median progression-free and overall survival of grade IV cases was 8.2 and 13.6 months, respectively. Higher age (≥ 80 years) and TERT promoter mutated were associated with shorter survival. Resection and adjuvant RT + TMZ were identified as independent factors for good prognosis. CONCLUSIONS: This community-based study reveals characteristics and outcomes of elderly glioma patients in a real-world setting. Elderly patients have several potential factors for poor prognosis, but resection followed by RT + TMZ could lengthen duration of survival.

Glioblastoma in long-term survivors of acute lymphoblastic leukemia: Report of two cases.

Acute lymphoblastic leukemia (ALL) is the most common form of cancer in children. Second neoplasms as late effects of therapy for ALL have been recognized as a significant clinical issue given the increasing number of long-term survivors of ALL, because they can be the cause of death in such cases. In contrast, glioblastoma (GBM) is the most common primary brain tumor in adults. It is a malignant brain tumor that most often occurs in elderly patients, and GBM in young adults or adolescents appears to be rare. Here, we describe our experience of two cases of GBM in young long-term survivors of ALL, and emphasize the necessity of careful follow up of patients treated for ALL for the potential occurrence of central nervous system second neoplasms, especially when the patients have previously undergone cranial radiotherapy.

Maximum 11C-methionine PET uptake as a prognostic imaging biomarker for newly diagnosed and untreated astrocytic glioma.

This study aimed whether the uptake of amino tracer positron emission tomography (PET) can be used as an additional imaging biomarker to estimate the prognosis of glioma. Participants comprised 56 adult patients with newly diagnosed and untreated World Health Organization (WHO) grade II-IV astrocytic glioma who underwent surgical excision and were evaluated by 11C-methionine PET prior to the surgical excision at Osaka City University Hospital from July 2011 to March 2018. Clinical and imaging studies were retrospectively reviewed based on medical records at our institution. Preoperative Karnofsky Performance Status (KPS) only influenced progression-free survival (hazard ratio [HR] 0.20; 95% confidence interval [CI] 0.10-0.41, p < 0.0001), whereas histology (anaplastic astrocytoma: HR 5.30, 95% CI 1.23-22.8, p = 0.025; glioblastoma: HR 11.52, 95% CI 2.27-58.47, p = 0.0032), preoperative KPS ≥ 80 (HR 0.23, 95% CI 0.09-0.62, p = 0.004), maximum lesion-to-contralateral normal brain tissue (LN max) ≥ 4.03 (HR 0.24, 95% CI 0.08-0.71, p = 0.01), and isocitrate dehydrogenase (IDH) status (HR 14.06, 95% CI 1.81-109.2, p = 0.011) were factors influencing overall survival (OS) in multivariate Cox regression. OS was shorter in patients with LN max ≥ 4.03 (29.3 months) than in patients with LN max < 4.03 (not reached; p = 0.03). OS differed significantly between patients with IDH mutant/LN max < 4.03 and patients with IDH mutant/LN max ≥ 4.03. LN max using 11C-methionine PET may be used in prognostic markers for newly identified and untreated WHO grade II-IV astrocytic glioma.

Non-normalized individual analysis of statistical parametric mapping for clinical fMRI.

BACKGROUND: Pre-operative evaluation to localize function within the cerebral cortices is essential before brain surgery. Blood oxygenation level-dependent functional magnetic resonance imaging (fMRI) has been used for this purpose. AIMS: To obtain clearer and more understandable functional images. PATIENTS AND METHODS: Ten patients with brain tumors underwent fMRI including hand-gripping and word generation tasks. The statistical parametric mapping (SPM) approach was used for subsequent analysis to localize the motor or language functions. SPM includes image pre-processing, statistical computation, and significance testing. In order to demonstrate a spatial relationship between the lesions and a functioning area in the individual structural MR images, normalization to the Montreal Neurological Institute coordinates was intentionally not performed. RESULTS: In seven cases out of 10, the patient's motor area was clearly visualized. Language areas were also demonstrated in seven cases. CONCLUSIONS: We conclude that application of SPM (version 8) analysis to non-normalized individual data for the purpose of performing pre-operative fMRI is a useful method for investigation of functional localization.

Specific Oscillatory Power Changes and Their Efficacy for Determining Laterality in Mesial Temporal Lobe Epilepsy: A Magnetoencephalographic Study.

Appropriate determination of the epileptic focus and its laterality are important for the diagnosis of mesial temporal lobe epilepsy (MTLE). The aims of this study are to establish a specific oscillatory distribution and laterality of the oscillatory power in unilateral MTLE with frequency analysis of magnetoencephalography (MEG), and to confirm their potential to carry significant information for determining lateralization of the epileptic focus. Thirty-five patients with MTLE [left (LtMTLE), 16; right (RtMTLE), 19] and 102 healthy control volunteers (CTR) were enrolled. Cortical oscillatory powers were compared among the groups by contrasting the source images using a one-way ANOVA model for each frequency band. Further, to compare the lateralization of regional oscillatory powers between LtMTLEs and RtMTLEs, the laterality index (LI) was calculated for four brain regions (frontal, temporal, parietal, and occipital) in each frequency band, which were compared between patient groups (LtMTLE, RtMTLE, and CTR), and used for machine learning prediction of the groups with support vector machine (SVM) with linear kernel function. Significant oscillatory power differences between MTLE and CTR were found in certain areas. In the theta to high-frequency oscillation bands, there were marked increases in the parietal lobe, especially on the left side, in LtMTLE. In the theta, alpha, and high-gamma bands, there were marked increases in the parietal lobe, especially on the right side in RtMTLE. Compared with CTR, LIs were significantly higher in 24/28 regions in LtMTLE, but lower in 4/28 regions and higher in 10/28 regions in RtMTLE. LI at the temporal lobe in the theta band was significantly higher in LtMTLE and significantly lower in RtMTLE. Comparing LtMTLE and RtMTLE, there were significant LI differences in most regions and frequencies (21/28 regions). In all frequency bands, there were significant differences between LtMTLE and RtMTLE in the temporal and parietal lobes. The leave-one-out cross-validation of the linear-SVM showed the classification accuracy to be over 91%, where the model had high specificity over 96% and mild sensitivity ~68-75%. Using MEG frequency analysis, the characteristics of the oscillatory power distribution in the MTLE were demonstrated. Compared with CTR, LIs shifted to the side of the epileptic focus in the temporal lobe in the theta band. The machine learning approach also confirmed that LIs have significant predictive ability in the lateralization of the epileptic focus. These results provide useful additional information for determining the laterality of the focus.

Diagnostic Performance of [11C]Methionine Positron Emission Tomography in Newly Diagnosed and Untreated Glioma Based on the Revised World Health Organization 2016 Classification.

BACKGROUND: The relationship between uptake of amino acid tracer with positron emission tomography (PET) and glioma subtypes/gene status is still unclear. OBJECTIVE: To assess the relationship between uptake of [11C]methionine using PET and pathology, IDH (isocitrate dehydrogenase) mutation, 1p/19q codeletion, and TERT (telomerase reverse transcriptase) promoter status in gliomas. METHODS: The participants were 68 patients with newly diagnosed and untreated glioma who underwent surgical excision and preoperative [11C]methionine PET examination at Osaka City University Hospital between July 2011 and March 2018. Clinical and imaging studies were reviewed retrospectively based on the medical records at our institution. RESULTS: The mean lesion/contralateral normal brain tissue (L/N) ratio of diffuse astrocytomas was significantly lower than that of anaplastic astrocytomas (P = 0.00155), glioblastoma (P < 0.001), and oligodendrogliomas (P = 0.0157). The mean L/N ratio of IDH mutant gliomas was significantly lower than that of IDH wild-type gliomas (median 1.75 vs. 2.61; P = 0.00162). A mean L/N ratio of 2.05 provided the best sensitivity and specificity for distinguishing between IDH mutant and IDH wild-type gliomas (69.2% and 76.2%, respectively). The mean L/N ratio of TERT promoter mutant gliomas was significantly higher than that of TERT promoter wild-type gliomas (P = 0.0147). Multiple regression analysis showed that pathologic diagnosis was the only influential factor on L/N ratio. CONCLUSIONS: Distinguishing glioma subtypes based on the revised 2016 World Health Organization classification of the central nervous system tumors on the basis of [11C]methionine PET alone seems to be difficult. However, [11C]methionine PET might be useful for predicting the IDH mutation status in newly diagnosed and untreated gliomas noninvasively before tumor resection.

Determining the extent of tumor resection at surgical planning with 18F-fluciclovine PET/CT in patients with suspected glioma: multicenter phase III trials.

OBJECTIVE: Glioma is the most common type of central nervous system tumor reported worldwide. Current imaging technologies have limitations in the diagnosis and assessment of glioma. The present study aimed to confirm the diagnostic efficacy and safety of anti-1-amino-3-[18F]fluorocyclobutane carboxylic acid (18F-fluciclovine; anti-[18F]FACBC) as a radiotracer for patients undergoing combined positron emission tomography and computed tomography (PET/CT) for suspected glioma. METHODS: Combined data from two multicenter, open-label phase III clinical trials were evaluated for this study. The two trials enrolled patients with suspected high- or low-grade glioma on the basis of clinical symptoms, clinical course, and magnetic resonance imaging findings, and who were scheduled for tumor resection surgery. Patients fasted for ≥ 4 h and received 2 mL of 18F-fluciclovine (radioactivity dose 78.3-297.0 MBq), followed by a 10-min PET scan 10-50 min after injection. The primary efficacy endpoint was the positive predictive value (PPV) of the gadolinium contrast-enhanced T1-weighted image negative [Gd (-)] and 18F-fluciclovine PET-positive [PET ( +)] area of the scans, using the histopathological diagnosis of the tissue sampled from that area as the standard of truth. All adverse events reported during the study were recorded for safety analysis. RESULTS: A total of 45 patients aged 23-89 years underwent 18F-fluciclovine PET; 31/45 patients (68.9%) were male, and 30/45 patients (66.7%) were suspected to have high-grade glioma. The PPV of 18F-fluciclovine PET in the Gd (-) PET ( +) area was 88.0% (22/25 areas, 95% confidence interval: 70.0-95.8). The extent of planned tumor resection was modified in 47.2% (17/36 cases) after 18F-fluciclovine PET scan, with an extension of area in 30.6% (11/36 cases) and reduction in 16.7% (6/36 cases). Furthermore, tissue samples collected from PET ( +) areas tended to have a higher malignancy grade compared with those from PET (-) areas. Overall, 18F-fluciclovine was well tolerated. CONCLUSION: 18F-fluciclovine PET/CT is useful for determining the extent of tumor resection at surgical planning, and may serve as a safe and effective diagnostic tool for patients with suspected glioma. TRIAL REGISTRATION: These trials were registered in the Japan Pharmaceutical Information Center Clinical Trials Information (JapicCTI-152986, JapicCTI-152985).

Fine-Tuning Approach for Segmentation of Gliomas in Brain Magnetic Resonance Images with a Machine Learning Method to Normalize Image Differences among Facilities.

Machine learning models for automated magnetic resonance image segmentation may be useful in aiding glioma detection. However, the image differences among facilities cause performance degradation and impede detection. This study proposes a method to solve this issue. We used the data from the Multimodal Brain Tumor Image Segmentation Benchmark (BraTS) and the Japanese cohort (JC) datasets. Three models for tumor segmentation are developed. In our methodology, the BraTS and JC models are trained on the BraTS and JC datasets, respectively, whereas the fine-tuning models are developed from the BraTS model and fine-tuned using the JC dataset. Our results show that the Dice coefficient score of the JC model for the test portion of the JC dataset was 0.779 ± 0.137, whereas that of the BraTS model was lower (0.717 ± 0.207). The mean Dice coefficient score of the fine-tuning model was 0.769 ± 0.138. There was a significant difference between the BraTS and JC models (p < 0.0001) and the BraTS and fine-tuning models (p = 0.002); however, no significant difference between the JC and fine-tuning models (p = 0.673). As our fine-tuning method requires fewer than 20 cases, this method is useful even in a facility where the number of glioma cases is small.

Quantitative imaging of spontaneous neuromagnetic activity for assessing cerebral ischemia using sLORETA-qm.

To image cerebral neural activity in ischemic areas, we proposed a novel technique to analyze spontaneous neuromagnetic fields based on standardized low-resolution brain electromagnetic tomography modified for a quantifiable method (sLORETA-qm). Using a 160-channel whole-head-type magnetoencephalographic system, cerebral magnetic fields were obtained pre- and postoperatively from 5 patients with unilateral internal carotid artery occlusive disease and 16 age-matched healthy volunteers. For quantitative imaging, voxel-based time-averaged intensities of slow waves in 4 frequency bands (0.3-2 Hz, 2-4 Hz, 4-6 Hz and 6-8 Hz) were obtained by the proposed technique based on sLORETA-qm. Positron emission tomography with (15)O gas inhalation ((15)O-PET) was also performed in these patients to evaluate cerebral blood flow and metabolism. In all 5 patients, slow waves in every frequency band were distributed in the area of cerebrovascular insufficiency, as confirmed by (15)O-PET preoperatively. In 4 patients, slow-wave intensities in theta bands (4-6 Hz, 6-8 Hz) decreased postoperatively along with improvements in cerebral blood flow and metabolism, whereas delta bands (0.3-2 Hz, 2-4 Hz) showed no significant differences between pre- and postoperatively. One patient with deterioration of cerebral infarction after surgery showed marked increases in slow-wave intensities in delta bands (0.3-2 Hz, 2-4 Hz) postoperatively, with distribution close to the infarct region. The proposed quantitative imaging of spontaneous neuromagnetic fields enabled clear visualization and alternations of cerebral neural conditions in the ischemic area. This technique may offer a novel, non-invasive method for identifying cerebral ischemia, although further studies in a larger number of patients are warranted.

[A Case of Primary Central Nervous System Lymphomatoid Granulomatosis that was Completely Ameliorated by Corticosteroid Treatment].

Lymphomatoid granulomatosis (LYG) is an angiocentric, angiodestructive lymphoreticular proliferative disease that usually affects the lungs but it has been speculated to also effect the central nervous system (CNS). However, unique primary LYG of the CNS has rarely been reported in the literature. Herein, we describe a clinical case of a 37-year-old female patient with grade 1 primary CNS-LYG having a good prognosis owing to corticosteroid treatment. The aforesaid patient, presented with a headache and left leg weakness with no evidence of a systemic disease. MRI revealed multiple small enhancing nodules in the right hemisphere with diffuse high-intensity lesions on T2/ FLAIR image. A brain biopsy showed lymphohistiocytic cells with blood vessels infiltrated with CD3+ and CD20+. The Epstein-Barr virus encoded small RNA-ISH test was negative. Based on the above findings, grade 1 primary CNS-LYG was diagnosed. Following the administration of oral corticosteroids, a systemic high-dose corticosteroid therapy was administrated. Complete remission was achieved and maintained for 24 months following treatment. Grade 1 primary CNS-LYG is a rare disease that is not apparently associated with the Epstein-Barr virus (EBV) and possibly yields much better prognosis than the frequently EBV-positive systemic LYG with CNS localization. (Received November 5, 2019; Accepted November 20, 2019; Published February 1, 2020).

Molecular characteristics and clinical outcomes of elderly patients with IDH-wildtype glioblastomas: comparative study of older and younger cases in Kansai Network cohort.

Aging is a known negative prognostic factor in glioblastomas (GBM). Whether particular genetic backgrounds are a factor in poor outcomes of elderly patients with GBM warrants investigation. We aim to elucidate any differences between older and younger adult patients with IDH-wildtype GBM regarding both molecular characteristics and clinical outcomes. We collected adult cases diagnosed with IDH-wildtype GBM from the Kansai Network. Clinical and pathological characteristics were analyzed retrospectively and compared between older (≥ 70 years) and younger (≤ 50 years) cases. Included were 92 older vs. 33 younger cases. The older group included more patients with preoperative Karnofsky performance status score < 70 and had a shorter survival time than the younger group. MGMT promoter was methylated more frequently in the older group. TERT promoter mutation was more common in the older group. There were significant differences in DNA copy-number alteration profiles between age groups in PTEN deletion and CDK4 amplification/gain. In the older group, no molecular markers were identified, but surgical resection was an independent prognostic factor. Age-specific survival difference was significant in the MGMT methylated and TERT wildtype subgroup. Elderly patients have several potential factors in poor prognosis of glioblastomas. Varying molecular profiles may explain differing rates of survival between generations.

Activated leukocyte cell adhesion molecule expression correlates with the WNT subgroup in medulloblastoma and is involved in regulating tumor cell proliferation and invasion.

Cluster of differentiation (CD) 166 or activated leukocyte cell adhesion molecule (ALCAM) is a transmembrane molecule known to be an intercellular adhesion factor. The expression and function of ALCAM in medulloblastoma (MB), a pediatric brain tumor with highly advanced molecular genetics, remains unclear. Therefore, this study aimed to clarify the significance and functional role of ALCAM expression in MB. ALCAM expression in 45 patients with MB was evaluated by immunohistochemical analysis of formalin-fixed paraffin-embedded clinical specimens and the relationship between ALCAM expression and pathological type/molecular subgroup, such as WNT, SHH, Group 3, and Group 4, was examined. Eight ALCAM positive (18%), seven partially positive (16%), and 30 negative (67%) cases were detected. All seven cases of the WNT molecular subgroup were ALCAM positive and ALCAM expression strongly correlated with this subgroup (P < 0.0001). In addition, functional studies using MB cell lines revealed ALCAM expression affected proliferation and migration as a positive regulator in vitro. However, ALCAM silencing did not affect survival or the formation of leptomeningeal dissemination in an orthotopic mouse model, but did induce a malignant phenotype with increased tumor cell invasion at the dissemination sites (P = 0.0029). In conclusion, our results revealed that ALCAM exhibited highly specific expression in the WNT subgroup of MB. Furthermore, we demonstrated that the cell kinetics of MB cell lines can be altered by the expression of ALCAM.

Prediction of seizure outcome following epilepsy surgery: asymmetry of thalamic glucose metabolism and cerebral neural activity in temporal lobe epilepsy.

OBJECTIVE: The objective of this retrospective study is to analyze whether preoperative functional imaging studies using FDG-PET and MEG enable prediction of postoperative seizure outcomes. METHODS: Thirty-six patients with intractable temporal lobe epilepsy were studied. Asymmetry index of tCMRgluc (PET-AI) and the equivalent current dipole intensity of first response of SEF (SEF-AI) were determined preoperatively using (18)F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and magnetoencephalography (MEG), respectively. Seizure outcomes were evaluated according to the classification proposed by the International League Against Epilepsy (ILAE) at least 24 months after resection of epileptic focuses. Twelve healthy volunteers were included in this study to determine the normal value. RESULTS: Quantitative analysis revealed mean PET-AI in the patients was 5.4+/-5.2% (significantly different from normal controls); mean SEF-AI was 25.2+/-20.6% (not significantly different). PET-AI was positive (indicative of epileptic focus) in 29 of 36 patients (80.6%), while SEF-AI was positive in 17 of 36 patients (47.2%). Although no significant correlation between PET-AI and SEF-AI was noted (r=0.43), concordant asymmetry in both PET-AI and SEF-AI was significantly associated with better seizure outcome than discordant or paradoxical asymmetry of both factors (p<0.01). CONCLUSIONS: The results suggest that quantitative analysis of tCMRgluc with SEF may be helpful in characterizing the preoperative epileptogenic condition and predicting postoperative seizure outcome in patients with temporal lobe epilepsy, although a constellation of developmental brain abnormalities and environmental factors that together produce epilepsy need to be further explored.

The influence of hypoglycemia on cerebral blood flow in cases of hypoglycemic coma.

The authors report two cases of hypoglycemic coma in which both diffusion-weighted imaging (DWI) and single photon emission computed tomography (SPECT) were used. A 74-year-old woman (case 1) presented with deep coma associated with hypoglycemia (blood glucose level: 20 mg/dl), and DWI on admission revealed extensive hyperintensity lesions. SPECT obtained on the second hospital day revealed diffuse hyperperfusion and a follow-up SPECT on the eighth hospital day showed relative hypoperfusion. An 89- year- old woman (case 2) presented with coma associated with hypoglycemia (blood glucose level: 45 mg/dl), and DWI showed diffuse hyperintensity lesions in both hemispheres. SPECT obtained on the ninth hospital day showed relative hypoperfusion compared to the first scan obtained on the third hospital day. Although the blood glucose level was rapidly corrected, the level of consciousness remained unchanged in both cases. Our results suggest that cerebral blood flow may increase even after glucose correction and that relative hypoperfusion could occur in the subacute stage of hypoglycemic coma.

Radiomics and MGMT promoter methylation for prognostication of newly diagnosed glioblastoma.

We attempted to establish a magnetic resonance imaging (MRI)-based radiomic model for stratifying prognostic subgroups of newly diagnosed glioblastoma (GBM) patients and predicting O (6)-methylguanine-DNA methyltransferase promotor methylation (pMGMT-met) status of the tumor. Preoperative MRI scans from 201 newly diagnosed GBM patients were included in this study. A total of 489 texture features including the first-order feature, second-order features from 162 datasets, and location data from 182 datasets were collected. Supervised principal component analysis was used for prognostication and predictive modeling for pMGMT-met status was performed based on least absolute shrinkage and selection operator regression. 22 radiomic features that were correlated with prognosis were used to successfully stratify patients into high-risk and low-risk groups (p = 0.004, Log-rank test). The radiomic high- and low-risk stratification and pMGMT status were independent prognostic factors. As a matter of fact, predictive accuracy of the pMGMT methylation status was 67% when modeled by two significant radiomic features. A significant survival difference was observed among the combined high-risk group, combined intermediate-risk group (this group consists of radiomic low risk and pMGMT-unmet or radiomic high risk and pMGMT-met), and combined low-risk group (p = 0.0003, Log-rank test). Radiomics can be used to build a prognostic score for stratifying high- and low-risk GBM, which was an independent prognostic factor from pMGMT methylation status. On the other hand, predictive accuracy of the pMGMT methylation status by radiomic analysis was insufficient for practical use.

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutional neural network (CNN) from magnetic resonance (MR) images and compared the accuracy to that of a diagnosis based on conventional radiomic features and patient age. Multisite preoperative MR images of 164 patients with grade II/III glioma were grouped by IDH and TERT promoter (pTERT) mutations as follows: (1) IDH wild type, (2) IDH and pTERT co-mutations, (3) IDH mutant and pTERT wild type. We applied a CNN (AlexNet) to four types of MR sequence and obtained the CNN texture features to classify the groups with a linear support vector machine. The classification was also performed using conventional radiomic features and/or patient age. Using all features, we succeeded in classifying patients with an accuracy of 63.1%, which was significantly higher than the accuracy obtained from using either the radiomic features or patient age alone. In particular, prediction of the pTERT mutation was significantly improved by the CNN texture features. In conclusion, the pretrained CNN texture features capture the information of IDH and TERT genotypes in grade II/III gliomas better than the conventional radiomic features.

Distribution differences in prognostic copy number alteration profiles in IDH-wild-type glioblastoma cause survival discrepancies across cohorts.

The diagnosis and prognostication of glioblastoma (GBM) remain to be solely dependent on histopathological findings and few molecular markers, despite the clinical heterogeneity in this entity. To address this issue, we investigated the prognostic impact of copy number alterations (CNAs) using two population-based IDH-wild-type GBM cohorts: an original Japanese cohort and a dataset from The Cancer Genome Atlas (TCGA). The molecular disproportions between these cohorts were dissected in light of cohort differences in GBM. The Japanese cohort was collected from cases registered in Kansai Molecular Diagnosis Network for CNS tumors (KNBTG). The somatic landscape around CNAs was analyzed for 212 KNBTG cases and 359 TCGA cases. Next, the clinical impacts of CNA profiles were investigated for 140 KNBTG cases and 152 TCGA cases treated by standard adjuvant therapy using temozolomide-based chemoradiation. The comparative profiling indicated unequal distribution of specific CNAs such as EGFR, CDKN2A, and PTEN among the two cohorts. Especially, the triple overlap CNAs in these loci (triple CNA) were much higher in frequency in TCGA (70.5%) than KNBTG (24.3%), and its prognostic impact was independently validated in both cohorts. The KNBTG cohort significantly showed better prognosis than the TCGA cohort (median overall survival 19.3 vs 15.6 months). This survival difference between the two cohorts completely resolved after subclassifying all cases according to the triple CNA status. The prognostic significance of triple CNA was identified in IDH-wild-type GBM. Distribution difference in prognostic CNA profiles potentially could cause survival differences across cohorts in clinical studies.

Diagnostic accuracy of 11C-methionine PET for differentiation of recurrent brain tumors from radiation necrosis after radiotherapy.

UNLABELLED: We evaluated the diagnostic accuracy of PET with l-methyl-(11)C-methionine ((11)C-MET) for the differentiation of recurrent brain tumors from radiation necrosis. METHODS: Seventy-seven patients who had been previously treated with radiotherapy after primary treatment for metastatic brain tumor (n=51) or glioma (n=26) were studied to clarify the diagnostic performance of (11)C-MET PET in differentiating between recurrent brain tumors and radiation necrosis. A total of 88 PET scans with (11)C-MET were obtained; sometimes more than one scan was obtained when there was an indication of recurrent brain tumor or radiation necrosis. A definitive diagnosis was made on the basis of pathologic examination for recurrent brain tumors and on the basis of pathologic examination or clinical course for radiation necrosis. Several indices characterizing the lesions were determined; these included mean and maximum standardized uptake values (SUV(mean) and SUV(max), respectively) and the ratios of lesion uptake to contralateral normal frontal-lobe gray matter uptake corresponding to the SUV(mean) and the SUV(max) (L/N(mean) and L/N(max), respectively). Receiver-operating-characteristic (ROC) curve analysis was used to determine the optimal index of (11)C-MET PET and cutoff values for the differential diagnosis of tumor recurrence and radiation necrosis. RESULTS: The values of each index of (11)C-MET PET tended to be higher for tumor recurrence than for radiation necrosis. There were significant differences between tumor recurrence and radiation necrosis in all of the indices except for the L/N(max) for glioma. ROC analysis indicated that the L/N(mean) was the most informative index for differentiating between tumor recurrence and radiation necrosis. An L/N(mean) of greater than 1.41 provided the best sensitivity and specificity for metastatic brain tumor (79% and 75%, respectively), and an L/N(mean) of greater than 1.58 provided the best sensitivity and specificity for glioma (75% and 75%, respectively). CONCLUSION: (11)C-MET PET can provide quantitative values to aid in the differentiation of tumor recurrence from radiation necrosis, although these values do not appear to be absolute indicators. Quantitative analysis of (11)C-MET PET data may be helpful in managing irradiated brain tumors.

Lesion location implemented magnetic resonance imaging radiomics for predicting IDH and TERT promoter mutations in grade II/III gliomas.

Molecular biological characterization of tumors has become a pivotal procedure for glioma patient care. The aim of this study is to build conventional MRI-based radiomics model to predict genetic alterations within grade II/III gliomas attempting to implement lesion location information in the model to improve diagnostic accuracy. One-hundred and ninety-nine grade II/III gliomas patients were enrolled. Three molecular subtypes were identified: IDH1/2-mutant, IDH1/2-mutant with TERT promoter mutation, and IDH-wild type. A total of 109 radiomics features from 169 MRI datasets and location information from 199 datasets were extracted. Prediction modeling for genetic alteration was trained via LASSO regression for 111 datasets and validated by the remaining 58 datasets. IDH mutation was detected with an accuracy of 0.82 for the training set and 0.83 for the validation set without lesion location information. Diagnostic accuracy improved to 0.85 for the training set and 0.87 for the validation set when lesion location information was implemented. Diagnostic accuracy for predicting 3 molecular subtypes of grade II/III gliomas was 0.74 for the training set and 0.56 for the validation set with lesion location information implemented. Conventional MRI-based radiomics is one of the most promising strategies that may lead to a non-invasive diagnostic technique for molecular characterization of grade II/III gliomas.