Factors influencing timely diagnosis in neurolymphomatosis.

BACKGROUND: Neurolymphomatosis refers to infiltration of the peripheral nervous system (PNS) by non-Hodgkin lymphoma (NHL). Diagnostic intervals in neurolymphomatosis and factors delaying diagnosis have not been evaluated. We therefore aimed to analyze diagnostic intervals in a large cohort. METHODS: The quality control database at Yale Cancer Center, Section of Neuro-Oncology, was searched for neurolymphomatosis cases diagnosed between 2001 and 2021. Univariate analyses were performed to identify parameters influencing diagnostic intervals. RESULTS: We identified 22 neurolymphomatosis cases including 7 with primary and 15 with secondary disease, which occurred a median (range: 4-144) of 16 months after initial NHL diagnosis. Patients typically presented with painful polyneuropathy (73%), that was asymmetrical and rapidly progressive. Diagnosis was based on PNS biopsy (50%) or integration of neuroimaging findings (50%) with NHL history and diagnostic cerebrospinal fluid examinations. Median interval from symptom onset to diagnosis was 3 months (range: 1-12). Secondary neurolymphomatosis compared to primary disease (median 2 vs. 6 months, p = 0.02), and cases with rapidly-progressive asymmetrical neuropathy as opposed to other presentations (median 2 vs. 6 months; p < 0.001) were diagnosed earlier. Upfront conventional CT compared to other modalities (median 2 vs. 5 months p = 0.04) and nerve root localization as opposed to other disease sites (median 1.5 vs. 4 months; p = 0.04) delayed diagnosis. CONCLUSIONS: NL type and localization, neuropathy course and distribution, and imaging modality selected for initial evaluation influence diagnostic intervals in neurolymphomatosis. Knowledge of this rare entity is critical for early suspicion, and diagnosis.

Surgical strategies for intracranial meningioma in the molecular era.

INTRODUCTION: Surgical resection has long been the treatment of choice for meningiomas and is considered curative in many cases. Indeed, the extent of resection (EOR) remains a significant factor in determining disease recurrence and outcome optimization for patients undergoing surgery. Although the Simpson Grading Scale continues to be widely accepted as the measure of EOR and is used to predict symptomatic recurrence, its utility is under increasing scrutiny. The influence of surgery in the definitive management of meningioma is being re-appraised considering the rapid evolution of our understanding of the biology of meningioma. DISCUSSION: Although historically considered "benign" lesions, meningioma natural history can vary greatly, behaving with unexpectedly high recurrence rates and growth which do not always behave in accordance with their WHO grade. Histologically confirmed WHO grade 1 tumors may demonstrate unexpected recurrence, malignant transformation, and aggressive behavior, underscoring the molecular complexity and heterogeneity. CONCLUSION: As our understanding of the clinical predictive power of genomic and epigenomic factors matures, we here discuss the importance of surgical decision-making paradigms in the context of our rapidly evolving understanding of these molecular features.

Frailty and postoperative outcomes in brain tumor patients: a systematic review subdivided by tumor etiology.

PURPOSE: Frailty has gained prominence in neurosurgical oncology, with more studies exploring its relationship to postoperative outcomes in brain tumor patients. As this body of literature continues to grow, concisely reviewing recent developments in the field is necessary. Here we provide a systematic review of frailty in brain tumor patients subdivided by tumor type, incorporating both modern frailty indices and traditional Karnofsky Performance Status (KPS) metrics. METHODS: Systematic literature review was performed using PRISMA guidelines. PubMed and Google Scholar were queried for articles related to frailty, KPS, and brain tumor outcomes. Only articles describing novel associations between frailty or KPS and primary intracranial tumors were included. RESULTS: After exclusion criteria, systematic review yielded 52 publications. Amongst malignant lesions, 16 studies focused on glioblastoma. Amongst benign tumors, 13 focused on meningiomas, and 6 focused on vestibular schwannomas. Seventeen studies grouped all brain tumor patients together. Seven studies incorporated both frailty indices and KPS into their analyses. Studies correlated frailty with various postoperative outcomes, including complications and mortality. CONCLUSION: Our review identified several patterns of overall postsurgical outcomes reporting for patients with brain tumors and frailty. To date, reviews of frailty in patients with brain tumors have been largely limited to certain frailty indices, analyzing all patients together regardless of lesion etiology. Although this technique is beneficial in providing a general overview of frailty's use for brain tumor patients, given each tumor pathology has its own unique etiology, this combined approach potentially neglects key nuances governing frailty's use and prognostic value.

Interleaved fluid-attenuated inversion recovery (FLAIR) MRI and deuterium metabolic imaging (DMI) on human brain in vivo.

PURPOSE: To integrate deuterium metabolic imaging (DMI) with clinical MRI through an interleaved MRI and DMI acquisition workflow. Interleaved MRI-DMI was enabled with hardware and pulse sequence modifications, and the performance was demonstrated using fluid-attenuated inversion recovery (FLAIR) MRI as an example. METHODS: Interleaved FLAIR-DMI was developed by interleaving the 2 H excitation and acquisition time windows into the intrinsic delay periods presented in the FLAIR method. All 2 H MR signals were up-converted to the 1 H Larmor frequency using a custom-built hardware unit, which also achieved frequency and phase locking of the output signal in real-time. The interleaved measurements were compared with direct measurements both in phantom and in the human brain in vivo. RESULTS: The interleaved MRI-DMI acquisition strategy allowed simultaneous detection of FLAIR MRI and DMI in the same scan time as a FLAIR-only MRI acquisition. Both phantom and in vivo data showed that the MR image quality, DMI sensitivity as well as information content were preserved using interleaved MRI-DMI. CONCLUSION: The interleaved MRI-DMI technology can be used to extend clinical MRI protocols with DMI, thereby offering a metabolic component to the MR imaging contrasts without a penalty on patient comfort or scan time.

Systemic inflammation enhances stimulant-induced striatal dopamine elevation in tobacco smokers.

Immune-brain interactions influence the pathophysiology of addiction. Lipopolysaccharide (LPS)-induced systemic inflammation produces effects on reward-related brain regions and the dopamine system. We previously showed that LPS amplifies dopamine elevation induced by methylphenidate (MP), compared to placebo (PBO), in eight healthy controls. However, the effects of LPS on the dopamine system of tobacco smokers have not been explored. The goal of Study 1 was to replicate previous findings in an independent cohort of tobacco smokers. The goal of Study 2 was to combine tobacco smokers with the aforementioned eight healthy controls to examine the effect of LPS on dopamine elevation in a heterogenous sample for power and effect size determination. Eight smokers were each scanned with [11C]raclopride positron emission tomography three times-at baseline, after administration of LPS (0.8 ng/kg, intravenously) and MP (40 mg, orally), and after administration of PBO and MP, in a double-blind, randomized order. Dopamine elevation was quantified as change in [11C]raclopride binding potential (ΔBPND) from baseline. A repeated-measures ANOVA was conducted to compare LPS and PBO conditions. Smokers and healthy controls were well-matched for demographics, drug dosing, and scanning parameters. In Study 1, MP-induced striatal dopamine elevation was significantly higher following LPS than PBO (p = 0.025, 18 ± 2.9 % vs 13 ± 2.7 %) for smokers. In Study 2, MP-induced striatal dopamine elevation was also significantly higher under LPS than under PBO (p < 0.001, 18 ± 1.6 % vs 11 ± 1.5 %) in the combined sample. Smoking status did not interact with the effect of condition. This is the first study to translate the phenomenon of amplified dopamine elevation after experimental activation of the immune system to an addicted sample which may have implications for drug reinforcement, seeking, and treatment.

In vivo evidence of differential frontal cortex metabolic abnormalities in progressive and relapsing-remitting multiple sclerosis.

The pathophysiology of progressive multiple sclerosis remains elusive, significantly limiting available disease-modifying therapies. Proton MRS (1 H-MRS) enables in vivo measurement of small molecules implicated in multiple sclerosis, but its application to key metabolites glutamate, γ-aminobutyric acid (GABA), and glutathione has been sparse. We employed, at 7 T, a previously validated 1 H-MRS protocol to measure glutamate, GABA, and glutathione, as well as glutamine, N-acetyl aspartate, choline, and myoinositol, in the frontal cortex of individuals with relapsing-remitting (N = 26) or progressive (N = 21) multiple sclerosis or healthy control adults (N = 25) in a cross-sectional analysis. Only individuals with progressive multiple sclerosis demonstrated reduced glutamate (F2,65 = 3.424, p = 0.04; 12.40 ± 0.62 mM versus control 13.17 ± 0.95 mM, p = 0.03) but not glutamine (F2,65 = 0.352, p = 0.7; 4.71 ± 0.35 mM versus control 4.84 ± 0.42 mM), reduced GABA (F2,65 = 3.89, p = 0.03; 1.29 ± 0.23 mM versus control 1.47 ± 0.25 mM, p = 0.05), and possibly reduced glutathione (F2,65 = 0.352, p = 0.056; 2.23 ± 0.46 mM versus control 2.51 ± 0.48 mM, p < 0.1). As a group, multiple sclerosis patients demonstrated significant negative correlations between disease duration and glutamate or GABA (ρ = -0.4, p = 0.02) but not glutamine or glutathione. Alone, only relapsing-remitting multiple sclerosis patients exhibited a significant negative correlation between disease duration and GABA (ρ = -0.5, p = 0.03). Taken together, these results indicate that frontal cortex metabolism is differentially disturbed in progressive and relapsing-remitting multiple sclerosis.

Type of bony involvement predicts genomic subgroup in sphenoid wing meningiomas.

PURPOSE: As sphenoid wing meningiomas (SWMs) are associated with varying degrees of bony involvement, we sought to understand potential relationships between genomic subgroup and this feature. METHODS: Patients treated at Yale-New Haven Hospital for SWM were reviewed. Genomic subgroup was determined via whole exome sequencing, while the extent of bony involvement was radiographically classified as no bone invasion (Type I), hyperostosis only (Type II), tumor invasion only (Type III), or both hyperostosis and tumor invasion (Type IV). Among additional clinical variables collected, a subset of tumors was identified as spheno-orbital meningiomas (SOMs). Machine-learning approaches were used to predict genomic subgroups based on pre-operative clinical features. RESULTS: Among 64 SWMs, 53% had Type-II, 9% had Type-III, and 14% had Type-IV bone involvement; nine SOMs were identified. Tumors with invasion (i.e., Type III or IV) were more likely to be WHO grade II (p: 0.028). Additionally, tumors with invasion were nearly 30 times more likely to harbor NF2 mutations (OR 27.6; p: 0.004), while hyperostosis only were over 4 times more likely to have a TRAF7 mutation (OR 4.5; p: 0.023). SOMs were a significant predictor of underlying TRAF7 mutation (OR 10.21; p: 0.004). CONCLUSIONS: SWMs with invasion into bone tend to be higher grade and are more likely to be NF2 mutated, while SOMs and those with hyperostosis are associated with TRAF7 variants. Pre-operative prediction of molecular subtypes based on radiographic bony characteristics may have significant biological and clinical implications based on known recurrence patterns associated with genomic drivers and grade.

Surgical strategies for older patients with glioblastoma.

OBJECTIVE: While adjuvant treatment regimens have been modified for older patients with glioblastoma (GBM), surgical strategies have not been tailored. METHODS: Clinical data of 48 consecutive patients aged 70 years or older, who underwent surgical resection for GBM with intraoperative ultrasonography (IoUS) alone or combination with intraoperative MRI (IoMRI) at Yale New Haven Hospital were retrospectively reviewed. Variables were analyzed, and comparative analyses were performed. RESULTS: The addition of IoMRI was not superior to IoUS alone in terms of overall survival (OS) (P = 0.306), Karnofsky Performance Score (KPS) at postoperative 6 weeks (P = 0.704) or extent of resection (P = 0.263). Length of surgery (LOSx), however, was significantly longer (P = 0.0002) in the IoMRI group. LOSx (P = 0.015) and hospital stay (P = 0.025) were predictors of postoperative complications. Increased EOR (GTR or NTR) (P = 0.030), postoperative adjuvant treatment (P < 0.0001) and postoperative complications (P = 0.006) were predictive for OS. Patients with relatively lower preoperative KPS scores (<70) showed significant improvement at postoperative 6 weeks (P<0.0001). Patients with complications (P = 0.038) were more likely to have lower KPS at postoperative 6 weeks. CONCLUSIONS: Aggressive management with surgical resection should be considered in older patients with GBM, even those with relatively poor KPS. The use of ioMRI in this population does not appear to confer any measurable benefit over ioUS in experienced hands, but prolongs the length of surgery significantly, which is a preventable prognostic factor for impeding care.

Primary dural lymphomas: Clinical presentation, management, and outcome.

BACKGROUND: Clinical experience is limited for primary central nervous system (CNS) lymphoma that arises from the dura mater, which is denoted with the term primary dural lymphoma (PDL). This study was aimed at determining the relative incidence, presentation, and outcomes of PDL. METHODS: The institutional databases of the Divisions of Neuro-Oncology at the Massachusetts General Hospital and the Yale School of Medicine were retrospectively searched for patients with primary CNS lymphoma. Patients with pathologically confirmed dural lymphoma and no evidence of primary cerebral or systemic involvement were identified. Clinical data, diagnostic findings, treatments, and outcomes were recorded. RESULTS: A total of 20 patients with PDL were identified, and they represented 6.3% of the individuals with primary CNS lymphomas (20 of 316). Histopathological examination of PDL revealed the following underlying subtypes: diffuse large B-cell lymphoma (10 of 20 patients), marginal zone lymphoma (6 of 20), follicular lymphoma (2 of 20), undefined B-cell non-Hodgkin lymphoma (1 of 20), and T-cell non-Hodgkin lymphoma (1 of 20). On imaging, all tumors appeared as extra-axial masses with avid contrast enhancement and mostly mimicked meningioma. The median apparent diffusion coefficient value was 667 ± 26 mm2 /s. Cerebrospinal fluid analyses and symptoms were nonspecific, and the diagnosis rested on tissue analysis. Therapeutic approaches included surgery, radiotherapy, and chemotherapy. The median overall survival was not reached after 5 years. Three patients were deceased at database closure because of tumor progression. The extent of tumor resection correlated positively with overall survival (P = .044). CONCLUSIONS: PDL is a rare variant of primary CNS lymphoma that can be radiographically mistaken for meningioma. The outcome is excellent with multimodality treatment, and aggressive surgery may convey a survival advantage in select cases.

Correction to: A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma.

The original version of this article, published on 05 February 2020, unfortunately contained a mistake.

A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma.

OBJECTIVES: To establish a quantitative MR model that uses clinically relevant features of tumor location and tumor volume to differentiate lower grade glioma (LRGG, grades II and III) and glioblastoma (GBM, grade IV). METHODS: We extracted tumor location and tumor volume (enhancing tumor, non-enhancing tumor, peritumor edema) features from 229 The Cancer Genome Atlas (TCGA)-LGG and TCGA-GBM cases. Through two sampling strategies, i.e., institution-based sampling and repeat random sampling (10 times, 70% training set vs 30% validation set), LASSO (least absolute shrinkage and selection operator) regression and nine-machine learning method-based models were established and evaluated. RESULTS: Principal component analysis of 229 TCGA-LGG and TCGA-GBM cases suggested that the LRGG and GBM cases could be differentiated by extracted features. For nine machine learning methods, stack modeling and support vector machine achieved the highest performance (institution-based sampling validation set, AUC > 0.900, classifier accuracy > 0.790; repeat random sampling, average validation set AUC > 0.930, classifier accuracy > 0.850). For the LASSO method, regression model based on tumor frontal lobe percentage and enhancing and non-enhancing tumor volume achieved the highest performance (institution-based sampling validation set, AUC 0.909, classifier accuracy 0.830). The formula for the best performance of the LASSO model was established. CONCLUSIONS: Computer-generated, clinically meaningful MRI features of tumor location and component volumes resulted in models with high performance (validation set AUC > 0.900, classifier accuracy > 0.790) to differentiate lower grade glioma and glioblastoma. KEY POINTS: • Lower grade glioma and glioblastoma have significant different location and component volume distributions. • We built machine learning prediction models that could help accurately differentiate lower grade gliomas and GBM cases. We introduced a fast evaluation model for possible clinical differentiation and further analysis.

Transverse myelitis following measles vaccination in a rhesus macaque (Macaca mulatta).

A 16-year-old rhesus macaque presented with progressive, ascending quadriparesis following measles vaccination. He was diagnosed with transverse myelitis following MRI, gross necropsy, and histopathology. This is the first report of transverse myelitis in a rhesus macaque following measles vaccination.

Voxel-based logistic analysis of PPMI control and Parkinson's disease DaTscans.

A comprehensive analysis of the Parkinson's Progression Markers Initiative (PPMI) Dopamine Transporter Single Photon Emission Computed Tomography (DaTscan) images is carried out using a voxel-based logistic lasso model. The model reveals that sub-regional voxels in the caudate, the putamen, as well as in the globus pallidus are informative for classifying images into control and PD classes. Further, a new technique called logistic component analysis is developed. This technique reveals that intra-population differences in dopamine transporter concentration and imperfect normalization are significant factors influencing logistic analysis. The interactions with handedness, sex, and age are also evaluated.

Print-Speech Convergence Predicts Future Reading Outcomes in Early Readers.

Becoming a skilled reader requires building a functional neurocircuitry for printed-language processing that integrates with spoken-language-processing networks. In this longitudinal study, functional MRI (fMRI) was used to examine convergent activation for printed and spoken language (print-speech coactivation) in selected regions implicated in printed-language processing (the reading network). We found that print-speech coactivation across the left-hemisphere reading network in beginning readers predicted reading achievement 2 years later beyond the effects of brain activity for either modality alone; moreover, coactivation effects accounted for variance in later reading after controlling for initial reading performance. Within the reading network, effects of coactivation were significant in bilateral inferior frontal gyrus (IFG) and left inferior parietal cortex and fusiform gyrus. The contribution of left and right IFG differed, with more coactivation in left IFG predicting better achievement but more coactivation in right IFG predicting poorer achievement. Findings point to the centrality of print-speech convergence in building an efficient reading circuitry in children.

Glutamate and choline levels predict individual differences in reading ability in emergent readers.

Reading disability is a brain-based difficulty in acquiring fluent reading skills that affects significant numbers of children. Although neuroanatomical and neurofunctional networks involved in typical and atypical reading are increasingly well characterized, the underlying neurochemical bases of individual differences in reading development are virtually unknown. The current study is the first to examine neurochemistry in children during the critical period in which the neurocircuits that support skilled reading are still developing. In a longitudinal pediatric sample of emergent readers whose reading indicators range on a continuum from impaired to superior, we examined the relationship between individual differences in reading and reading-related skills and concentrations of neurometabolites measured using magnetic resonance spectroscopy. Both continuous and group analyses revealed that choline and glutamate concentrations were negatively correlated with reading and related linguistic measures in phonology and vocabulary (such that higher concentrations were associated with poorer performance). Correlations with behavioral scores obtained 24 months later reveal stability for the relationship between glutamate and reading performance. Implications for neurodevelopmental models of reading and reading disability are discussed, including possible links of choline and glutamate to white matter anomalies and hyperexcitability. These findings point to new directions for research on gene-brain-behavior pathways in human studies of reading disability.

Neural correlates of language and non-language visuospatial processing in adolescents with reading disability.

Despite anecdotal evidence of relative visuospatial processing strengths in individuals with reading disability (RD), only a few studies have assessed the presence or the extent of these putative strengths. The current study examined the cognitive and neural bases of visuospatial processing abilities in adolescents with RD relative to typically developing (TD) peers. Using both cognitive tasks and functional magnetic resonance imaging (fMRI) we contrasted printed word recognition with non-language visuospatial processing tasks. Behaviorally, lower reading skill was related to a visuospatial processing advantage (shorter latencies and equivalent accuracy) on a geometric figure processing task, similar to findings shown in two published studies. FMRI analyses revealed key group by task interactions in patterns of cortical and subcortical activation, particularly in frontostriatal networks, and in the distributions of right and left hemisphere activation on the two tasks. The results are discussed in terms of a possible neural tradeoff in visuospatial processing in RD.

A Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging.

Magnetic Resonance Spectroscopic Imaging (MRSI) is a non-invasive imaging technique for studying metabolism and has become a crucial tool for understanding neurological diseases, cancers and diabetes. High spatial resolution MRSI is needed to characterize lesions, but in practice MRSI is acquired at low resolution due to time and sensitivity restrictions caused by the low metabolite concentrations. Therefore, there is an imperative need for a post-processing approach to generate high-resolution MRSI from low-resolution data that can be acquired fast and with high sensitivity. Deep learning-based super-resolution methods provided promising results for improving the spatial resolution of MRSI, but they still have limited capability to generate accurate and high-quality images. Recently, diffusion models have demonstrated superior learning capability than other generative models in various tasks, but sampling from diffusion models requires iterating through a large number of diffusion steps, which is time-consuming. This work introduces a Flow-based Truncated Denoising Diffusion Model (FTDDM) for super-resolution MRSI, which shortens the diffusion process by truncating the diffusion chain, and the truncated steps are estimated using a normalizing flow-based network. The network is conditioned on upscaling factors to enable multi-scale super-resolution. To train and evaluate the deep learning models, we developed a 1H-MRSI dataset acquired from 25 high-grade glioma patients. We demonstrate that FTDDM outperforms existing generative models while speeding up the sampling process by over 9-fold compared to the baseline diffusion model. Neuroradiologists' evaluations confirmed the clinical advantages of our method, which also supports uncertainty estimation and sharpness adjustment, extending its potential clinical applications.

Variations in the genomic profiles and clinical behavior of meningioma by racial and ethnic group.

OBJECTIVE: The influence of socioeconomic factors on racial disparities among patients with sporadic meningiomas is well established, yet other potential causative factors warrant further exploration. The authors of this study aimed to determine whether there is significant variation in the genomic profile of meningiomas among patients of different races and ethnicities and its correlation with clinical outcomes. METHODS: The demographic, genomic, and clinical data of patients aged 18 years and older who had undergone surgery for sporadic meningioma between September 2008 and November 2021 were analyzed. Statistical analyses were performed to detect differences across all racial/ethnic groups, as were direct comparisons between Black and non-Black groups plus Hispanic and non-Hispanic groups. RESULTS: This study included 460 patients with intracranial meningioma. Hispanic patients were significantly younger at surgery (53.9 vs 60.2 years, p = 0.0006) and more likely to show symptoms. Black patients had a higher incidence of anterior skull base tumors (OR 3.2, 95% CI 1.7-6.3, p = 0.0008) and somatic hedgehog mutations (OR 5.3, 95% CI 1.6-16.6, p = 0.003). Hispanics were less likely to exhibit the aggressive genomic characteristic of chromosome 1p deletion (OR 0.28, 95% CI 0.07-1.2, p = 0.06) and displayed higher rates of TRAF7 somatic driver mutations (OR 2.96 95% CI 1.1-7.8, p = 0.036). Black patients had higher rates of recurrence (OR 2.6, 95% CI 1.3-5.2, p = 0.009) and shorter progression-free survival (PFS; HR 2.9, 95% CI 1.6-5.4, p = 0.002) despite extents of resection (EORs) similar to those of non-Black patients (p = 0.745). No significant differences in overall survival were observed among groups. CONCLUSIONS: Despite similar EORs, Black patients had worse clinical outcomes following meningioma resection, characterized by a higher prevalence of somatic hedgehog mutations, increased recurrence rates, and shorter PFS. Meanwhile, Hispanic patients had less aggressive meningiomas, a predisposition for TRAF7 mutations, and no difference in PFS. These findings could inform the care and treatment strategies for meningiomas, and they establish the foundation for future studies focusing on the genomic origins of these observed differences.

A left cerebellar pathway mediates language in prematurely-born young adults.

Preterm (PT) subjects are at risk for developmental delay, and task-based studies suggest that developmental disorders may be due to alterations in neural connectivity. Since emerging data imply the importance of right cerebellar function for language acquisition in typical development, we hypothesized that PT subjects would have alternate areas of cerebellar connectivity, and that these areas would be responsible for differences in cognitive outcomes between PT subjects and term controls at age 20 years. Nineteen PT and 19 term control young adults were prospectively studied using resting-state functional MRI (fMRI) to create voxel-based contrast maps reflecting the functional connectivity of each tissue element in the grey matter through analysis of the intrinsic connectivity contrast degree (ICC-d). Left cerebellar ICC-d differences between subjects identified a region of interest that was used for subsequent seed-based connectivity analyses. Subjects underwent standardized language testing, and correlations with cognitive outcomes were assessed. There were no differences in gender, hand preference, maternal education, age at study, or Peabody Picture Vocabulary Test (PPVT) scores. Functional connectivity (FcMRI) demonstrated increased tissue connectivity in the biventer, simple and quadrangular lobules of the L cerebellum (p<0.05) in PTs compared to term controls; seed-based analyses from these regions demonstrated alterations in connectivity from L cerebellum to both R and L inferior frontal gyri (IFG) in PTs compared to term controls. For PTs but not term controls, there were significant positive correlations between these connections and PPVT scores (R IFG: r=0.555, p=0.01; L IFG: r=0.454, p=0.05), as well as Verbal Comprehension Index (VCI) scores (R IFG: r=0.472, p=0.04). These data suggest the presence of a left cerebellar language circuit in PT subjects at young adulthood. These findings may represent either a delay in maturation or the engagement of alternative neural pathways for language in the developing PT brain.