Changes in Bone Marrow Adipose Tissue in Transgender and Gender Non-Conforming Youth Undergoing Pubertal Suppression: A Pilot Study.

Pubertal suppression with gonadotropin-releasing hormone (GnRH) agonists in transgender and gender non-conforming (TGNC) youth may affect acquisition of peak bone mass. Bone marrow adipose tissue (BMAT) has an inverse relationship with bone mineral density (BMD). To evaluate the effect of pubertal suppression on BMAT, in this pilot study we prospectively studied TGNC youth undergoing pubertal suppression and cisgender control participants with similar pubertal status over a 12-month period. BMD was measured by dual-energy X-ray absorptiometry and peripheral quantitative computed tomography. Magnetic Resonance T1 relaxometry (T1-R) and spectroscopy (MRS) were performed to quantify BMAT at the distal femur. We compared the change in BMD, T1-R values, and MRS lipid indices between the two groups. Six TGNC (two assigned female and four assigned male at birth) and three female control participants (mean age 10.9 and 11.7 years, respectively) were enrolled. The mean lumbar spine BMD Z-score declined by 0.29 in the TGNC group, but increased by 0.48 in controls (between-group difference 0.77, 95% CI: 0.05, 1.45). Similar findings were observed with the change in trabecular volumetric BMD at the 3% tibia site (-4.1% in TGNC, +3.2% in controls, between-group difference 7.3%, 95% CI: 0.5%-14%). Distal femur T1 values declined (indicative of increased BMAT) by 7.9% in the TGNC group, but increased by 2.1% in controls (between-group difference 10%, 95% CI: -12.7%, 32.6%). Marrow lipid fraction by MRS increased by 8.4% in the TGNC group, but declined by 0.1% in controls (between-group difference 8.5%, 95% CI: -50.2%, 33.0%). In conclusion, we observed lower bone mass acquisition and greater increases in BMAT indices by MRI and MRS in TGNC youth after 12 months of GnRH agonists compared with control participants. Early changes in BMAT may underlie an alteration in bone mass acquisition with pubertal suppression, including alterations in mesenchymal stem cells within marrow.

Quantifying radiation therapy response using apparent diffusion coefficient (ADC) parametric mapping of pediatric diffuse intrinsic pontine glioma: a report from the pediatric brain tumor consortium.

BACKGROUND AND PURPOSE: Baseline diffusion or apparent diffusion coefficient (ADC) characteristics have been shown to predict outcome related to DIPG, but the predictive value of post-radiation ADC is less well understood. ADC parametric mapping (FDM) was used to measure radiation-related changes in ADC and compared these metrics to baseline ADC in predicting progression-free survival and overall survival using a large multi-center cohort of DIPG patients (Pediatric Brain Tumor Consortium-PBTC). MATERIALS AND METHODS: MR studies at baseline and post-RT in 95 DIPG patients were obtained and serial quantitative ADC parametric maps were generated from diffusion-weighted imaging based on T2/FLAIR and enhancement regions of interest (ROIs). Metrics assessed included total voxels with: increase in ADC (iADC); decrease in ADC (dADC), no change in ADC (nADC), fraction of voxels with increased ADC (fiADC), fraction of voxels with decreased ADC (fdADC), and the ratio of fiADC and fdADC (fDM Ratio). RESULTS: A total of 72 patients were included in the final analysis. Tumors with higher fiADC between baseline and the first RT time point showed a trend toward shorter PFS with a hazard ratio of 6.44 (CI 0.79, 52.79, p = 0.083). In contrast, tumors with higher log mean ADC at baseline had longer PFS, with a hazard ratio of 0.27 (CI 0.09, 0.82, p = 0.022). There was no significant association between fDM derived metrics and overall survival. CONCLUSIONS: Baseline ADC values are a stronger predictor of outcome compared to radiation related ADC changes in pediatric DIPG. We show the feasibility of employing parametric mapping techniques in multi-center studies to quantitate spatially heterogeneous treatment response in pediatric tumors, including DIPG.

Bone marrow fat content in 70 adolescent girls with anorexia nervosa: Magnetic resonance imaging and magnetic resonance spectroscopy assessment.

BACKGROUND: Adolescents and women with anorexia nervosa have increased bone marrow fat and decreased bone formation, at least in part due to hormonal changes leading to preferential stem cell differentiation to adipocytes over osteoblasts. OBJECTIVE: The purpose of this study was to evaluate marrow fat content and correlate with age and disease severity using knee MRI with T1 relaxometry (T1-R) and MR spectroscopy (MRS) in 70 adolescents with anorexia nervosa. MATERIALS AND METHODS: We enrolled 70 girls with anorexia nervosa who underwent 3-T knee MRI with coronal T1-W images, T1-R and single-voxel proton MRS at 30 and 60 ms TE. Metaphyses were scored visually on the T1-W images for red marrow. Visual T1 score, T1 relaxometry values, MRS lipid indices and fat fractions were analyzed by regression on age, body mass index (BMI) and bone mineral density (BMD) as disease severity markers. MRS measures included unsaturated fat index, T2 water, unsaturated and saturated fat fractions. RESULTS: All red marrow measures declined significantly with age. T1-R values were associated negatively with BMI and BMD for girls ≤16 years (P=0.03 and P=0.002, respectively) and positively for those≥17 years (P=0.05 and P=0.003, respectively). MRS identified a strong inverse association between T2 water and saturated fat fraction from 60 ms TE data (r=-0.85, P<0.0001). There was no association between unsaturated fat index and BMI or BMD. CONCLUSIONS: The association between T1 and BMI and BMD among older girls suggests more marrow fat in those with severe anorexia nervosa. In contrast, the physiological association between marrow fat content and age remained dominant in younger patients. The strong association between T2 water and saturated fat may relate to the restricted mobility of water with increasing marrow fat.

A phase I trial and PK study of cediranib (AZD2171), an orally bioavailable pan-VEGFR inhibitor, in children with recurrent or refractory primary CNS tumors.

BACKGROUND: Cediranib (AZD2171), an oral pan-vascular endothelial growth factor (VEGF) inhibitor, was evaluated in this phase I study to determine its toxicity profile, dose-limiting toxicities (DLTs), maximum-tolerated dose (MTD), pharmacokinetics, and pharmacodynamics in children and adolescents with recurrent or refractory primary central nervous system (CNS) tumors. METHODS: Children and adolescents <22 years were enrolled into one of two strata: stratum I­those not receiving enzyme-inducing anticonvulsant drugs (EIACD) and stratum II­those receiving EIACDs. Dose-level selection was based on the continual reassessment method (CRM). RESULTS: Thirty-six eligible patients with median age of 12.7 years (range, 5.4-21.7 years) in stratum I (24 males) and 12 patients (7 males) in stratum II with median age of 13.4 years (range, 8.9-19.5 years) were initially assessed over a 4-week DLT evaluation period, modified to 6 weeks during the study. An MTD of 32 mg/m(2)/day was declared; however, excessive toxicities (transaminitis, proteinuria, diarrhea, hemorrhage, palmer-planter syndrome, reversible posterior leukoencephalopathy) in the expansion cohort treated at this dose suggested that it might not be tolerated over a longer time period. An expansion cohort at 20 mg/m(2)/day also demonstrated poor longer-term tolerability. Diffusion and perfusion MRI and PET imaging variables as well as biomarker analysis were performed and correlated with outcome. At 20 mg/m(2)/day, the median plasma area under the concentration-time curve at steady state was lower than that observed in adults at similar dosages. CONCLUSIONS: While the MTD of once daily oral cediranib in children with recurrent or progressive CNS tumors was initially defined as 32 mg/m(2)/day, this dose and 20 mg/m(2)/day were not considered tolerable over a protracted time period.

White matter microstructure and cognition in adolescents with congenital heart disease.

OBJECTIVE: To describe the relationship between altered white matter microstructure and neurodevelopment in children with dextro-transposition of the great arteries (d-TGA). STUDY DESIGN: We report correlations between regional white matter microstructure as measured by fractional anisotropy (FA) and cognitive outcome in a homogeneous group of adolescents with d-TGA. Subjects with d-TGA (n = 49) and controls (n = 29) underwent diffusion tensor imaging and neurocognitive testing. In the group with d-TGA, we correlated neurocognitive scores with FA in 14 composite regions of interest in which subjects with d-TGA had lower FA than controls. RESULTS: Among the patients with d-TGA, mathematics achievement correlated with left parietal FA (r = 0.39; P = .006), inattention/hyperactivity symptoms correlated with right precentral FA (r = -0.39; P = .006) and left parietal FA (r = -0.30; P = .04), executive function correlated with right precentral FA (r = -0.30; P = .04), and visual-spatial skills correlated with right frontal FA (r = 0.30; P = .04). We also found an unanticipated correlation between memory and right posterior limb of the internal capsule FA (r = 0.29; P = .047). CONCLUSION: Within the group with d-TGA, regions of reduced white matter microstructure are associated with cognitive performance in a pattern similar to that seen in healthy adolescents and adults. Diminished white matter microstructure may contribute to cognitive compromise in adolescents who underwent open-heart surgery in infancy.

Stepwise Transfer Learning for Expert-Level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning (DL) pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-weighted MRI datasets (May 2001-December 2015) from a national brain tumor consortium (n = 184; median age, 7 years (range: 1-23 years); 94 male) and a pediatric cancer center (n = 100; median age, 8 years (range: 1-19 years); 47 male) to develop and evaluate DL neural networks for pediatric low-grade glioma segmentation using a novel stepwise transfer learning approach to maximize performance in a limited data scenario. The best model was externally-tested on an independent test set and subjected to randomized, blinded evaluation by three clinicians, wherein they assessed clinical acceptability of expert- and artificial intelligence (AI)-generated segmentations via 10-point Likert scales and Turing tests. Results The best AI model used in-domain, stepwise transfer learning (median DSC: 0.88 [IQR 0.72-0.91] versus 0.812 [0.56-0.89] for baseline model; P = .049). On external testing, AI model yielded excellent accuracy using reference standards from three clinical experts (Expert-1: 0.83 [0.75-0.90]; Expert-2: 0.81 [0.70-0.89]; Expert-3: 0.81 [0.68-0.88]; mean accuracy: 0.82)). On clinical benchmarking (n = 100 scans), experts rated AI-based segmentations higher on average compared with other experts (median Likert score: median 9 [IQR 7-9]) versus 7 [IQR 7-9]) and rated more AI segmentations as clinically acceptable (80.2% versus 65.4%). Experts correctly predicted the origin of AI segmentations in an average of 26.0% of cases. Conclusion Stepwise transfer learning enabled expert-level, automated pediatric brain tumor auto-segmentation and volumetric measurement with a high level of clinical acceptability. ©RSNA, 2024.

Noninvasive Molecular Subtyping of Pediatric Low-Grade Glioma with Self-Supervised Transfer Learning.

Purpose To develop and externally test a scan-to-prediction deep learning pipeline for noninvasive, MRI-based BRAF mutational status classification for pediatric low-grade glioma. Materials and Methods This retrospective study included two pediatric low-grade glioma datasets with linked genomic and diagnostic T2-weighted MRI data of patients: Dana-Farber/Boston Children's Hospital (development dataset, n = 214 [113 (52.8%) male; 104 (48.6%) BRAF wild type, 60 (28.0%) BRAF fusion, and 50 (23.4%) BRAF V600E]) and the Children's Brain Tumor Network (external testing, n = 112 [55 (49.1%) male; 35 (31.2%) BRAF wild type, 60 (53.6%) BRAF fusion, and 17 (15.2%) BRAF V600E]). A deep learning pipeline was developed to classify BRAF mutational status (BRAF wild type vs BRAF fusion vs BRAF V600E) via a two-stage process: (a) three-dimensional tumor segmentation and extraction of axial tumor images and (b) section-wise, deep learning-based classification of mutational status. Knowledge-transfer and self-supervised approaches were investigated to prevent model overfitting, with a primary end point of the area under the receiver operating characteristic curve (AUC). To enhance model interpretability, a novel metric, center of mass distance, was developed to quantify the model attention around the tumor. Results A combination of transfer learning from a pretrained medical imaging-specific network and self-supervised label cross-training (TransferX) coupled with consensus logic yielded the highest classification performance with an AUC of 0.82 (95% CI: 0.72, 0.91), 0.87 (95% CI: 0.61, 0.97), and 0.85 (95% CI: 0.66, 0.95) for BRAF wild type, BRAF fusion, and BRAF V600E, respectively, on internal testing. On external testing, the pipeline yielded an AUC of 0.72 (95% CI: 0.64, 0.86), 0.78 (95% CI: 0.61, 0.89), and 0.72 (95% CI: 0.64, 0.88) for BRAF wild type, BRAF fusion, and BRAF V600E, respectively. Conclusion Transfer learning and self-supervised cross-training improved classification performance and generalizability for noninvasive pediatric low-grade glioma mutational status prediction in a limited data scenario. Keywords: Pediatrics, MRI, CNS, Brain/Brain Stem, Oncology, Feature Detection, Diagnosis, Supervised Learning, Transfer Learning, Convolutional Neural Network (CNN) Supplemental material is available for this article. © RSNA, 2024.

Noninvasive molecular subtyping of pediatric low-grade glioma with self-supervised transfer learning.

Purpose: To develop and externally validate a scan-to-prediction deep-learning pipeline for noninvasive, MRI-based BRAF mutational status classification for pLGG. Materials and Methods: We conducted a retrospective study of two pLGG datasets with linked genomic and diagnostic T2-weighted MRI of patients: BCH (development dataset, n=214 [60 (28%) BRAF fusion, 50 (23%) BRAF V600E, 104 (49%) wild-type), and Child Brain Tumor Network (CBTN) (external validation, n=112 [60 (53%) BRAF-Fusion, 17 (15%) BRAF-V600E, 35 (32%) wild-type]). We developed a deep learning pipeline to classify BRAF mutational status (V600E vs. fusion vs. wildtype) via a two-stage process: 1) 3D tumor segmentation and extraction of axial tumor images, and 2) slice-wise, deep learning-based classification of mutational status. We investigated knowledge-transfer and self-supervised approaches to prevent model overfitting with a primary endpoint of the area under the receiver operating characteristic curve (AUC). To enhance model interpretability, we developed a novel metric, COMDist, that quantifies the accuracy of model attention around the tumor. Results: A combination of transfer learning from a pretrained medical imaging-specific network and self-supervised label cross-training (TransferX) coupled with consensus logic yielded the highest macro-average AUC (0.82 [95% CI: 0.70-0.90]) and accuracy (77%) on internal validation, with an AUC improvement of +17.7% and a COMDist improvement of +6.4% versus training from scratch. On external validation, the TransferX model yielded AUC (0.73 [95% CI 0.68-0.88]) and accuracy (75%). Conclusion: Transfer learning and self-supervised cross-training improved classification performance and generalizability for noninvasive pLGG mutational status prediction in a limited data scenario.

Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learning.

Purpose: Artificial intelligence (AI)-automated tumor delineation for pediatric gliomas would enable real-time volumetric evaluation to support diagnosis, treatment response assessment, and clinical decision-making. Auto-segmentation algorithms for pediatric tumors are rare, due to limited data availability, and algorithms have yet to demonstrate clinical translation. Methods: We leveraged two datasets from a national brain tumor consortium (n=184) and a pediatric cancer center (n=100) to develop, externally validate, and clinically benchmark deep learning neural networks for pediatric low-grade glioma (pLGG) segmentation using a novel in-domain, stepwise transfer learning approach. The best model [via Dice similarity coefficient (DSC)] was externally validated and subject to randomized, blinded evaluation by three expert clinicians wherein clinicians assessed clinical acceptability of expert- and AI-generated segmentations via 10-point Likert scales and Turing tests. Results: The best AI model utilized in-domain, stepwise transfer learning (median DSC: 0.877 [IQR 0.715-0.914]) versus baseline model (median DSC 0.812 [IQR 0.559-0.888]; p<0.05). On external testing (n=60), the AI model yielded accuracy comparable to inter-expert agreement (median DSC: 0.834 [IQR 0.726-0.901] vs. 0.861 [IQR 0.795-0.905], p=0.13). On clinical benchmarking (n=100 scans, 300 segmentations from 3 experts), the experts rated the AI model higher on average compared to other experts (median Likert rating: 9 [IQR 7-9]) vs. 7 [IQR 7-9], p<0.05 for each). Additionally, the AI segmentations had significantly higher (p<0.05) overall acceptability compared to experts on average (80.2% vs. 65.4%). Experts correctly predicted the origins of AI segmentations in an average of 26.0% of cases. Conclusions: Stepwise transfer learning enabled expert-level, automated pediatric brain tumor auto-segmentation and volumetric measurement with a high level of clinical acceptability. This approach may enable development and translation of AI imaging segmentation algorithms in limited data scenarios.

Automated temporalis muscle quantification and growth charts for children through adulthood.

Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown normal growth trajectory and reference ranges and lack of standardized measurement. Here, we develop an automated deep learning pipeline to accurately measure temporalis muscle thickness (iTMT) from routine brain magnetic resonance imaging (MRI). We apply iTMT to 23,876 MRIs of healthy subjects, ages 4 through 35, and generate sex-specific iTMT normal growth charts with percentiles. We find that iTMT was associated with specific physiologic traits, including caloric intake, physical activity, sex hormone levels, and presence of malignancy. We validate iTMT across multiple demographic groups and in children with brain tumors and demonstrate feasibility for individualized longitudinal monitoring. The iTMT pipeline provides unprecedented insights into temporalis muscle growth during human development and enables the use of LMM tracking to inform clinical decision-making.

Bone marrow adiposity in pediatric Crohn's disease.

Patients with Crohn's disease often have low bone mineral density and an increased risk of osteoporosis. Although decreased bone formation can be seen at diagnosis, the underlying pathophysiology of suboptimal bone accrual remains poorly understood. We sought to evaluate a novel mechanism affecting osteogenesis in patients with Crohn's disease. In this case series, we evaluated bone marrow composition at the distal femur and proximal tibia of the left knee measured via magnetic resonance (MR) spectroscopy and relaxometry in five adolescents with the diagnosis of Crohn's disease. The subjects were enrolled prospectively between 2011 and 2013 at Boston Children's Hospital. Additional clinical information, including DXA scans to evaluate bone mineral density and body composition, and Crohn's disease history, such as glucocorticoid use and disease duration, were assessed. Healthy adolescents have persistent hematopoietic marrow with only 40 to 50 % fat in the long bone metaphyses. The current participants with Crohn's disease had increased marrow adiposity, with a mean fat fraction of 67.8 %. There appeared to be a trend towards higher fat fraction with shorter disease duration, while participants with the longest disease duration had the lowest fat fraction. Participants also had decreased bone density, increased fat mass, and lower lean mass, as assessed by DXA and compared to pediatric reference data. Our MRI results demonstrate increased marrow adiposity in children with Crohn's disease, especially early in the course of the disease. DXA may better demonstrate longer-term effects on bone. Additional studies are needed to evaluate bone marrow composition in these patients and to elucidate further the inverse relationship between marrow adipocytes and osteogenesis, as well as the relationship between bone marrow adiposity and body composition.

Bone density and bone marrow composition in transgender girls prior to pubertal blockade: A case series.

PURPOSE: To determine bone mineral density (BMD) of transgender girls before pubertal blockade, and correlate with lifestyle and clinical variables. METHODS: Six transfemale peri-pubertal girls had knee magnetic resonance imaging (MRI) with T1-weighted images and single-voxel proton magnetic resonance spectroscopy (MRS). BMD measurements were obtained via dual-energy X-ray absorptiometry. Questionnaires about physical activity, diet, and the Eating Attitudes Test (EAT-26) were completed. The T2 relaxation rate of water (R2 = 1/T2 in s -1) was correlated with scores on surveys. RESULTS: Three participants (50 %) had a low bone mineral density for age based on total body less head Z-score less than -2; two participants (33 %) had a low BMD for age at lumbar spine. All had EAT-26 scores below threshold for clinical concern. All participants self-reported regular exercise. Bone marrow MR variables (T1, fat fraction, unsaturation index and R2 of water) were not correlated with DXA measures. CONCLUSIONS: Participants had low BMD on beginning pubertal blockade. Clinicians should consider monitoring BMD among youth AMAB, a group at potential risk for poor bone health.

DTI assessment of the brainstem white matter tracts in pediatric BSG before and after therapy: a report from the Pediatric Brain Tumor Consortium.

PURPOSE: To assess changes in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values in brainstem gliomas (BSG) in children and to observe the temporal evolution of changes in the white matter tracts following therapy using diffusion tensor imaging (DTI) analysis. METHODS: Serial ADC and FA measurements were obtained in three patients with newly diagnosed BSG on two approved treatment protocols. Values were compared with a set of normative ADC, FA, and eigenvalues of age-matched children of the corticospinal, transverse pontine and medial lemniscal tracts. Fiber tracking of the tracts coursing through the brainstem was performed using standard diffusion tractography analysis. RESULTS: We found increased ADC values within tumor at baseline compared to age-matched controls, with subsequent drop following treatment and subsequent increase with recurrence. Correspondingly, FA values were reduced at presentation, but transiently recovered during the phase of tumor response to treatment, and finally decreased significantly during tumor progression. These changes were concordant with the tractography analysis of white matter tracts in the brainstem. Based on these results, we suggest that initial changes in ADC and FA values reflects tract infiltration by tumor, but not complete disruption, whereas tumor progression results in complete loss of anisotropy possibly due to tract disruption. CONCLUSION: Serial changes in ADC and FA values and tractography data in pediatric BSG suggest initial tumor infiltration, with transient improvement on treatment and subsequent loss of tract anisotropy during tumor progression. This technique may have potential use in assessing response to treatment regimens for pediatric BSG.

Magnetic resonance imaging and spectroscopy evidence of efficacy for adrenal and gonadal hormone replacement therapy in anorexia nervosa.

PURPOSE: Dehydroepiandrosterone (DHEA)+estrogen/progestin therapy for adolescent girls with anorexia nervosa (AN) has the potential to arrest bone loss. The primary aim of this study was to test the effects of DHEA+estrogen/progestin therapy in adolescent girls with AN on bone marrow in the distal femur using magnetic resonance imaging (MRI) and spectroscopy. METHODS: Seventy adolescent girls with AN were enrolled in a double blind, randomized, placebo-controlled trial at two urban hospital-based programs. INTERVENTION: Seventy-six girls were randomly assigned to receive 12months of either oral micronized DHEA or placebo. DHEA was administered with conjugated equine estrogens (0.3mg daily) for 3months, then an oral contraceptive (20µg ethinyl estradiol/ 0.1mg levonorgestrel) for 9months. The primary outcome measure was bone marrow fat by MRI and magnetic resonance spectroscopy (MRS). RESULTS: T2 of the water resonance dropped significantly less in the active vs. placebo group over 12months at both the medial and lateral distal femur (p=0.02). Body mass index (BMI) was a significant effect modifier for T1 and for T2 of unsaturated (T2unsat) and saturated fat (T2sat) in the lateral distal femur. Positive effects of the treatment of DHEA+estrogen/progestin were seen primarily for girls above a BMI of about 18kg/m2. CONCLUSIONS: These findings suggest treatment with oral DHEA+estrogen/progestin arrests the age- and disease-related changes in marrow fat composition in the lateral distal femur reported previously in this population.

Correlation of 18F-FDG PET and MRI Apparent Diffusion Coefficient Histogram Metrics with Survival in Diffuse Intrinsic Pontine Glioma: A Report from the Pediatric Brain Tumor Consortium.

The purpose of this study was to describe baseline 18F-FDG PET voxel characteristics in pediatric diffuse intrinsic pontine glioma (DIPG) and to correlate these metrics with baseline MRI apparent diffusion coefficient (ADC) histogram metrics, progression-free survival (PFS), and overall survival. Methods: Baseline brain 18F-FDG PET and MRI scans were obtained in 33 children from Pediatric Brain Tumor Consortium clinical DIPG trials. 18F-FDG PET images, postgadolinium MR images, and ADC MR images were registered to baseline fluid attenuation inversion recovery MR images. Three-dimensional regions of interest on fluid attenuation inversion recovery MR images and postgadolinium MR images and 18F-FDG PET and MR ADC histograms were generated. Metrics evaluated included peak number, skewness, and kurtosis. Correlation between PET and MR ADC histogram metrics was evaluated. PET pixel values within the region of interest for each tumor were plotted against MR ADC values. The association of these imaging markers with survival was described. Results: PET histograms were almost always unimodal (94%, vs. 6% bimodal). None of the PET histogram parameters (skewness or kurtosis) had a significant association with PFS, although a higher PET postgadolinium skewness tended toward a less favorable PFS (hazard ratio, 3.48; 95% confidence interval [CI], 0.75-16.28 [P = 0.11]). There was a significant association between higher MR ADC postgadolinium skewness and shorter PFS (hazard ratio, 2.56; 95% CI, 1.11-5.91 [P = 0.028]), and there was the suggestion that this also led to shorter overall survival (hazard ratio, 2.18; 95% CI, 0.95-5.04 [P = 0.067]). Higher MR ADC postgadolinium kurtosis tended toward shorter PFS (hazard ratio, 1.30; 95% CI, 0.98-1.74 [P = 0.073]). PET and MR ADC pixel values were negatively correlated using the Pearson correlation coefficient. Further, the level of PET and MR ADC correlation was significantly positively associated with PFS; tumors with higher values of ADC-PET correlation had more favorable PFS (hazard ratio, 0.17; 95% CI, 0.03-0.89 [P = 0.036]), suggesting that a higher level of negative ADC-PET correlation leads to less favorable PFS. A more significant negative correlation may indicate higher-grade elements within the tumor leading to poorer outcomes. Conclusion:18F-FDG PET and MR ADC histogram metrics in pediatric DIPG demonstrate different characteristics with often a negative correlation between PET and MR ADC pixel values. A higher negative correlation is associated with a worse PFS, which may indicate higher-grade elements within the tumor.

Apparent diffusion coefficient histogram metrics correlate with survival in diffuse intrinsic pontine glioma: a report from the Pediatric Brain Tumor Consortium.

BACKGROUND: Diffuse intrinsic pontine glioma (DIPG) is associated with poor survival regardless of therapy. We used volumetric apparent diffusion coefficient (ADC) histogram metrics to determine associations with progression-free survival (PFS) and overall survival (OS) at baseline and after radiation therapy (RT). METHODS: Baseline and post-RT quantitative ADC histograms were generated from fluid-attenuated inversion recovery (FLAIR) images and enhancement regions of interest. Metrics assessed included number of peaks (ie, unimodal or bimodal), mean and median ADC, standard deviation, mode, skewness, and kurtosis. RESULTS: Based on FLAIR images, the majority of tumors had unimodal peaks with significantly shorter average survival. Pre-RT FLAIR mean, mode, and median values were significantly associated with decreased risk of progression; higher pre-RT ADC values had longer PFS on average. Pre-RT FLAIR skewness and standard deviation were significantly associated with increased risk of progression; higher pre-RT FLAIR skewness and standard deviation had shorter PFS. Nonenhancing tumors at baseline showed higher ADC FLAIR mean values, lower kurtosis, and higher PFS. For enhancing tumors at baseline, bimodal enhancement histograms had much worse PFS and OS than unimodal cases and significantly lower mean peak values. Enhancement in tumors only after RT led to significantly shorter PFS and OS than in patients with baseline or no baseline enhancement. CONCLUSIONS: ADC histogram metrics in DIPG demonstrate significant correlations between diffusion metrics and survival, with lower diffusion values (increased cellularity), increased skewness, and enhancement associated with shorter survival, requiring future investigations in large DIPG clinical trials.

Pediatric brain tumor consortium multisite assessment of apparent diffusion coefficient z-axis variation assessed with an ice-water phantom.

RATIONALE AND OBJECTIVES: Magnetic resonance diffusion imaging can characterize physiologic characteristics of pediatric brain tumors used to assess therapy response. The purpose of this study was to assess the variability of the apparent diffusion coefficient (ADC) along z-axis of scanners in the multicenter Pediatric Brain Tumor Consortium (PBTC). MATERIALS AND METHODS: Ice-water diffusion phantoms for each PBTC site were distributed with a specific diffusion imaging protocol. The phantom was scanned four successive times to 1) confirm water in the tube reached thermal equilibrium and 2) allow for assessment of intra-examination ADC repeatability. ADC profiles across slice positions for each vendor and institution combination were characterized using linear regression modeling with a quadratic fit. RESULTS: Eleven sites collected data with a high degree of compliance to the diffusion protocol for each scanner. The mean ADC value at slice position zero for vendor A was 1.123 × 10(-3) mm(2)/s, vendor B was 1.0964 × 10(-3) mm(2)/s, and vendor C was 1.110 × 10(-3) mm(2)/s. The percentage coefficient of variation across all sites was 0.309% (standard deviation = 0.322). The ADC values conformed well to a second-order polynomial along the z-axis, (ie, following a linear model pattern with quadratic fit) for vendor-institution combinations and across vendor-institution combinations as shown in the longitudinal model. CONCLUSIONS: Assessment of the variability of diffusion metrics is essential for establishing the validity of using these quantitative metrics in multicenter trials. The low variability in ADC values across vendors and institutions and validates the use of ADC as a quantitative tumor marker in pediatric multicenter trials.

A functional magnetic resonance imaging study of paced finger tapping in children.

Fourteen typically developing children from 7.9-11.3 years in age were studied with functional magnetic resonance imaging to identify the cerebral loci involved in performance of paced finger tapping by children. Each child performed two bimanual alternating paced finger-tapping tasks. In the first, paced finger tapping was conducted to external 3-Hz pacing provided by a metronome. In the second, the metronome was turned off and finger tapping continued while each child tried to maintain the 3-Hz rhythm by self pacing. Individual and group data were analyzed with statistical parametric mapping techniques that resulted in activation maps for the two tasks. Metronome tapping produced activation of the posterior regions of both superior temporal gyri, both primary sensorimotor cortices, anterodorsomedial cerebellum and supplementary motor area. Self-tapping resulted in recruitment of pre-supplementary motor area and cerebellum in addition to bilateral supplementary motor area and primary sensorimotor cortical activation. Bimanual alternating paced finger tapping performed by children activates a neural network involving primary motor cortex, supplementary motor area, and cerebellum. Posterior superior temporal gyrus may be important for encoding auditory information, and presupplementary motor area and midline cerebellum play an important role in self-paced finger tapping.

18F-FDG PET and MR imaging associations across a spectrum of pediatric brain tumors: a report from the pediatric brain tumor consortium.

UNLABELLED: The purpose of this study was to describe (18)F-FDG uptake across a spectrum of pediatric brain tumors and correlate (18)F-FDG PET with MR imaging variables, progression-free survival (PFS), and overall survival (OS). METHODS: A retrospective analysis was conducted of children enrolled in phase I/II clinical trials through the Pediatric Brain Tumor Consortium from August 2000 to June 2010. PET variables were summarized within diagnostic categories using descriptive statistics. Associations of PET with MR imaging variables and PFS and OS by tumor types were evaluated. RESULTS: Baseline (18)F-FDG PET was available in 203 children; 66 had newly diagnosed brain tumors, and 137 had recurrent/refractory brain tumors before enrolling in a Pediatric Brain Tumor Consortium trial. MR imaging was performed within 2 wk of PET and before therapy in all cases. The (18)F-FDG uptake pattern and MR imaging contrast enhancement (CE) varied by tumor type. On average, glioblastoma multiforme and medulloblastoma had uniform, intense uptake throughout the tumor, whereas brain stem gliomas (BSGs) had low uptake in less than 50% of the tumor and ependymoma had low uptake throughout the tumor. For newly diagnosed BSG, correlation of (18)F-FDG uptake with CE portended reduced OS (P = 0.032); in refractory/recurrent BSG, lack of correlation between (18)F-FDG uptake and CE suggested decreased PFS (P = 0.023). In newly diagnosed BSG for which more than 50% of the tumor had (18)F-FDG uptake, there was a suggestion of lower apparent diffusion coefficient (P = 0.061) and decreased PFS (P = 0.065). CONCLUSION: (18)F-FDG PET and MR imaging showed a spectrum of patterns depending on tumor type. In newly diagnosed BSG, the correlation of (18)F-FDG uptake and CE suggested decreased OS, likely related to more aggressive disease. When more than 50% of the tumor had (18)F-FDG uptake, the apparent diffusion coefficient was lower, consistent with increased cellularity. In refractory/recurrent BSG, poor correlation between (18)F-FDG uptake and CE was associated with decreased PFS, which may reflect concurrent tissue breakdown at sites of treated disease and development of new sites of (18)F-FDG-avid malignancy.

Efficacy of bevacizumab plus irinotecan in children with recurrent low-grade gliomas--a Pediatric Brain Tumor Consortium study.

BACKGROUND: A phase II study of bevacizumab (BVZ) plus irinotecan (CPT-11) was conducted in children with recurrent low-grade glioma to measure sustained response and/or stable disease lasting ≥6 months and progression-free survival. METHODS: Thirty-five evaluable patients received 2 doses (10 mg/kg each) of single-agent BVZ intravenously 2 weeks apart and then BVZ + CPT-11 every 2 weeks until progressive disease, unacceptable toxicity, or a maximum of 2 years of therapy. Correlative studies included neuroimaging and expression of tumor angiogenic markers (vascular endothelial growth factor [VEGF], VEGF receptor 2, hypoxia-inducible factor 2α, and carbonic anhydrase 9). RESULTS: Thirty-five evaluable patients (median age 8.4 y [range, 0.6-17.6]) received a median of 12 courses of BVZ + CPT-11 (range, 2-26). Twenty-nine of 35 patients (83%) received treatment for at least 6 months. Eight patients progressed on treatment at a median time of 5.4 months (range, 1-17.8). Six patients (17.7%) still in follow-up have had stable disease without receiving additional treatment for a median of 40.1 months (range, 30.6-49.3) from initiating therapy. The 6-month and 2-year progression-free survivals were 85.4% (SE ± 5.96%) and 47.8% (SE ± 9.27%), respectively. The commonest toxicities related to BVZ included grades 1-2 hypertension in 24, grades 1-2 fatigue in 23, grades 1-2 epistaxis in 18, and grades 1-4 proteinuria in 15. The median volume of enhancement decreased significantly between baseline and day 15 (P < .0001) and over the duration of treatment (P < .037). CONCLUSION: The combination of BVZ + CPT-11 appears to produce sustained disease control in some children with recurrent low-grade gliomas.