Detecting Alzheimer's Disease Stages and Frontotemporal Dementia in Time Courses of Resting-State fMRI Data Using a Machine Learning Approach.

Early, accurate diagnosis of neurodegenerative dementia subtypes such as Alzheimer's disease (AD) and frontotemporal dementia (FTD) is crucial for the effectiveness of their treatments. However, distinguishing these conditions becomes challenging when symptoms overlap or the conditions present atypically. Resting-state fMRI (rs-fMRI) studies have demonstrated condition-specific alterations in AD, FTD, and mild cognitive impairment (MCI) compared to healthy controls (HC). Here, we used machine learning to build a diagnostic classification model based on these alterations. We curated all rs-fMRIs and their corresponding clinical information from the ADNI and FTLDNI databases. Imaging data underwent preprocessing, time course extraction, and feature extraction in preparation for the analyses. The imaging features data and clinical variables were fed into gradient-boosted decision trees with fivefold nested cross-validation to build models that classified four groups: AD, FTD, HC, and MCI. The mean and 95% confidence intervals for model performance metrics were calculated using the unseen test sets in the cross-validation rounds. The model built using only imaging features achieved 74.4% mean balanced accuracy, 0.94 mean macro-averaged AUC, and 0.73 mean macro-averaged F1 score. It accurately classified FTD (F1 = 0.99), HC (F1 = 0.99), and MCI (F1 = 0.86) fMRIs but mostly misclassified AD scans as MCI (F1 = 0.08). Adding clinical variables to model inputs raised balanced accuracy to 91.1%, macro-averaged AUC to 0.99, macro-averaged F1 score to 0.92, and improved AD classification accuracy (F1 = 0.74). In conclusion, a multimodal model based on rs-fMRI and clinical data accurately differentiates AD-MCI vs. FTD vs. HC.

Prolonged venous transit on perfusion imaging is associated with higher odds of mortality in successfully reperfused patients with large vessel occlusion stroke.

BACKGROUND: Poor venous outflow (VO) profiles are associated with unfavorable outcomes in patients with acute ischemic stroke caused by large vessel occlusion (AIS-LVO), despite achieving successful reperfusion. The objective of this study is to assess the association between mortality and prolonged venous transit (PVT), a novel visual qualitative VO marker on CT perfusion (CTP) time to maximum (Tmax) maps. METHODS: We performed a retrospective analysis of prospectively collected data from consecutive adult patients with AIS-LVO with successful reperfusion (modified Thrombolysis in Cerebral Infarction 2b/2c/3). PVT+ was defined as Tmax ≥10 s timing on CTP Tmax maps in at least one of the following: superior sagittal sinus (proximal venous drainage) and/or torcula (deep venous drainage). PVT- was defined as lacking this in both regions. The primary outcome was mortality at 90 days. In a 1:1 propensity score-matched cohort, regressions were performed to determine the effect of PVT on 90-day mortality. RESULTS: In 127 patients of median (IQR) age 71 (64-81) years, mortality occurred in a significantly greater proportion of PVT+ patients than PVT- patients (32.5% vs 12.6%, P=0.01). This significant difference persisted after matching (P=0.03). PVT+ was associated with a significantly increased likelihood of 90-day mortality (OR 1.22 (95% CI 1.02 to 1.46), P=0.03) in the matched cohort. CONCLUSIONS: PVT+ was significantly associated with 90-day mortality despite successful reperfusion therapy in patients with AIS-LVO. PVT is a simple VO profile marker with potential as an adjunctive metric during acute evaluation of AIS-LVO patients. Future studies will expand our understanding of using PVT in the evaluation of patients with AIS-LVO.

Resting-state fMRI is associated with trauma experiences, mood and psychosis in Afro-descendants with bipolar disorder and schizophrenia.

BACKGROUND: Bipolar disorder (BD) and schizophrenia (SCZ) may exhibit functional abnormalities in several brain areas, including the medial temporal and prefrontal cortex and hippocampus; however, a less explored topic is how brain connectivity is linked to premorbid trauma experiences and clinical features in non-Caucasian samples of SCZ and BD. METHODS: Sixty-two individuals with SCZ (n = 20), BD (n = 21), and healthy controls (HC, n = 21) from indigenous and African ethnicity were submitted to clinical screening (Di-PAD), traumata experiences (ETISR-SF), cognitive and functional MRI assessment. The item psychosis/hallucinations in SCZ patients showed a negative correlation with the global efficiency (GE) in the right dorsal attention network. The items mania, irritable mood, and racing thoughts in the Di-PAD scale had a significant negative correlation with the GE in the parietal right default mode network. CONCLUSIONS: Differences in the activation of specific networks were associated with earlier disease onset, history of physical abuse, and more severe psychotic and mood symptoms in SCZ and BD subjects of indigenous and black ethnicity. Findings provide further evidence on SZ and BD's brain connectivity disturbances, and their clinical significance, in non-Caucasian samples.

Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis.

PURPOSE: In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects. METHODS: We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves. RESULTS: We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however. CONCLUSION: The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.

The association between post-traumatic stress disorder (PTSD) and cognitive impairment: A systematic review of neuroimaging findings.

BACKGROUND: Accumulating evidence suggests that post-traumatic stress disorder (PTSD) may increase the risk of various types of dementia. Despite the large number of studies linking these critical conditions, the underlying mechanisms remain unclear. The past decade has witnessed an exponential increase in interest on brain imaging research to assess the neuroanatomical underpinnings of PTSD. This systematic review provides a critical assessment of available evidence of neuroimaging correlates linking PTSD to a higher risk of dementia. METHODS: The EMBASE, PubMed/MEDLINE, and SCOPUS electronic databases were systematically searched from 1980 to May 22, 2021 for original references on neuroimaging correlates of PTSD and risk of dementia. Literature search, screening of references, methodological quality appraisal of included articles as well as data extractions were independently conducted by at least two investigators. Eligibility criteria included: 1) a clear PTSD definition; 2) a subset of included participants must have developed dementia or cognitive impairment at any time point after the diagnosis of PTSD through any diagnostic criteria; and 3) brain imaging protocols [structural, molecular or functional], including whole-brain morphologic and functional MRI, and PET imaging studies linking PTSD to a higher risk of cognitive impairment/dementia. RESULTS: Overall, seven articles met eligibility criteria, comprising findings from 366 participants with PTSD. Spatially convergent structural abnormalities in individuals with PTSD and co-occurring cognitive dysfunction involved primarily the bilateral frontal (e.g., prefrontal, orbitofrontal, cingulate cortices), temporal (particularly in those with damage to the hippocampi), and parietal (e.g., superior and precuneus) regions. LIMITATIONS: A meta-analysis could not be performed due to heterogeneity and paucity of measurable data in the eligible studies. CONCLUSIONS: Our systematic review provides putative neuroimaging correlates associated with PTSD and co-occurring dementia/cognitive impairment particularly involving the hippocampi. Further research examining neuroimaging features linking PTSD to dementia are clearly an unmet need of the field. Future imaging studies should provide a better control for relevant confounders, such as the selection of more homogeneous samples (e.g., age, race, education), a proper control for co-occurring disorders (e.g., co-occurring major depressive and anxiety disorders) as well as the putative effects of psychotropic medication use. Furthermore, prospective studies examining imaging biomarkers associated with a higher rate of conversion from PTSD to dementia could aid in the stratification of people with PTSD at higher risk for developing dementia for whom putative preventative interventions could be especially beneficial.

White matter microstructural changes in internet addiction disorder: A systematic review of diffusion tensor imaging studies.

Diffusion tensor imaging (DTI) is a kind of magnetic resonance imaging (MRI) modality that helps designate tracts with brain microstructural changes. Internet gaming disorder (IGD) is an internet addiction that can cause many social and personality problems, such as problems in social communication, anxiety, and depression. There are several pieces of evidence showing the impact of this condition on brain regions, and many studies have investigated DTI measurements in these individuals. Therefore, we decided to systematically review the studies that have reported DTI parameters in IGD individuals. We searched the PubMed and Scopus databases to find relevant articles. Two reviewers separately screened the studies, and finally, 14 articles, including diffusion and network studies, were found eligible for our systematic review. Most of the studies reported findings on FA, showing an increase in the thalamus, anterior thalamic radiation, corticospinal tract, and inferior longitudinal fasciculus (ILF), while other regions mentioned in the studies demonstrated inconsistent findings. Moreover, in network studies, IGD individuals showed a decrease in nodal and global efficiencies. In conclusion, our study illuminates the neuropsychological basis of this condition and suggests that internet gaming can correlate with microstructural abnormalities in the central nervous system. Some correlate with the characteristics of online gaming, the addiction state, and the illness's duration.

Resting-state fMRI functional connectivity and clinical correlates in Afro-descendants with schizophrenia and bipolar disorder.

Schizophrenia (SCZ) and bipolar disorder (BD) exhibited altered activation in several brain areas, including the prefrontal and temporal cortex; however, a less explored topic is how brain connectivity and functional disturbances occur in non-Caucasian samples of SCZ and BD. Individuals with SCZ (n=20), BD (n=21), and healthy controls (HC, n=21) from indigenous and African ethnicity were submitted to clinical screening and functional assessments. Mood, compulsive and psychotic symptoms were also correlated to network dysfunction in each group. Two distinct networks' subcomponents demonstrated significant lower global efficiency (GE) in SCZ versus HC, corresponding to left posterior dorsal attention and medial left ventral attention (VA) networks. Lower GE was found in BD versus controls in four subcomponents, including the left medial and right VA. Higher compulsion scores correlated in BD with lower GE in the left VA, whereas increased report of alcohol abuse was associated with higher GE in left default mode network. Although preliminary, differences in the activation of specific networks, notably the left hemisphere, in SCZ versus controls, and lower activation in VA areas, in BD versus controls. Results highlight default mode and salient network as relevant for the emotional processing of SCZ and BD of indigenous and black ethnicity. Abstract: schizophrenia, bipolar disorder, functional neuroimaging, ethnicity, default network.

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

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

Neuroimaging Correlates of Post-Traumatic Stress Disorder in Traumatic Brain Injury: A Systematic Review of the Literature.

Neuroimaging is widely utilized in studying traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD). The risk for PTSD is greater after TBI than after non-TBI trauma, and PTSD is associated with worse outcomes after TBI. Studying the neuroimaging correlates of TBI-related PTSD may provide insights into the etiology of both conditions and help identify those TBI patients most at risk of developing persistent symptoms. The objectives of this systematic review were to examine the current literature on neuroimaging in TBI-related PTSD, summarize key findings, and highlight strengths and limitations to guide future research. A Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) compliant literature search was conducted in PubMed (MEDLINE®), PsycINFO, Embase, and Scopus databases prior to January 2022. The database query yielded 4486 articles, which were narrowed based on specified inclusion criteria to a final cohort of 16 studies, composed of 854 participants with TBI. There was no consensus regarding neuroimaging correlates of TBI-related PTSD among the included articles. A small number of studies suggest that TBI-related PTSD is associated with white matter tract changes, particularly in frontotemporal regions, as well as changes in whole-brain networks of resting-state connectivity. Future studies hoping to identify reliable neuroimaging correlates of TBI-related PTSD would benefit from ensuring consistent case definition, preferably with clinician-diagnosed TBI and PTSD, selection of comparable control groups, and attention to imaging timing post-injury. Prospective studies are needed and should aim to further differentiate predisposing factors from sequelae of TBI-related PTSD.

Clinical application of brain perfusion imaging in detecting stroke mimics: A review.

Stroke mimics constitute a significant proportion of patients with suspected acute ischemic stroke. These conditions may resemble acute ischemic stroke and demonstrate abnormalities on perfusion imaging sequences. The most common stroke mimics include seizure/epilepsy, migraine with aura, brain tumors, functional disorders, infectious encephalopathies, Wernicke's encephalopathy, and metabolic abnormalities. Brain perfusion imaging techniques, particularly computed tomography perfusion and magnetic resonance perfusion, are being widely used in routine clinical practice for treatment selection in patients presenting with large vessel occlusion. At the same time, the utilization of these imaging modalities enables the opportunity to better diagnose patients with stroke mimics in a time-sensitive setting, leading to appropriate management, decision-making, and resource allocation. In this review, we describe patterns of perfusion abnormalities that could discriminate patients with stroke mimics from those with acute ischemic stroke and provide specific case examples to illustrate these perfusion abnormalities. In addition, we discuss the challenges associated with interpretation of perfusion images in stroke-related pathologies. In general, perfusion imaging can provide additional information in some cases-when used in combination with conventional magnetic resonance imaging and computed tomography-and might help in detecting stroke mimics among patients who present with acute onset focal neurological symptoms.

Behavioral and Emotional Dyscontrol Following Traumatic Brain Injury: A Systematic Review of Neuroimaging and Electrophysiological Correlates.

BACKGROUND: Behavioral and emotional dyscontrol commonly occur following traumatic brain injury (TBI). Neuroimaging and electrophysiological correlates of dyscontrol have not been systematically summarized in the literature to date. OBJECTIVE: To complete a systematic review of the literature examining neuroimaging and electrophysiological findings related to behavioral and emotional dyscontrol due to TBI. METHODS: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant literature search was conducted in PubMed (MEDLINE), PsycINFO, EMBASE, and Scopus databases prior to May 2019. The database query yielded 4392 unique articles. These articles were narrowed based on specific inclusion criteria (e.g., clear TBI definition, statistical analysis of the relationship between neuroimaging and dyscontrol). RESULTS: A final cohort of 24 articles resulted, comprising findings from 1552 patients with TBI. Studies included civilian (n = 12), military (n = 10), and sport (n = 2) samples with significant variation in the severity of TBI incorporated. Global and region-based structural imaging was more frequently used to study dyscontrol than functional imaging or diffusion tensor imaging. The prefrontal cortex was the most common neuroanatomical region associated with behavioral and emotional dyscontrol, followed by other frontal and temporal lobe findings. CONCLUSIONS: Frontal and temporal lesions are most strongly implicated in the development of postinjury dyscontrol symptoms although they are also the most frequently investigated regions of the brain for these symptom categories. Future studies can make valuable contributions to the field by (1) emphasizing consistent definitions of behavioral and emotional dyscontrol, (2) assessing premorbid dyscontrol symptoms in subjects, (3) utilizing functional or structural connectivity-based imaging techniques, or (4) restricting analyses to more focused brain regions.

A systematic review and meta-analysis of structural and functional brain alterations in individuals with genetic and clinical high-risk for psychosis and bipolar disorder.

Neuroimaging findings in people at either genetic risk or at clinical high-risk for psychosis (CHR-P) or bipolar disorder (CHR-B) remain unclear. A meta-analytic review of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies in individuals with genetic risk or CHR-P or CHR-B and controls identified 94 datasets (N = 7942). Notwithstanding no significant findings were observed following adjustment for multiple comparisons, several findings were noted at a more liberal threshold. Subjects at genetic risk for schizophrenia or bipolar disorder or at CHR-P exhibited lower gray matter (GM) volumes in the gyrus rectus (Hedges' g = -0.19). Genetic risk for psychosis was associated with GM reductions in the right cerebellum and left amygdala. CHR-P was associated with decreased GM volumes in the frontal superior gyrus and hypoactivation in the right precuneus, the superior frontal gyrus and the right inferior frontal gyrus. Genetic and CHR-P were associated with small structural and functional alterations involving regions implicated in psychosis. Further neuroimaging studies in individuals with genetic or CHR-B are warranted.

Added Value of Arterial Spin Labeling in Detecting Posterior Reversible Encephalopathy Syndrome as a Stroke Mimic on Baseline Neuroimaging: A Single Center Experience.

Differentiating stroke from stroke mimics is a diagnostic challenge in every day practice. Posterior Reversible Encephalopathy Syndrome (PRES) is an important stroke mimic with nonspecific symptomatology, making prompt and accurate diagnosis challenging. Baseline neuroimaging plays a pivotal role in detection and differentiation of stroke from many common mimics and is thus critical in guiding appropriate management. In particular, MR perfusion (MRP) imaging modalities provide added value through detection and quantification of multiple physiological parameters. Arterial Spin Labeling (ASL) is a non-contrast, noninvasive MRP technique increasingly used in clinical practice; however, there is limited description of ASL in PRES in the existing literature. In this single center retrospective pilot study, we investigate the added value of ASL in detecting PRES in the largest series to date. We hope this study can serve as the basis for larger scale investigations exploring the utility of ASL in detecting stroke mimics such as PRES for accurate and efficient management of such patients.

Parotid Warthin's tumor: novel MR imaging score as diagnostic indicator.

OBJECTIVES: Despite known characteristic radiologic and clinical features, differentiation between Warthin's tumor (WT) and other parotid tumors remains challenging. The purpose of this study was to more precisely assess the MR imaging features of WT and to develop a scoring system combining the most specific characteristics. METHODS: A total of 208 patients with parotid gland tumors and presurgical MRI were included. Tumors were divided into 5 histological subtypes, and different MRI features were compared between groups. An MRI scoring test was developed including MR parameters that contributed significantly in distinguishing WT from other tumors. RESULTS: The best MRI features for differentiating between WTs from other tumors included bilaterality (P = 0.002), multifocality (P < 0.001), ADC values <905.1 (P < 0.001), and high signal intensity on T1-W images (P < 0.001). Six or more points on the 14-point scoring MRI scale was associated with an area under the curve of 0.99 (Accuracy of 98%), while a cut-off value of 7 indicated 100% specificity and 100% positive predictive value. CONCLUSIONS: Ill-defined margins, low T1-W signal, and location in the upper 2/3 of the parotid gland excluded WTs in 100% of cases. The proposed scoring method allows WTs to be distinguished from other tumors with high accuracy.

Neuroimaging Correlates of Syndromal Anxiety Following Traumatic Brain Injury: A Systematic Review of the Literature.

BACKGROUND: Traumatic brain injury (TBI) can precipitate new-onset psychiatric symptoms or worsen existing psychiatric conditions. To elucidate specific mechanisms for this interaction, neuroimaging is often used to study both psychiatric conditions and TBI. This systematic review aims to synthesize the existing literature of neuroimaging findings among patients with anxiety after TBI. METHODS: We conducted a Preferred Reporting Items for Systematic Review and Meta-Analyses-compliant literature search via PubMed (MEDLINE), PsychINFO, EMBASE, and Scopus databases before May, 2019. We included studies that clearly defined TBI, measured syndromal anxiety as a primary outcome, and statistically analyzed the relationship between neuroimaging findings and anxiety symptoms. RESULTS: A total of 5982 articles were retrieved from the systematic search, of which 65 studied anxiety and 13 met eligibility criteria. These studies were published between 2004 and 2017, collectively analyzing 764 participants comprised of 470 patients with TBI and 294 non-TBI controls. Imaging modalities used included magnetic resonance imaging, functional magnetic resonance imaging, diffusion tensor imaging, electroencephalogram, magnetic resonance spectrometry, and magnetoencephalography. Eight of 13 studies presented at least one significant finding and together reflect a complex set of changes that lead to anxiety in the setting of TBI. The left cingulate gyrus in particular was found to be significant in 2 studies using different imaging modalities. Two studies also revealed perturbances in functional connectivity within the default mode network. CONCLUSIONS: This is the first systemic review of neuroimaging changes associated with anxiety after TBI, which implicated multiple brain structures and circuits, such as the default mode network. Future research with consistent, rigorous measurements of TBI and syndromal anxiety, as well as attention to control groups, previous TBIs, and time interval between TBI and neuroimaging, are warranted. By understanding neuroimaging correlates of psychiatric symptoms, this work could inform future post-TBI screening and surveillance, preventative efforts, and early interventions to improve neuropsychiatric outcomes.

Can Preoperative Mapping with Functional MRI Reduce Morbidity in Brain Tumor Resection? A Systematic Review and Meta-Analysis of 68 Observational Studies.

Background Preoperative functional MRI (fMRI) is one of several techniques developed to localize critical brain structures and brain tumors. However, the usefulness of fMRI for preoperative surgical planning and its potential effect on neurologic outcomes remain unclear. Purpose To assess the overall postoperative morbidity among patients with brain tumors by using preoperative fMRI versus surgery without this tool or with use of standard (nonfunctional) neuronavigation. Materials and Methods A systematic review and meta-analysis of studies across major databases from 1946 to June 20, 2020, were conducted. Inclusion criteria were original studies that (a) included patients with brain tumors, (b) performed preoperative neuroimaging workup with fMRI, (c) investigated the usefulness of a preoperative or intraoperative functional neuroimaging technique and used that technique to resect cerebral tumors, and (d) reported postoperative clinical measures. Pooled estimates for adverse event rate (ER) effect size (log ER, log odds ratio, or Hedges g) with 95% CIs were computed by using a random-effects model. Results Sixty-eight studies met eligibility criteria (3280 participants; 58.9% men [1555 of 2641]; mean age, 46 years ± 8 [standard deviation]). Functional deterioration after surgical procedure was less likely to occur when fMRI mapping was performed before the operation (odds ratio, 0.25; 95% CI: 0.12, 0.53; P < .001]), and postsurgical Karnofsky performance status scores were higher in patients who underwent fMRI mapping (Hedges g, 0.66; 95% CI: 0.21, 1.11; P = .004]). Craniotomies for tumor resection performed with preoperative fMRI were associated with a pooled adverse ER of 11% (95% CI: 8.4, 13.1), compared with a 21.0% ER (95% CI: 12.2, 33.5) in patients who did not undergo fMRI mapping. Conclusion From the currently available data, the benefit of preoperative functional MRI planning for the resection of brain tumors appears to reduce postsurgical morbidity, especially when used with other advanced imaging techniques, such as diffusion-tensor imaging, intraoperative MRI, or cortical stimulation. © RSNA, 2021 Online supplemental material is available for this article.

Cortical gray matter reduction precedes transition to psychosis in individuals at clinical high-risk for psychosis: A voxel-based meta-analysis.

Gray matter and cortical thickness reductions have been documented in individuals at clinical high-risk for psychosis and may be more pronounced in those who transition to psychosis. However, these findings rely on small samples and are inconsistent across studies. In this review and meta-analysis we aimed to investigate neuroanatomical correlates of clinical high-risk for psychosis and potential predictors of transition, using a novel meta-analytic method (Seed-based d Mapping with Permutation of Subject Images) and cortical mask, combining data from surface-based and voxel-based morphometry studies. Individuals at clinical high-risk for psychosis who later transitioned to psychosis were compared to those who did not and to controls, and included three statistical maps. Overall, individuals at clinical high-risk for psychosis did not differ from controls, however, within the clinical high-risk for psychosis group, transition to psychosis was associated with less cortical gray matter in the right temporal lobe (Hedges' g = -0.377), anterior cingulate and paracingulate (Hedges' g = -0.391). These findings have the potential to help refine prognostic and etiopathological research in early psychosis.

Role of Functional Magnetic Resonance Imaging in the Presurgical Mapping of Brain Tumors.

When planning for brain tumor resection, a balance between maximizing resection and minimizing injury to eloquent brain parenchyma is paramount. The advent of blood oxygenation level-dependent functional magnetic resonance (fMR) imaging has allowed researchers and clinicians to reliably measure physiologic fluctuations in brain oxygenation related to neuronal activity with good spatial resolution. fMR imaging can offer a unique insight into preoperative planning for brain tumors by identifying eloquent areas of the brain affected or spared by the neoplasm. This article discusses the fMR imaging techniques and their applications in neurosurgical planning.

Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks.

PURPOSE: Quantitative bone single-photon emission computed tomography (QBSPECT) has the potential to provide a better quantitative assessment of bone metastasis than planar bone scintigraphy due to its ability to better quantify activity in overlapping structures. An important element of assessing the response of bone metastasis is accurate image segmentation. However, limited by the properties of QBSPECT images, the segmentation of anatomical regions-of-interests (ROIs) still relies heavily on the manual delineation by experts. This work proposes a fast and robust automated segmentation method for partitioning a QBSPECT image into lesion, bone, and background. METHODS: We present a new unsupervised segmentation loss function and its semi- and supervised variants for training a convolutional neural network (ConvNet). The loss functions were developed based on the objective function of the classical Fuzzy C-means (FCM) algorithm. The first proposed loss function can be computed within the input image itself without any ground truth labels, and is thus unsupervised; the proposed supervised loss function follows the traditional paradigm of the deep learning-based segmentation methods and leverages ground truth labels during training. The last loss function is a combination of the first and the second and includes a weighting parameter, which enables semi-supervised segmentation using deep learning neural network. EXPERIMENTS AND RESULTS: We conducted a comprehensive study to compare our proposed methods with ConvNets trained using supervised, cross-entropy and Dice loss functions, and conventional clustering methods. The Dice similarity coefficient (DSC) and several other metrics were used as figures of merit as applied to the task of delineating lesion and bone in both simulated and clinical SPECT/CT images. We experimentally demonstrated that the proposed methods yielded good segmentation results on a clinical dataset even though the training was done using realistic simulated images. On simulated SPECT/CT, the proposed unsupervised model's accuracy was greater than the conventional clustering methods while reducing computation time by 200-fold. For the clinical QBSPECT/CT, the proposed semi-supervised ConvNet model, trained using simulated images, produced DSCs of 0.75 and 0.74 for lesion and bone segmentation in SPECT, and a DSC of 0.79 bone segmentation of CT images. These DSCs were larger than that for standard segmentation loss functions by > 0.4 for SPECT segmentation, and > 0.07 for CT segmentation with P-values < 0.001 from a paired t-test. CONCLUSIONS: A ConvNet-based image segmentation method that uses novel loss functions was developed and evaluated. The method can operate in unsupervised, semi-supervised, or fully-supervised modes depending on the availability of annotated training data. The results demonstrated that the proposed method provides fast and robust lesion and bone segmentation for QBSPECT/CT. The method can potentially be applied to other medical image segmentation applications.