Quality assessment of the MRI-radiomics studies for MGMT promoter methylation prediction in glioma: a systematic review and meta-analysis.

OBJECTIVES: To evaluate the methodological quality and diagnostic accuracy of MRI-based radiomic studies predicting O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in gliomas. METHODS: PubMed Medline, EMBASE, and Web of Science were searched to identify MRI-based radiomic studies on MGMT methylation in gliomas published until December 31, 2022. Three raters evaluated the study methodological quality with Radiomics Quality Score (RQS, 16 components) and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis (TRIPOD, 22 items) scales. Risk of bias and applicability concerns were assessed with QUADAS-2 tool. A meta-analysis was performed to estimate the pooled area under the curve (AUC) and to assess inter-study heterogeneity. RESULTS: We included 26 studies, published from 2016. The median RQS total score was 8 out of 36 (22%, range 8-44%). Thirteen studies performed external validation. All studies reported AUC or accuracy, but only 4 (15%) performed calibration and decision curve analysis. No studies performed phantom analysis, cost-effectiveness analysis, and prospective validation. The overall TRIPOD adherence score was between 50% and 70% in 16 studies and below 50% in 10 studies. The pooled AUC was 0.78 (95% CI, 0.73-0.83, I2 = 94.1%) with a high inter-study heterogeneity. Studies with external validation and including only WHO-grade IV gliomas had significantly lower AUC values (0.65; 95% CI, 0.57-0.73, p < 0.01). CONCLUSIONS: Study RQS and adherence to TRIPOD guidelines was generally low. Radiomic prediction of MGMT methylation status showed great heterogeneity of results and lower performances in grade IV gliomas, which hinders its current implementation in clinical practice. CLINICAL RELEVANCE STATEMENT: MGMT promoter methylation status appears to be variably correlated with MRI radiomic features; radiomic models are not sufficiently robust to be integrated into clinical practice to accurately predict MGMT promoter methylation status in patients with glioma before surgery. KEY POINTS: • Adherence to the indications of TRIPOD guidelines was generally low, as was RQS total score. • MGMT promoter methylation status prediction with MRI radiomic features provided heterogeneous diagnostic accuracy results across studies. • Studies that included grade IV glioma only and performed external validation had significantly lower diagnostic accuracy than others.

scMuffin: an R package to disentangle solid tumor heterogeneity by single-cell gene expression analysis.

INTRODUCTION: Single-cell (SC) gene expression analysis is crucial to dissect the complex cellular heterogeneity of solid tumors, which is one of the main obstacles for the development of effective cancer treatments. Such tumors typically contain a mixture of cells with aberrant genomic and transcriptomic profiles affecting specific sub-populations that might have a pivotal role in cancer progression, whose identification eludes bulk RNA-sequencing approaches. We present scMuffin, an R package that enables the characterization of cell identity in solid tumors on the basis of a various and complementary analyses on SC gene expression data. RESULTS: scMuffin provides a series of functions to calculate qualitative and quantitative scores, such as: expression of marker sets for normal and tumor conditions, pathway activity, cell state trajectories, Copy Number Variations, transcriptional complexity and proliferation state. Thus, scMuffin facilitates the combination of various evidences that can be used to distinguish normal and tumoral cells, define cell identities, cluster cells in different ways, link genomic aberrations to phenotypes and identify subtle differences between cell subtypes or cell states. We analysed public SC expression datasets of human high-grade gliomas as a proof-of-concept to show the value of scMuffin and illustrate its user interface. Nevertheless, these analyses lead to interesting findings, which suggest that some chromosomal amplifications might underlie the invasive tumor phenotype and the presence of cells that possess tumor initiating cells characteristics. CONCLUSIONS: The analyses offered by scMuffin and the results achieved in the case study show that our tool helps addressing the main challenges in the bioinformatics analysis of SC expression data from solid tumors.

Magnetic resonance imaging characteristics of pediatric pilocytic astrocytoma.

PURPOSE: MRI has an important role in diagnosing pilocytic astrocytoma and post-surgical follow-up since the surgical approach has a leading role in its treatment. The purpose of our study is to provide an overview of the typical and atypical MRI findings in a series of pediatric patients with isolated-not NF1-related-pilocytic astrocytomas and to correlate specific MRI patterns with clinical variables. METHODS: This is a cross-sectional retrospective study providing the analysis of several clinical and neuroradiological findings from a cohort of pediatric pilocytic astrocytoma, starting from the data collected in the Fondazione IRCCS Istituto Neurologico Carlo Besta (FINCB) internal Cancer Registry during an 11-year time period (January 2008-January 2019). RESULTS: Fifty-six patients were included in the study. Median age at diagnosis was 9.4 years; a slight female prevalence was noticed (m/f ratio 44.6%/55.4%). The majority of pPAs had well-defined contours: 51 (91.1%), 47 (88.7%) were hypointense on T1-wi, all of them were hyperintense on T2-wi, 46 (90.2%) were hyperintense on FLAIR, and 48 (85.7%) were heterogeneous on T1-wi and T2-wi sequences. We found positive correlation between pPAs location and age (r = 0.017), and small degree of connection between pPAs location and gender (Cramer's V = 0.268). CONCLUSIONS: We presented typical and atypical pPAs MRI findings. Age and tumor location were positevely correlated, while degree of connection between gender and pPAs location was small. All of this may aid clinicians, most of all neuroradiologists, neurosurgeons, and neurologists in proper diagnoses and follow-up of these specific patient population.

A discriminative event-based model for subtype diagnosis of sporadic Creutzfeldt-Jakob disease using brain MRI.

INTRODUCTION: Sporadic Creutzfeldt-Jakob disease (sCJD) comprises multiple subtypes (MM1, MM2, MV1, MV2C, MV2K, VV1, and VV2) with distinct disease durations and spatiotemporal cascades of brain lesions. Our goal was to establish the ante mortem diagnosis of sCJD subtype, based on patient-specific estimates of the spatiotemporal cascade of lesions detected by diffusion-weighted magnetic resonance imaging (DWI). METHODS: We included 488 patients with autopsy-confirmed diagnosis of sCJD subtype and 50 patients with exclusion of prion disease. We applied a discriminative event-based model (DEBM) to infer the spatiotemporal cascades of lesions, derived from the DWI scores of 12 brain regions assigned by three neuroradiologists. Based on the DEBM cascades and the prion protein genotype at codon 129, we developed and validated a novel algorithm for the diagnosis of the sCJD subtype. RESULTS: Cascades of MM1, MM2, MV1, MV2C, and VV1 originated in the parietal cortex and, following subtype-specific orderings of propagation, went toward the striatum, thalamus, and cerebellum; conversely, VV2 and MV2K cascades showed a striatum-to-cortex propagation. The proposed algorithm achieved 76.5% balanced accuracy for the sCJD subtype diagnosis, with low rater dependency (differences in accuracy of ± 1% among neuroradiologists). DISCUSSION: Ante mortem diagnosis of sCJD subtype is feasible with this novel data-driven approach, and it may be valuable for patient prognostication, stratification in targeted clinical trials, and future therapeutics. HIGHLIGHTS: Subtype diagnosis of sporadic Creutzfeldt-Jakob disease (sCJD) is achievable with diffusion MRI. Cascades of diffusion MRI abnormalities in the brain are subtype-specific in sCJD. We proposed a diagnostic algorithm based on cascades of diffusion MRI abnormalities and demonstrated that it is accurate. Our method may aid early diagnosis, prognosis, stratification in clinical trials, and future therapeutics. The present approach is applicable to other neurodegenerative diseases, enhancing the differential diagnoses.

Development of A Radiomic Model for MGMT Promoter Methylation Detection in Glioblastoma Using Conventional MRI.

The methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a molecular marker associated with a better response to chemotherapy in patients with glioblastoma (GB). Standard pre-operative magnetic resonance imaging (MRI) analysis is not adequate to detect MGMT promoter methylation. This study aims to evaluate whether the radiomic features extracted from multiple tumor subregions using multiparametric MRI can predict MGMT promoter methylation status in GB patients. This retrospective single-institution study included a cohort of 277 GB patients whose 3D post-contrast T1-weighted images and 3D fluid-attenuated inversion recovery (FLAIR) images were acquired using two MRI scanners. Three separate regions of interest (ROIs) showing tumor enhancement, necrosis, and FLAIR hyperintensities were manually segmented for each patient. Two machine learning algorithms (support vector machine (SVM) and random forest) were built for MGMT promoter methylation prediction from a training cohort (196 patients) and tested on a separate validation cohort (81 patients), based on a set of automatically selected radiomic features, with and without demographic variables (i.e., patients' age and sex). In the training set, SVM based on the selected radiomic features of the three separate ROIs achieved the best performances, with an average of 83.0% (standard deviation: 5.7%) for accuracy and 0.894 (0.056) for the area under the curve (AUC) computed through cross-validation. In the test set, all classification performances dropped: the best was obtained by SVM based on the selected features extracted from the whole tumor lesion constructed by merging the three ROIs, with 64.2% (95% confidence interval: 52.8-74.6%) accuracy and 0.572 (0.439-0.705) for AUC. The performances did not change when the patients' age and sex were included with the radiomic features into the models. Our study confirms the presence of a subtle association between imaging characteristics and MGMT promoter methylation status. However, further verification of the strength of this association is needed, as the low diagnostic performance obtained in this validation cohort is not sufficiently robust to allow clinically meaningful predictions.

Subtype Diagnosis of Sporadic Creutzfeldt-Jakob Disease with Diffusion Magnetic Resonance Imaging.

OBJECTIVE: Sporadic Creutzfeldt-Jakob disease (sCJD) comprises several subtypes as defined by genetic and prion protein characteristics, which are associated with distinct clinical and pathological phenotypes. To date, no clinical test can reliably diagnose the subtype. We established two procedures for the antemortem diagnosis of sCJD subtype using diffusion magnetic resonance imaging (MRI). METHODS: MRI of 1,458 patients referred to the National Prion Disease Pathology Surveillance Center were collected through its consultation service. One neuroradiologist blind to the diagnosis scored 12 brain regions and generated a lesion profile for each MRI scan. We selected 487 patients with autopsy-confirmed diagnosis of "pure" sCJD subtype and at least one positive diffusion MRI examination. We designed and tested two data-driven procedures for subtype diagnosis: the first procedure-prion subtype classification algorithm with MRI (PriSCA_MRI)-uses only MRI examinations; the second-PriSCA_MRI + Gen-includes knowledge of the prion protein codon 129 genotype, a major determinant of sCJD subtypes. Both procedures were tested on the first MRI and the last MRI follow-up. RESULTS: PriSCA_MRI classified the 3 most prevalent subtypes with 82% accuracy. PriSCA_MRI + Gen raised the accuracy to 89% and identified all subtypes. Individually, the 2 most prevalent sCJD subtypes, MM1 and VV2, were diagnosed with sensitivities up to 95 and 97%, respectively. The performances of both procedures did not change in 168 patients with longitudinal MRI studies when the last examination was used. INTERPRETATION: This study provides the first practical algorithms for antemortem diagnosis of sCJD subtypes. MRI diagnosis of subtype is likely to be attainable at early disease stages to prognosticate clinical course and design future therapeutic trials. ANN NEUROL 2021;89:560-572.

Kearns-Sayre syndrome: expanding spectrum of a "novel" mitochondrial leukomyeloencephalopathy.

Kearns-Sayre syndrome (KSS) is a rare mitochondrial disease associated to a widespread cerebral leukodystrophy. MRI shows a typical centripetal pattern where U-fibers are mainly affected with a relative spare of periventricular white matter. Recently, different patterns of spinal cord involvement have been described in KSS. Here we report 4 new cases with typical cerebral leukodystrophy associated with spinal cord lesions. A pattern characterized by abnormal signal intensity in the H gray matter and posterior columns was found in 2 patients, while the remaining 2 presented a peculiar involvement of the spinal trigeminal nuclei at the junction of low medulla and cervical cord. MRI spinal cord involvement in KSS is probably an underestimated finding and should be evaluated in the diagnostic work up of these patients.

Characterization of 22q12 Microdeletions Causing Position Effect in Rare NF2 Patients with Complex Phenotypes.

Neurofibromatosis type 2 is an autosomal dominant tumor-prone disorder mainly caused by NF2 point mutations or intragenic deletions. Few individuals with a complex phenotype and 22q12 microdeletions have been described. The 22q12 microdeletions' pathogenic effects at the genetic and epigenetic levels are currently unknown. We here report on 22q12 microdeletions' characterization in three NF2 patients with different phenotype complexities. A possible effect of the position was investigated by in silico analysis of 22q12 topologically associated domains (TADs) and regulatory elements, and by expression analysis of 12 genes flanking patients' deletions. A 147 Kb microdeletion was identified in the patient with the mildest phenotype, while two large deletions of 561 Kb and 1.8 Mb were found in the other two patients, showing a more severe symptomatology. The last two patients displayed intellectual disability, possibly related to AP1B1 gene deletion. The microdeletions change from one to five TADs, and the 22q12 chromatin regulatory landscape, according to the altered expression levels of four deletion-flanking genes, including PIK3IP1, are likely associated with an early ischemic event occurring in the patient with the largest deletion. Our results suggest that the identification of the deletion extent can provide prognostic markers, predictive of NF2 phenotypes, and potential therapeutic targets, thus overall improving patient management.

Gene relevance based on multiple evidences in complex networks.

MOTIVATION: Multi-omics approaches offer the opportunity to reconstruct a more complete picture of the molecular events associated with human diseases, but pose challenges in data analysis. Network-based methods for the analysis of multi-omics leverage the complex web of macromolecular interactions occurring within cells to extract significant patterns of molecular alterations. Existing network-based approaches typically address specific combinations of omics and are limited in terms of the number of layers that can be jointly analysed. In this study, we investigate the application of network diffusion to quantify gene relevance on the basis of multiple evidences (layers). RESULTS: We introduce a gene score (mND) that quantifies the relevance of a gene in a biological process taking into account the network proximity of the gene and its first neighbours to other altered genes. We show that mND has a better performance over existing methods in finding altered genes in network proximity in one or more layers. We also report good performances in recovering known cancer genes. The pipeline described in this article is broadly applicable, because it can handle different types of inputs: in addition to multi-omics datasets, datasets that are stratified in many classes (e.g., cell clusters emerging from single cell analyses) or a combination of the two scenarios. AVAILABILITY AND IMPLEMENTATION: The R package 'mND' is available at URL: https://www.itb.cnr.it/mnd. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hypomyelinating leukodystrophies in adults: Clinical and genetic features.

BACKGROUND AND PURPOSE: Little is known about hypomyelinating leukodystrophies (HLDs) in adults. The aim of this study was to investigate HLD occurrence, clinical features, and etiology among undefined leukoencephalopathies in adulthood. METHODS: We recruited the patients with cerebral hypomyelinating magnetic resonance imaging pattern (mild T2 hyperintensity with normal or near-normal T1 signal) from our cohort of 62 adult index cases with undefined leukoencephalopathies, reviewed their clinical features, and used a leukoencephalopathy-targeted next generation sequencing panel. RESULTS: We identified 25/62 patients (~40%) with hypomyelination. Cardinal manifestations were spastic gait and varying degree of cognitive impairment. Etiology was determined in 44% (definite, 10/25; likely, 1/25). Specifically, we found pathogenic variants in the POLR3A (n = 2), POLR1C (n = 1), RARS1 (n = 1), and TUBB4A (n = 1) genes, which are typically associated with severe early-onset HLDs, and in the GJA1 gene (n = 1), which is associated with oculodentodigital dysplasia. Duplication of a large chromosome X region encompassing PLP1 and a pathogenic GJC2 variant were found in two patients, both females, with early-onset HLDs persisting into adulthood. Finally, we found likely pathogenic variants in PEX3 (n = 1) and PEX13 (n = 1) and potentially relevant variants of unknown significance in TBCD (n = 1), which are genes associated with severe, early-onset diseases with central hypomyelination/dysmyelination. CONCLUSIONS: A hypomyelinating pattern characterizes a relevant number of undefined leukoencephalopathies in adulthood. A comprehensive genetic screening allows definite diagnosis in about half of patients, and demonstrates the involvement of many disease-causing genes, including genes associated with severe early-onset HLDs, and genes causing peroxisome biogenesis disorders.

Immediate versus early non-occlusal loading of dental implants placed flapless in partially edentulous patients: A 10-year randomized clinical trial.

AIM: To compare immediate versus early non-occlusal loading of dental implants placed flapless in a 10-year, parallel group, randomized clinical trial. MATERIALS AND METHODS: Patients were randomized to receive implants for fixed partial dentures. The immediate group was represented by immediate non-occlusal implant loading, whereas the early group was represented by early non-occlusal implant loading. The outcome variables were implant failure, complications, subjective satisfaction and radiographic bone level at implant sites 10 years after loading. RESULTS: Sixty patients were randomized: 30 to the immediately loaded group and 30 to the early loaded group. Three patients dropped out in the immediate group, and three patients dropped out in the early group. One implant failure occurred in the early group (p = 1.0). Three complications occurred in the immediate group and four in the early group (RR = 0.75, 95% CI 0.19 to 3.04, p = 1.0). The difference in bone level was 0.1 mm (95% CI -0.2 to 0.5, p = .3752) favouring the early group. Difference in subjective functional satisfaction was 0.2 (95% CI -0.2 to 0.7; p = .3271). Difference in subjective aesthetic satisfaction was 0.0 (95% CI -0.4 to 0.4; p = .9656). CONCLUSION: At 10-year follow-up, no differences between implants loaded immediately and early were detected in this randomized clinical trial.

isma: an R package for the integrative analysis of mutations detected by multiple pipelines.

BACKGROUND: Recent comparative studies have brought to our attention how somatic mutation detection from next-generation sequencing data is still an open issue in bioinformatics, because different pipelines result in a low consensus. In this context, it is suggested to integrate results from multiple calling tools, but this operation is not trivial and the burden of merging, comparing, filtering and explaining the results demands appropriate software. RESULTS: We developed isma (integrative somatic mutation analysis), an R package for the integrative analysis of somatic mutations detected by multiple pipelines for matched tumor-normal samples. The package provides a series of functions to quantify the consensus, estimate the variability, underline outliers, integrate evidences from publicly available mutation catalogues and filter sites. We illustrate the capabilities of isma analysing breast cancer somatic mutations generated by The Cancer Genome Atlas (TCGA) using four pipelines. CONCLUSIONS: Comparing different "points of view" on the same data, isma generates a unique mutation catalogue and a series of reports that underline common patterns, variability, as well as sites already catalogued by other studies (e.g. TCGA), so as to design and apply filtering strategies to screen more reliable sites. The package is available for non-commercial users at the URL https://www.itb.cnr.it/isma .

Intrauterine fetal MR versus postmortem MR imaging after therapeutic termination of pregnancy: evaluation of the concordance in the detection of brain abnormalities at early gestational stage.

BACKGROUND AND PURPOSE: Fetal postmortem MR Imaging (pmMRI) has been recently used as an adjuvant tool to conventional brain autopsy after termination of pregnancy (TOP). Our purpose was to compare the diagnostic performance of intrauterine MRI (iuMRI) and pmMRI in the detection of brain anomalies in fetuses at early gestational age (GA). MATERIAL AND METHODS: We retrospectively collected 53 fetuses who had undergone iuMRI and pmMRI for suspected brain anomalies. Two pediatric neuroradiologists reviewed iuMRI and pmMRI examinations separately and then together. We used Cohen's K to assess the agreement between pmMRI and iuMRI. Using the combined evaluation iuMRI+pMRI as the reference standard, we calculated the "correctness ratio." We used Somers' D to assess the cograduation between postmortem image quality and time elapsed after fetus expulsion. RESULTS: Our data showed high agreement between iuMRI and pmMRI considering all the categories together, for both observers (K1 0.84; K2 0.86). The correctness ratio of iuMRI and pmMRI was 79% and 45% respectively. The major disagreements between iuMRI and pmMRI were related to postmortem changes as the collapse of liquoral structures and distorting phenomena. We also found a significant cograduation between the time elapsed from expulsion and pmMRI contrast resolution and distortive phenomena (both p < 0.001). CONCLUSIONS: Our study demonstrates an overall high concordance between iuMRI and pmMRI in detecting fetal brain abnormalities at early GA. Nevertheless, for the correct interpretation of pmMRI, the revision of fetal examination seems to be crucial, in particular when time elapsed from expulsion is longer than 24 h. KEY POINTS: • IuMRI and pmMRI showed overall high concordance in detecting fetal brain abnormalities at early GA. • PmMRI corroborated the antemortem diagnosis and it could be a valid alternative to conventional brain autopsy, only when the latter cannot be performed. • Some caution should be taken in interpreting pmMR images when performed after 24 h from fetal death.

Pott's Disease: An Emerging Source of Potentially Inappropriate Treatment.

Spinal Tuberculosis in children is uncommon, even more so in cases of involvement of posterior vertebral elements, and its diagnosis is often delayed. Here we report the case of a young female presenting neuroradiological features and clinical symptoms suspicious for malignant tumor. Histological examination of biopsy specimen evidenced a Pott's disease. We highlight the importance of suspecting this disorder in children with both aspecific systemic and neurological symptoms, in order to reach a timely diagnosis for appropriate and targeted intervention, avoiding the risk of overtreatment and malpractice claims.

An infrastructure for precision medicine through analysis of big data.

BACKGROUND: Nowadays, the increasing availability of omics data, due to both the advancements in the acquisition of molecular biology results and in systems biology simulation technologies, provides the bases for precision medicine. Success in precision medicine depends on the access to healthcare and biomedical data. To this end, the digitization of all clinical exams and medical records is becoming a standard in hospitals. The digitization is essential to collect, share, and aggregate large volumes of heterogeneous data to support the discovery of hidden patterns with the aim to define predictive models for biomedical purposes. Patients' data sharing is a critical process. In fact, it raises ethical, social, legal, and technological issues that must be properly addressed. RESULTS: In this work, we present an infrastructure devised to deal with the integration of large volumes of heterogeneous biological data. The infrastructure was applied to the data collected between 2010-2016 in one of the major diagnostic analysis laboratories in Italy. Data from three different platforms were collected (i.e., laboratory exams, pathological anatomy exams, biopsy exams). The infrastructure has been designed to allow the extraction and aggregation of both unstructured and semi-structured data. Data are properly treated to ensure data security and privacy. Specialized algorithms have also been implemented to process the aggregated information with the aim to obtain a precise historical analysis of the clinical activities of one or more patients. Moreover, three Bayesian classifiers have been developed to analyze examinations reported as free text. Experimental results show that the classifiers exhibit a good accuracy when used to analyze sentences related to the sample location, diseases presence and status of the illnesses. CONCLUSIONS: The infrastructure allows the integration of multiple and heterogeneous sources of anonymized data from the different clinical platforms. Both unstructured and semi-structured data are processed to obtain a precise historical analysis of the clinical activities of one or more patients. Data aggregation allows to perform a series of statistical assessments required to answer complex questions that can be used in a variety of fields, such as predictive and precision medicine. In particular, studying the clinical history of patients that have developed similar pathologies can help to predict or individuate markers able to allow an early diagnosis of possible illnesses.

Single-Shot Version of FLAIR Sequence in the Detection of Intraventricular Anomalies: Preliminary Experience in Fetal MR Imaging.

OBJECTIVE: To evaluate single-shot (ss) FLAIR sequence in the detection of intraventricular anomalies in a series of fetuses showing mild-moderate ventriculomegaly at ultrasound. SUBJECTS AND METHODS: Fetuses with mild-moderate isolated ventriculomegaly, which underwent MR imaging between 2003 and 2014 were considered eligible. Fetuses were examined by standard MR protocol and ss-FLAIR sequence, tailored for snapshot imaging. Two paediatric neuroradiologists evaluated MR images. RESULTS: 542 cases were selected. MR imaging was performed at mean 26 weeks of gestation. ss-FLAIR sequence detected intraventricular findings, consistent with cysts in 10 cases. In 3/10 intraventricular cysts were also evident on ss-FSE T2 and FSE T1-weighted images. In no case diffusion weighted imaging was able to detect cyst. No cyst was highlighted on ss-FSE-T2 and FSE-T1-weighted images, without being visible also on ss-FLAIR. CONCLUSION: ss-FLAIR sequence may be useful to detect intraventricular anomalies especially when fetal position or maternal obesity prevents adequate visualization by ultrasound.