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

Time-to-Event Endpoints in Imaging Biomarker Studies

Time-to-event endpoints are widely used as measures of patients' well-being and indicators of prognosis. In imaging-based biomarker studies, there are increasingly more studies that focus on examining imaging biomarkers' prognostic or predictive utilities on those endpoints, whether in a trial or an observational study setting. In this educational review article, we briefly introduce some basic concepts of time-to-event endpoints and point out potential pitfalls in the context of imaging biomarker research in hope of improving radiologists' understanding of related subjects. Besides, we have included some review and discussions on the benefits of using time-to-event endpoints and considerations on selecting overall survival or progression-free survival for primary analysis. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Magnetic resonance imaging characteristics of brain metastases in small cell lung cancer

BACKGROUND

Lung is the most common primary site of brain metastases (BMs). For different pathological types of BMs have some similar characteristics, it is still a challenge to confirm the origin based on their characteristics directly. BMs of small cell lung cancer (SCLC) have favorable therapeutic expectations due to their high sensitivity to radiotherapy. This study sought to identify unique characteristics of BMs in SCLC, aiming to assist in clinical decision-making.

METHODS

Patients diagnosed with BMs of lung cancer who received radiotherapy from January 2017 to January 2022 were reviewed (N = 284). Definitive diagnosis of BMs of SCLC was reached for 36 patients. All patients underwent head examination using magnetic resonance imaging. The number, size, location, and signal characteristics of lesions were analyzed.

RESULTS

There were 7 and 29 patients with single focus and non-single focus, respectively. Ten patients had diffuse lesions, and the remaining 26 patients had a total of 90 lesions. These lesions were divided into three groups according to size: <1, 1-3, and >3 cm (43.33%, 53.34%, and 3.33%, respectively). Sixty-six lesions were located in the supratentorial area, primarily including cortical and subcortical lesions (55.56%) and deep brain lesions (20%). Moreover, 22 lesions were located in the infratentorial area. According to diffusion-weighted imaging and T1-weighted contrast enhancement, the imaging characteristics were classified into six patterns. Hyperintensity in diffusion-weighted imaging and homogeneous enhancement was the most common pattern of BMs in SCLC (46.67%), while partial lesions showed hyperintensity in diffusion-weighted imaging without enhancement (7.78%).

CONCLUSIONS

The manifestations of BMs in SCLC were multiple lesions (diameter: 1-3 cm), hyperintensity in diffusion-weighted imaging, and homogeneous enhancement. Interestingly, hyperintensity in diffusion-weighted imaging without enhancement was also one of the characteristics.

Correlation between Multiparametric MR Imaging and Molecular Genetics in Pontine Pediatric High-Grade Glioma

BACKGROUND AND PURPOSE

Molecular profiling is a crucial feature in the "integrated diagnosis" of CNS tumors. We aimed to determine whether radiomics could distinguish molecular types of pontine pediatric high-grade gliomas that have similar/overlapping phenotypes on conventional anatomic MR images.

MATERIALS AND METHODS

Baseline MR images from children with pontine pediatric high-grade gliomas were analyzed. Retrospective imaging studies included standard precontrast and postcontrast sequences and DTI. Imaging analyses included median, mean, mode, skewness, and kurtosis of the ADC histogram of the tumor volume based on T2 FLAIR and enhancement at baseline. Histone H3 mutations were identified through immunohistochemistry and/or Sanger or next-generation DNA sequencing. The log-rank test identified imaging factors prognostic of survival from the time of diagnosis. Wilcoxon rank-sum and Fisher exact tests compared imaging predictors among groups.

RESULTS

Eighty-three patients had pretreatment MR imaging and evaluable tissue sampling. The median age was 6 years (range, 0.7-17 years); 50 tumors had a K27M mutation in H3-3A, and 11, in H3C2/3. Seven tumors had histone H3 K27 alteration, but the specific gene was unknown. Fifteen were H3 wild-type. Overall survival was significantly higher in H3C2/3- compared with H3-3A-mutant tumors (P = .003) and in wild-type tumors compared with any histone mutation (P = .001). Lower overall survival was observed in patients with enhancing tumors (P = .02) compared with those without enhancement. H3C2/3-mutant tumors showed higher mean, median, and mode ADC_total values (P < .001) and ADC_enhancement (P < .004), with lower ADC_total skewness and kurtosis (P < .003) relative to H3-3A-mutant tumors.

CONCLUSIONS

ADC histogram parameters are correlated with histone H3 mutation status in pontine pediatric high-grade glioma.

An ultrasound-based radiomics model to distinguish between sclerosing adenosis and invasive ductal carcinoma

Objectives

We aimed to develop an ultrasound-based radiomics model to distinguish between sclerosing adenosis (SA) and invasive ductal carcinoma (IDC) to avoid misdiagnosis and unnecessary biopsies.

Methods

From January 2020 to March 2022, 345 cases of SA or IDC that were pathologically confirmed were included in the study. All participants underwent pre-surgical ultrasound (US), from which clinical information and ultrasound images were collected. The patients from the study population were randomly divided into a training cohort (n = 208) and a validation cohort (n = 137). The US images were imported into MaZda software (Version 4.2.6.0) to delineate the region of interest (ROI) and extract features. Intragroup correlation coefficient (ICC) was used to evaluate the consistency of the extracted features. The least absolute shrinkage and selection operator (LASSO) logistic regression and cross-validation were performed to obtain the radiomics score of the features. Based on univariate and multivariate logistic regression analyses, a model was developed. 56 cases from April 2022 to December 2022 were included for independent validation of the model. The diagnostic performance of the model and the radiomics scores were evaluated by performing the receiver operating characteristic (ROC) analysis. The calibration curve and decision curve analysis (DCA) were used for calibration and evaluation. Leave-One-Out Cross-Validation (LOOCV) was used for the stability of the model.

Results

Three predictors were selected to develop the model, including radiomics score, palpable mass and BI-RADS. In the training cohort, validation cohort and independent validation cohort, AUC of the model and radiomics score were 0.978 and 0.907, 0.946 and 0.886, 0.951 and 0.779, respectively. The model showed a statistically significant difference compared with the radiomics score (p<0.05). The Kappa value of the model was 0.79 based on LOOCV. The Brier score, calibration curve, and DCA showed the model had a good calibration and clinical usefulness.

Conclusions

The model based on radiomics, ultrasonic features, and clinical manifestations can be used to distinguish SA from IDC, which showed good stability and diagnostic performance. The model can be considered a potential candidate diagnostic tool for breast lesions and can contribute to effective clinical diagnosis.

Changes to pediatric brain tumors in 2021 World Health Organization classification of tumors of the central nervous system

New tumor types are continuously being described with advances in molecular testing and genomic analysis resulting in better prognostics, new targeted therapy options and improved patient outcomes. As a result of these advances, pathological classification of tumors is periodically updated with new editions of the World Health Organization (WHO) Classification of Tumors books. In 2021, WHO Classification of Tumors of the Central Nervous System, 5^th edition (CNS5), was published with major changes in pediatric brain tumors officially recognized including pediatric gliomas being separated from adult gliomas, ependymomas being categorized based on anatomical compartment and many new tumor types, most of them seen in children. Additional general changes, such as tumor grading now being done within tumor types rather than across entities and changes in definition of glioblastoma, are also relevant to pediatric neuro-oncology practice. The purpose of this manuscript is to highlight the major changes in pediatric brain tumors in CNS5 most relevant to radiologists. Additionally, brief descriptions of newly recognized entities will be presented with a focus on imaging findings.

Clinical, pathological, and radiological features of 80 pediatric diffuse intrinsic pontine gliomas: A single-institute study

Objective

Diffuse intrinsic pontine gliomas (DIPGs) are rare but devastating diseases. This retrospective cross-sectional study aimed to investigate the clinical, radiological, and pathological features of DIPGs.

Materials and methods

The clinical data of 80 pediatric DIPGs under clinical treatment in Beijing Tiantan Hospital from July 2013 to July 2019 were retrospectively collected and studied. A follow-up evaluation was performed.

Results

This study included 48 men and 32 women. The most common symptoms were cranial nerve palsy (50.0%, 40/80 patients) and limb weakness (41.2%, 33/80 patients). Among the 80 patients, 24 cases were clinically diagnosed, 56 cases were pathologically verified, and 45 cases were tested for H3K27 alteration status, with 34 H3K27 alteration cases confirmed. Radiological results indicated that enhancement was common (65.0%, 52/80 patients). Cho/Cr was of predictive value for H3K27 alteration status (P = 0.012, cutoff value = 2.38, AUC = 0.801). Open cranial surgery followed by further chemotherapy and radiotherapy was beneficial for patients' overall survival. Cox regression analysis indicated H3K27 alteration to be the independent prognostic influencing factor for DIPGs in this series (P = 0.002).

Conclusion

DIPGs displayed a wide spectrum of clinical and imaging features. Surgery-suitable patients could benefit from postoperative comprehensive therapy for a better overall survival. H3K27 alteration was the independent prognostic influencing factor for DIPGs.

Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse Intrinsic Pontine Glioma

Purpose: Biopsy-based assessment of H3 K27 M status helps in predicting survival, but biopsy is usually limited to unusual presentations and clinical trials. We aimed to evaluate whether radiomics can serve as prognostic marker to stratify diffuse intrinsic pontine glioma (DIPG) subsets. Methods: In this retrospective study, diagnostic brain MRIs of children with DIPG were analyzed. Radiomic features were extracted from tumor segmentations and data were split into training/testing sets (80:20). A conditional survival forest model was applied to predict progression-free survival (PFS) using training data. The trained model was validated on the test data, and concordances were calculated for PFS. Experiments were repeated 100 times using randomized versions of the respective percentage of the training/test data. Results: A total of 89 patients were identified (48 females, 53.9%). Median age at time of diagnosis was 6.64 years (range: 1-16.9 years) and median PFS was 8 months (range: 1-84 months). Molecular data were available for 26 patients (29.2%) (1 wild type, 3 K27M-H3.1, 22 K27M-H3.3). Radiomic features of FLAIR and nonenhanced T1-weighted sequences were predictive of PFS. The best FLAIR radiomics model yielded a concordance of .87 [95% CI: .86-.88] at 4 months PFS. The best T1-weighted radiomics model yielded a concordance of .82 [95% CI: .8-.84] at 4 months PFS. The best combined FLAIR + T1-weighted radiomics model yielded a concordance of .74 [95% CI: .71-.77] at 3 months PFS. The predominant predictive radiomic feature matrix was gray-level size-zone. Conclusion: MRI-based radiomics may predict progression-free survival in pediatric diffuse midline glioma/diffuse intrinsic pontine glioma.

Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives

MRI is undoubtedly the cornerstone of brain tumor imaging, playing a key role in all phases of patient management, starting from diagnosis, through therapy planning, to treatment response and/or recurrence assessment. Currently, neuroimaging can describe morphologic and non-morphologic (functional, hemodynamic, metabolic, cellular, microstructural, and sometimes even genetic) characteristics of brain tumors, greatly contributing to diagnosis and follow-up. Knowing the technical aspects, strength and limits of each MR technique is crucial to correctly interpret MR brain studies and to address clinicians to the best treatment strategy. This article aimed to provide an overview of neuroimaging in the assessment of adult primary brain tumors. We started from the basilar role of conventional/morphological MR sequences, then analyzed, one by one, the non-morphological techniques, and finally highlighted future perspectives, such as radiomics and artificial intelligence.

11C-methionine PET imaging characteristics in children with diffuse intrinsic pontine gliomas and relationship to survival and H3 K27M mutation status

PURPOSE

This study aimed to describe ¹¹C-methionine (¹¹C-MET) PET imaging characteristics in patients with paediatric diffuse intrinsic pontine glioma (DIPG) and correlate them with survival and H3 K27M mutation status.

METHODS

We retrospectively analysed 98 children newly diagnosed with DIPG who underwent ¹¹C-MET PET. PET imaging characteristics evaluated included uptake intensity, uniformity, metabolic tumour volume (MTV), and total lesion methionine uptake (TLMU). The maximum, mean, and peak of the tumour-to-background ratio (TBR), calculated as the corresponding standardised uptake values (SUV) divided by the mean reference value, were also recorded. The associations between the PET imaging characteristics and clinical outcomes in terms of progression-free survival (PFS) and overall survival (OS) and H3 K27M mutation status were assessed, respectively.

RESULTS

In univariate analysis, imaging characteristics significantly associated with shorter PFS and OS included a higher uniformity grade, higher TBRs, larger MTV, and higher TLMU. In multivariate analysis, larger MTV at diagnosis, shorter symptom duration, and no treatment were significantly correlated with shorter PFS and OS. The PET imaging features were not correlated with H3 K27M mutation status.

CONCLUSION

Although several imaging features were significantly associated with PFS and OS, only MTV, indicating the size of the active tumour, was identified as a strong independent prognostic factor.

Relative T2-FLAIR signal intensity surrounding residual cavity is associated with survival prognosis in patients with lower-grade gliomas

Aims

To investigate whether the relative signal intensity surrounding the residual cavity on T2-fluid-attenuated inversion recovery (rFLAIR) can improve the survival prediction of lower-grade glioma (LGG) patients.

Methods

Clinical and pathological data and the follow-up MR imaging of 144 patients with LGG were analyzed. We calculated rFLAIR with Image J software. Logistic analysis was used to explore the significant impact factors on progression-free survival (PFS) and overall survival (OS). Several models were set up to predict the survival prognosis of LGG.

Results

A higher rFLAIR [1.81 (0.83)] [median (IQR)] of non-enhancing regions surrounding the residual cavity was detected in the progressed group (n=77) than that [1.55 (0.33)] [median (IQR)] of the not-progressed group (n = 67) (P<0.001). Multivariate analysis showed that lower KPS (≤75), and higher rFLAIR (>1.622) were independent predictors for poor PFS (P<0.05), whereas lower KPS (≤75) and thick-linear and nodular enhancement were the independent predictors for poor OS (P<0.05). The cutoff rFLAIR value of 1.622 could be used to predict poor PFS (HR = 0.31, 95%CI 0.20–0.48) (P<0.001) and OS (HR = 0.27, 95%CI 0.14–0.51) (P=0.002). Both the areas under the ROC curve (AUCs) for predicting poor PFS (AUC, 0.771) and OS (AUC, 0.831) with a combined model that contained rFLAIR were higher than those of any other models.

Conclusion

Higher rFALIR (>1.622) in non-enhancing regions surrounding the residual cavity can be used as a biomarker of the poor survival of LGG. rFLAIR is helpful to improve the survival prediction of posttreatment LGG patients.

Role of apparent diffusion coefficient measurement in differentiating histological subtypes of brain metastasis of lung cancer

OBJECTIVE:

The aim of this study was to investigate the role of apparent diffusion coefficient of diffusion-weighted imaging in differentiating histological subtypes of brain metastasis of lung cancer.

METHODS:

Diffusion-weighted imaging of 158 patients (mean age: 61.2±10.68 years) with brain metastasis of lung cancer (36 small cell lung cancer and 122 non-small cell lung cancer) were retrospectively evaluated. The minimum and mean apparent diffusion coefficient values of the metastasis, apparent diffusion coefficient of edema around the metastasis, and apparent diffusion coefficient of contralateral brain parenchyma were measured. Normalized apparent diffusion coefficient was calculated by proportioning the mean apparent diffusion coefficient of the metastasis to the apparent diffusion coefficient of the contralateral brain parenchyma. Minimum and mean apparent diffusion coefficient of the metastasis, apparent diffusion coefficient of edema around metastasis, and normalized apparent diffusion coefficient were compared between small cell lung cancer and non-small cell lung cancer metastases.

RESULTS:

Minimum apparent diffusion coefficient, mean apparent diffusion coefficient, and normalized apparent diffusion coefficient values of small cell lung cancer metastases (0.43±0.19×10⁻³mm²/s, 0.63±0.20×10⁻³mm²/s, and 0.81 [0.55–1.44], respectively) were significantly lower than those of non-small cell lung cancer metastases (0.71±0.26×10⁻³mm²/s, 0.93±0.29×10⁻³mm²/s, and 1.30 [0.60–3.20], respectively; p<0.001). Mean apparent diffusion coefficient of edema of small cell lung cancer metastases (1.21±0.28×10⁻³mm²/s) was significantly lower than that of non-small cell lung cancer metastases (1.39±0.26×10⁻³mm²/s, p=0.020). The best cutoff values of minimum apparent diffusion coefficient, mean apparent diffusion coefficient, normalized apparent diffusion coefficient, and apparent diffusion coefficient of edema for the differentiation of small cell lung cancer and non-small cell lung cancer were found to be 0.56×10⁻³mm²/s, 0.82×10⁻³mm²/s, 1.085, and 1.21×10⁻³mm²/s, respectively. The area under the receiver operating characteristic curve, sensitivity, and specificity values were, respectively, 0.812, 80.6, and 73.8% for minimum apparent diffusion coefficient; 0.825, 91.7, and 61.5% for mean apparent diffusion coefficient; 0.845, 80.6, and 73.8% for normalized apparent diffusion coefficient; and 0.698, 75.0, and 67.7% for apparent diffusion coefficient of edema.

CONCLUSIONS:

Minimum apparent diffusion coefficient, mean apparent diffusion coefficient, normalized apparent diffusion coefficient, and apparent diffusion coefficient of edema around metastasis can differentiate histological subtypes of brain metastasis of lung cancer.

MR Imaging Characteristics and ADC Histogram Metrics for Differentiating Molecular Subgroups of Pediatric Low-Grade Gliomas

BACKGROUND AND PURPOSE

BRAF and type 1 neurofibromatosis status are distinctive features in pediatric low-grade gliomas with prognostic and therapeutic implications. We hypothesized that DWI metrics obtained through volumetric ADC histogram analyses of pediatric low-grade gliomas at baseline would enable early detection of BRAF and type 1 neurofibromatosis status.

MATERIALS AND METHODS

We retrospectively evaluated 40 pediatric patients with histologically proved pilocytic astrocytoma (n = 33), ganglioglioma (n = 4), pleomorphic xanthoastrocytoma (n = 2), and diffuse astrocytoma grade 2 (n = 1). Apart from 1 patient with type 1 neurofibromatosis who had a biopsy, 11 patients with type 1 neurofibromatosis underwent conventional MR imaging to diagnose a low-grade tumor without a biopsy. BRAF molecular analysis was performed for patients without type 1 neurofibromatosis. Eleven patients presented with BRAF V600E-mutant, 20 had BRAF-KIAA rearrangement, and 8 had BRAF wild-type tumors. Imaging studies were reviewed for location, margins, hemorrhage or calcifications, cystic components, and contrast enhancement. Histogram analysis of tumoral diffusivity was performed.

RESULTS

Diffusion histogram metrics (mean, median, and 10th and 90th percentiles) but not kurtosis or skewness were different among pediatric low-grade glioma subgroups (P < .05). Diffusivity was lowest in BRAF V600E-mutant tumors (the 10th percentile reached an area under the curve of 0.9 on receiver operating characteristic analysis). There were significant differences between evaluated pediatric low-grade glioma margins and cystic components (P = .03 and P = .001, respectively). Well-defined margins were characteristic of BRAF-KIAA or wild-type BRAF rather than BRAF V600E-mutant or type 1 neurofibromatosis tumors. None of the type 1 neurofibromatosis tumors showed a cystic component.

CONCLUSIONS

Imaging features of pediatric low-grade gliomas, including quantitative diffusion metrics, may assist in predicting BRAF and type 1 neurofibromatosis status, suggesting a radiologic-genetic correlation, and might enable early genetic signature characterization.

Standard clinical approaches and emerging modalities for glioblastoma imaging

Glioblastoma (GBM) is the most common primary adult intracranial malignancy and carries a dismal prognosis despite an aggressive multimodal treatment regimen that consists of surgical resection, radiation, and adjuvant chemotherapy. Radiographic evaluation, largely informed by magnetic resonance imaging (MRI), is a critical component of initial diagnosis, surgical planning, and post-treatment monitoring. However, conventional MRI does not provide information regarding tumor microvasculature, necrosis, or neoangiogenesis. In addition, traditional MRI imaging can be further confounded by treatment-related effects such as pseudoprogression, radiation necrosis, and/or pseudoresponse(s) that preclude clinicians from making fully informed decisions when structuring a therapeutic approach. A myriad of novel imaging modalities have been developed to address these deficits. Herein, we provide a clinically oriented review of standard techniques for imaging GBM and highlight emerging technologies utilized in disease characterization and therapeutic development.

Imaging diagnosis and treatment selection for brain tumors in the era of molecular therapeutics

Currently, most CNS tumors require tissue sampling to discern their molecular/genomic landscape. However, growing research has shown the powerful role imaging can play in non-invasively and accurately detecting the molecular signature of these tumors. The overarching theme of this review article is to provide neuroradiologists and neurooncologists with a framework of several important molecular markers, their associated imaging features and the accuracy of those features. A particular emphasis is placed on those tumors and mutations that have specific or promising imaging correlates as well as their respective therapeutic potentials.

MR Imaging of Pediatric Brain Tumors

Primary brain tumors are the most common solid neoplasms in children and a leading cause of mortality in this population. MRI plays a central role in the diagnosis, characterization, treatment planning, and disease surveillance of intracranial tumors. The purpose of this review is to provide an overview of imaging methodology, including conventional and advanced MRI techniques, and illustrate the MRI appearances of common pediatric brain tumors.

MRI-based radiomics signature and clinical factor for predicting H3K27M mutation in pediatric high-grade gliomas located in the midline of the brain

OBJECTIVE

To develop a nomogram based on MRI radiomics and clinical features for preoperatively predicting H3K27M mutation in pediatric high-grade gliomas (pHGGs) with a midline location of the brain.

METHODS

The institutional database was reviewed to identify patients with pHGGs with a midline location of the brain who underwent tumor biopsy with preoperative MRI scans between June 2016 and June 2021. A total of 107 patients with pHGGs, including 79 patients with H3K27M mutation, were consecutively included and randomly divided into training and test sets. Radiomics features were extracted from fluid-attenuated inversion recovery (FLAIR), diffusion-weighted (DW) and post-contrast T1-weighted images, and apparent diffusion coefficient (ADC) maps. The minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) logistic regression were performed for radiomics signature construction. Clinical and radiological features were analyzed to select clinical predictors. A nomogram was then developed by incorporating the radiomics signature and selected clinical predictors.

RESULTS

Nine radiomics features were selected to construct the radiomics signature, which showed a favorable discriminatory ability in training and test sets with an area under the curve (AUC) of 0.95 and 0.92, respectively. Ring enhancement was identified as an independent clinical predictor (p < 0.01). The nomogram, constructed with radiomics signature and ring enhancement, showed good calibration and discrimination in training and testing sets (AUC: 0.95 and 0.90 respectively).

CONCLUSIONS

The nomogram which combined radiomics signature and ring enhancement had a satisfactory ability to predict H3K27M mutation in pHGGs with a midline of the brain.

KEY POINTS

• Conventional MRI features were not powerful enough to predict H3K27M mutation status in pediatric high-grade gliomas (pHGGs) with a midline location of the brain. • An MRI-based radiomics signature showed satisfactory ability to predict H3K27M mutation status of pHGGs located in the midline of the brain. • Associating the radiomics signature with clinical factors improved predictive performance.

ADC Histogram Analysis of Pediatric Low-Grade Glioma Treated with Selumetinib: A Report from the Pediatric Brain Tumor Consortium

BACKGROUND AND PURPOSE

Selumetinib is a promising MAP (mitogen-activated protein) kinase (MEK) 1/2 inhibitor treatment for pediatric low-grade gliomas. We hypothesized that MR imaging-derived ADC histogram metrics would be associated with survival and response to treatment with selumetinib.

MATERIALS AND METHODS

Children with recurrent, refractory, or progressive pediatric low-grade gliomas who had World Health Organization grade I pilocytic astrocytoma with KIAA1549-BRAF fusion or the BRAF V600E mutation (stratum 1), neurofibromatosis type 1-associated pediatric low-grade gliomas (stratum 3), or sporadic non-neurofibromatosis type 1 optic pathway and hypothalamic glioma (OPHG) (stratum 4) were treated with selumetinib for up to 2 years. Quantitative ADC histogram metrics were analyzed for total and enhancing tumor volumes at baseline and during treatment.

RESULTS

Each stratum comprised 25 patients. Stratum 1 responders showed lower values of SD of baseline ADC_total as well as a larger decrease with time on treatment in ADC_total mean, mode, and median compared with nonresponders. Stratum 3 responders showed a greater longitudinal decrease in ADC_total. In stratum 4, higher baseline ADC_total skewness and kurtosis were associated with shorter progression-free survival. When all 3 strata were combined, responders showed a greater decrease with time in ADC_total mode and median. Compared with sporadic OPHG, neurofibromatosis type 1-associated OPHG had lower values of ADC_total mean, mode, and median as well as ADC_enhancement mean and median and higher values of ADC_total skewness and kurtosis at baseline. The longitudinal decrease in ADC_total median during treatment was significantly greater in sporadic OPHG compared with neurofibromatosis type 1-associated OPHG.

CONCLUSIONS

ADC histogram metrics are associated with progression-free survival and response to treatment with selumetinib in pediatric low-grade gliomas.

Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors

Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of individual tumor types. 69 children with biopsy-confirmed brain tumors were recruited into this study. All participants had perfusion and diffusion weighted imaging performed at diagnosis. Imaging data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features. Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumors with different survival characteristics (p < 0.01), which were subsequently classified with high accuracy (98%) by a neural network. Analysis of high-grade tumors showed a marked difference in survival (p = 0.029) between the two clusters with high risk and low risk imaging features. This study has developed a novel model of survival for pediatric brain tumors. Tumor perfusion plays a key role in determining survival and should be considered as a high priority for future imaging protocols.

MRI biomarkers in neuro-oncology

The central role of MRI in neuro-oncology is undisputed. The technique is used, both in clinical practice and in clinical trials, to diagnose and monitor disease activity, support treatment decision-making, guide the use of focused treatments and determine response to treatment. Despite recent substantial advances in imaging technology and image analysis techniques, clinical MRI is still primarily used for the qualitative subjective interpretation of macrostructural features, as opposed to quantitative analyses that take into consideration multiple pathophysiological features. However, the field of quantitative imaging and imaging biomarker development is maturing. The European Imaging Biomarkers Alliance (EIBALL) and Quantitative Imaging Biomarkers Alliance (QIBA) are setting standards for biomarker development, validation and implementation, as well as promoting the use of quantitative imaging and imaging biomarkers by demonstrating their clinical value. In parallel, advanced imaging techniques are reaching the clinical arena, providing quantitative, commonly physiological imaging parameters that are driving the discovery, validation and implementation of quantitative imaging and imaging biomarkers in the clinical routine. Additionally, computational analysis techniques are increasingly being used in the research setting to convert medical images into objective high-dimensional data and define radiomic signatures of disease states. Here, I review the definition and current state of MRI biomarkers in neuro-oncology, and discuss the clinical potential of quantitative image analysis techniques.

Radiogenomics of diffuse intrinsic pontine gliomas (DIPGs): correlation of histological and biological characteristics with multimodal MRI features

OBJECTIVES

The diffuse intrinsic pontine gliomas (DIPGs) are now defined by the type of histone H3 mutated at lysine 27. We aimed to correlate the multimodal MRI features of DIPGs, H3K27M mutant, with their histological and molecular characteristics.

METHODS

Twenty-seven treatment-naïve children with histopathologically confirmed DIPG H3K27M mutant were prospectively included. MRI performed prior to biopsy included multi-b-value diffusion-weighted imaging, ASL, and dynamic susceptibility contrast (DSC) perfusion imaging. The ADC and cerebral blood flow (CBF) and blood volume (CBV) were measured at the biopsy site. We assessed quantitative histological data, including microvascular density, nuclear density, and H3K27M-positive nuclear density. Gene expression profiling was also assessed in the samples. We compared imaging and histopathological data according to histone subgroup. We correlated MRI quantitative data with histological data and gene expression.

RESULTS

H3.1K27M mutated tumors showed higher ADC values (median 3151 μm²/s vs 1741 μm²/s, p = 0.003), and lower perfusion values (DSC-rCBF median 0.71 vs 1.43, p = 0.002, and DSC-rCBV median 1.00 vs 1.71, p = 0.02) than H3.3K27M ones. They had similar microvascular and nuclear density, but lower H3K27M-positive nuclear density (p = 0.007). The DSC-rCBV was positively correlated to the H3K27M-positive nuclear density (rho = 0.74, p = 0.02). ADC values were not correlated with nuclear density nor perfusion values with microvascular density. The expression of gated channel activity-related genes tended to be inversely correlated with ADC values and positively correlated with DSC perfusion.

CONCLUSIONS

H3.1K27M mutated tumors have higher ADC and lower perfusion values than H3.3K27M ones, without direct correlation with microvascular or nuclear density. This may be due to tissular edema possibly related to gated channel activity-related gene expression.

KEY POINTS

• H3.1K27M mutant DIPG had higher apparent diffusion coefficient (p = 0.003), lower α (p = 0.048), and lower relative cerebral blood volume (p = 0.02) than H3.3K27M mutant DIPG at their biopsy sites. • Biopsy samples obtained within the tumor's enhancing portion showed higher microvascular density (p = 0.03) than samples obtained outside the tumor's enhancing portion, but similar H3K27M-positive nuclear density (p = 0.84). • Relative cerebral blood volume measured at the biopsy site was significantly correlated with H3K27M-positive nuclear density (rho = 0.74, p = 0.02).

A phase I/II study of veliparib (ABT-888) with radiation and temozolomide in newly diagnosed diffuse pontine glioma: a Pediatric Brain Tumor Consortium study

BACKGROUND

A Pediatric Brain Tumor Consortium (PBTC) phase I/II trial of veliparib and radiation followed by veliparib and temozolomide (TMZ) was conducted in children with newly diagnosed diffuse intrinsic pontine glioma (DIPG). The objectives were to: (i) estimate the recommended phase II dose (RP2D) of veliparib with concurrent radiation; (ii) evaluate the pharmacokinetic parameters of veliparib during radiation; (iii) evaluate feasibility of intrapatient TMZ dose escalation; (iv) describe toxicities of protocol therapy; and (v) estimate the overall survival distribution compared with historical series.

METHODS

Veliparib was given Monday through Friday b.i.d. during radiation followed by a 4-week rest. Patients then received veliparib at 25 mg/m2 b.i.d. and TMZ 135 mg/m2 daily for 5 days every 28 days. Intrapatient dose escalation of TMZ was investigated for patients experiencing minimal toxicity.

RESULTS

Sixty-six patients (65 eligible) were enrolled. The RP2D of veliparib was 65 mg/m2 b.i.d. with radiation. Dose-limiting toxicities during radiation with veliparib therapy included: grade 2 intratumoral hemorrhage (n = 1), grade 3 maculopapular rash (n = 2), and grade 3 nervous system disorder (generalized neurologic deterioration) (n = 1). Intrapatient TMZ dose escalation during maintenance was not tolerated. Following a planned interim analysis, it was concluded that this treatment did not show a survival benefit compared with PBTC historical controls, and accrual was stopped for futility. The 1- and 2-year overall survival rates were 37.2% (SE 7%) and 5.3% (SE 3%), respectively.

CONCLUSION

Addition of veliparib to radiation followed by TMZ and veliparib was tolerated but did not improve survival for patients with newly diagnosed DIPG.

TRIAL REGISTRATION

NCT01514201.

MR imaging features of diffuse intrinsic pontine glioma and relationship to overall survival: report from the International DIPG Registry

BACKGROUND

This study describes imaging features of diffuse intrinsic pontine glioma (DIPG) and correlates with overall survival (OS) and histone mutation status in the International DIPG Registry (IDIPGR).

METHODS

Four hundred cases submitted to the IDIPGR with a local diagnosis of DIPG and baseline MRI were evaluated by consensus review of 2 neuroradiologists; 43 cases were excluded (inadequate imaging or alternative diagnoses). Agreement between reviewers, association with histone status, and univariable and multivariable analyses relative to OS were assessed.

RESULTS

On univariable analysis imaging features significantly associated with worse OS included: extrapontine extension, larger size, enhancement, necrosis, diffusion restriction, and distant disease. On central review, 9.5% of patients were considered not to have DIPG. There was moderate mean agreement of MRI features between reviewers. On multivariable analysis, chemotherapy, age, and distant disease were predictors of OS. There was no difference in OS between wild-type and H3 mutated cases. The only imaging feature associated with histone status was the presence of ill-defined signal infiltrating pontine fibers.

CONCLUSIONS

Baseline imaging features are assessed in the IDIPGR. There was a 9.5% discordance in DIPG diagnosis between local and central review, demonstrating need for central imaging confirmation for prospective trials. Although several imaging features were significantly associated with OS (univariable), only age and distant disease were significant on multivariable analyses. There was limited association of imaging features with histone mutation status, although numbers are small and evaluation exploratory.

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study

Background

Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model.

Methods

We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables.

Results

All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61–0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49–0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64–0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51–0.67], Noether’s test P = .02).

Conclusions

In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance.

Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors

Simple Summary

Advanced neuroimaging is gaining increasing relevance for the characterization and the molecular profiling of brain tumor tissue. On one hand, for some tumor types, the most widespread advanced techniques, investigating diffusion and perfusion features, have been proven clinically feasible and rather robust for diagnosis and prognosis stratification. In addition, 2-hydroxyglutarate spectroscopy, for the first time, offers the possibility to directly measure a crucial molecular marker. On the other hand, numerous innovative approaches have been explored for a refined evaluation of tumor microenvironments, particularly assessing microstructural and microvascular properties, and the potential applications of these techniques are vast and still to be fully explored.

Abstract

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.

A pilot radiogenomic study of DIPG reveals distinct subgroups with unique clinical trajectories and therapeutic targets

An adequate understanding of the relationships between radiographic and genomic features in diffuse intrinsic pontine glioma (DIPG) is essential, especially in the absence of universal biopsy, to further characterize the molecular heterogeneity of this disease and determine which patients are most likely to respond to biologically-driven therapies. Here, a radiogenomics analytic approach was applied to a cohort of 28 patients with DIPG. Tumor size and imaging characteristics from all available serial MRIs were evaluated by a neuro-radiologist, and patients were divided into three radiographic response groups (partial response [PR], stable disease [SD], progressive disease [PD]) based on MRI within 2 months of radiotherapy (RT) completion. Whole genome and RNA sequencing were performed on autopsy tumor specimens. We report several key, therapeutically-relevant findings: (1) Certain radiologic features on first and subsequent post-RT MRIs are associated with worse overall survival, including PD following irradiation as well as present, new, and/or increasing peripheral ring enhancement, necrosis, and diffusion restriction. (2) Upregulation of EMT-related genes and distant tumor spread at autopsy are observed in a subset of DIPG patients who exhibit poorer radiographic response to irradiation and/or higher likelihood of harboring H3F3A mutations, suggesting possible benefit of upfront craniospinal irradiation. (3) Additional genetic aberrations were identified, including DYNC1LI1 mutations in a subgroup of patients with PR on post-RT MRI; further investigation into potential roles in DIPG tumorigenesis and/or treatment sensitivity is necessary. (4) Whereas most DIPG tumors have an immunologically “cold” microenvironment, there appears to be a subset which harbor a more inflammatory genomic profile and/or higher mutational burden, with a trend toward improved overall survival and more favorable radiographic response to irradiation, in whom immunotherapy should be considered. This study has begun elucidating relationships between post-RT radiographic response with DIPG molecular profiles, revealing radiogenomically distinct subgroups with unique clinical trajectories and therapeutic targets.

Retrospective analysis of the clinical and radiological features of 94 consecutive DIPGs patients to investigate the factors determining the development of hydrocephalus and its impact on clinical status and survival

PURPOSE

There is no consensus in the literature about the impact of hydrocephalus on clinical course and overall survival of diffuse intrinsic pontine gliomas (DIPG) patients as well as about its specific treatment. Authors reviewed a series of DIPG patients to investigate factors related to the onset of hydrocephalus, its treatment, and its impact on clinical course and prognosis.

METHODS

A retrospective observational study was performed enrolling pediatric patients affected by DIPG from 2008 to 2018. Clinical and radiological charts were reviewed to find patients' demographic, pathologic and radiologic features in hydrocephalic and non-hydrocephalic patients. In the hydrocephalus cohort, treatment strategy and its effectiveness and complications were analyzed.

RESULTS

Ninety-four pediatric patients were enrolled in the study. Patients who developed hydrocephalus showed significantly lesser maximum axial tumor areas than patients without hydrocephalus (respectively 6.5 cm² vs 16.45 cm², p < 0.005). Hydrocephalus developed in 33 patients (35%) with an onset interval of 5.24 ± 1.21 months (range 3.2-7.3). The majority of hydrocephalic patients (28 cases, 90%) were treated by ventriculoperitoneal shunt, the remaining 3 patients being treated by endoscopic third ventriculostomy. Mean overall survival was 16.6 months ± 20 months without significative difference between the groups.

CONCLUSION

The onset of hydrocephalus occurs in the first moths of the disease story and found a negative correlation with tumor maximal axial diameter. Early treatment of hydrocephalus presents a very low complications rate with satisfying clinical outcome, as it allows the patients to continue the neurooncological therapies being a part of the treatment armamentarium instead of a palliative solution.

Correlation of multimodal 18F-DOPA PET and conventional MRI with treatment response and survival in children with diffuse intrinsic pontine gliomas

To evaluate the contribution of ¹⁸F-dihydroxyphenylalanine (DOPA) PET in association with conventional MRI in predicting treatment response and survival outcome of pediatric patients with diffuse intrinsic pontine gliomas (DIPGs).

Methods: We retrospectively analyzed 19 children with newly diagnosed DIPGs who underwent ¹⁸F-DOPA PET/CT and conventional MRI within one week of each other at admission and subsequent MRI follow-up. Following co-registration and fusion of PET and MRI, ¹⁸F-DOPA uptake avidity and extent (PET tumor volume and uniformity) at admission, along with MRI indices including presence of ring contrast-enhancement, tumor volume at admission and at maximum response following first-line treatment, were evaluated and correlated with overall survival (OS). The association between ¹⁸F-DOPA uptake tumor volume at admission and MRI tumor volume following treatment was evaluated. Statistics included Wilcoxon signed-rank and Mann-Whitney U tests, Kaplan-Meier OS curve and Cox analysis.

Results: DIPGs with a ¹⁸F-DOPA uptake Tumor/Striatum (T/S) ratio >1 presented an OS ≤ 12 months and lower degree of tumor volume reduction following treatment (p = 0.001). On multivariate analysis, T/S (p = 0.001), ring enhancement (p = 0.01) and the degree of MRI tumor volume reduction (p = 0.01) independently correlated with OS. In all patients, areas of increased ¹⁸F-DOPA uptake overlapped with regions demonstrating more prominent residual components/lack of response following treatment.

Conclusions:¹⁸F-DOPA PET provides useful information for evaluating the metabolism of DIPGs. T/S ratio is an independent predictor of outcome. ¹⁸F-DOPA uptake extent delineates tumoral regions with a more aggressive biological behaviour, less sensitive to first line treatment.

Advanced Imaging in Musculoskeletal Oncology: Moving Away From RECIST and Embracing Advanced Bone and Soft Tissue Tumor Imaging (ABASTI) - Part I - Tumor Response Criteria and Established Functional Imaging Techniques

According to the Revised Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, the majority of bone metastases are considered to be nonmeasurable disease. Traditional response criteria rely on physical measurements. New criteria would be valuable if they incorporated newly developed imaging features in order to provide a more comprehensive assessment of oncological status. Advanced magnetic resonance imaging (MRI) sequences such as diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) with dynamic contrast-enhanced (DCE) perfusion imaging are reviewed in the context of the initial and post-therapeutic assessment of musculoskeletal tumors. Particular attention is directed to the pseudoprogression phenomenon in which a successfully treated tumor enlarges from the pretherapeutic baseline, followed by regression without a change in therapy.

Improving long-term survival in diffuse intrinsic pontine glioma

INTRODUCTION

Diffuse intrinsic pontine glioma (DIPG) is an almost universally fatal pediatric brain cancer. There has been no improvement in event-free survival (EFS) or overall survival (OS) despite immense effort through a multitude of clinical trials to find a cure. Recently, there has been a surge in the knowledge of DIPG biology, including the discovery of a recurrent H3F3A mutation in over 80% of these tumors.

AREAS COVERED

The authors review the most recent approaches to diagnosis and treatment of DIPG including chemotherapy, biologics, surgical approaches, and immunotherapy.

EXPERT OPINION

The authors propose four main opportunities to improve long-term survival. First, patients should be enrolled in scientifically sound clinical trials that include molecularly profiling either via stereotactic biopsy or liquid biopsy. Second, clinical trials should include more innovative endpoints other than traditional EFS and OS such as MRI/PET imaging findings combined with surrogates of activity (e.g. serial liquid biopsies) to better ascertain biologically active treatments. Third, innovative clinical trial approaches are needed to help allow for the rapid development of combination therapies to be tested. Finally, effort should be concentrated on reversing the effects of the histone mutation, as this malfunctioning development program seems to be key to DIPG relentlessness.

MR Imaging Correlates for Molecular and Mutational Analyses in Children with Diffuse Intrinsic Pontine Glioma

BACKGROUND AND PURPOSE

Recent advances in molecular techniques have characterized distinct subtypes of diffuse intrinsic pontine gliomas. Our aim was the identification of MR imaging correlates of these subtypes.

MATERIALS AND METHODS

Initial MRIs from subjects with diffuse intrinsic pontine gliomas recruited for a prospective clinical trial before treatment were analyzed. Retrospective imaging analyses included FLAIR/T2 tumor volume, tumor volume enhancing, the presence of cyst and/or necrosis, median, mean, mode, skewness, kurtosis of ADC tumor volume based on FLAIR, and enhancement at baseline. Molecular subgroups based on EGFR and MGMT mutations were established. Histone mutations were also determined (H3F3A, HIST1H3B, HIST1H3C). Univariate Cox proportional hazards regression was used to test the association of imaging predictors with overall and progression-free survival. Wilcoxon rank sum, Kruskal-Wallis, and Fisher exact tests were used to compare imaging measures among groups.

RESULTS

Fifty patients had biopsy and MR imaging. The median age at trial registration was 6 years (range, 3.3-17.5 years); 52% were female. On the basis of immunohistochemical results, 48 patients were assigned to 1 of 4 subgroups: 28 in MGMT-/epidermal growth factor receptor (EGFR)-, 14 in MGMT-/EGFR+, 3 in MGMT+/EGFR-, and 3 in MGMT+/EGFR+. Twenty-three patients had histone mutations in H3F3A, 8 in HIST1H3B, and 3 in HIST1H3C. Enhancing tumor volume was near-significantly different across molecular subgroups (P = .04), after accounting for the false discovery rate. Tumor volume enhancing, median, mode, skewness, and kurtosis ADC T2-FLAIR/T2 were significantly different (P ≤ .048) between patients with H3F3A and HIST1H3B/C mutations.

CONCLUSIONS

MR imaging features including enhancement and ADC histogram parameters are correlated with molecular subgroups and mutations in children with diffuse intrinsic pontine gliomas.

Advanced ADC Histogram, Perfusion, and Permeability Metrics Show an Association with Survival and Pseudoprogression in Newly Diagnosed Diffuse Intrinsic Pontine Glioma: A Report from the Pediatric Brain Tumor Consortium

BACKGROUND AND PURPOSE

Diffuse intrinsic pontine glioma is a lethal childhood brain cancer with dismal prognosis and MR imaging is the primary methodology used for diagnosis and monitoring. Our aim was to determine whether advanced diffusion, perfusion, and permeability MR imaging metrics predict survival and pseudoprogression in children with newly diagnosed diffuse intrinsic pontine glioma.

MATERIALS AND METHODS

A clinical trial using the poly (adenosine diphosphate ribose) polymerase (PARP) inhibitor veliparib concurrently with radiation therapy, followed by maintenance therapy with veliparib + temozolomide, in children with diffuse intrinsic pontine glioma was conducted by the Pediatric Brain Tumor Consortium. Standard MR imaging, DWI, dynamic contrast-enhanced perfusion, and DSC perfusion were performed at baseline and approximately every 2 months throughout treatment. ADC histogram metrics of T2-weighted FLAIR and enhancing tumor volume, dynamic contrast-enhanced permeability metrics for enhancing tumors, and tumor relative CBV from DSC perfusion MR imaging were calculated. Baseline values, post-radiation therapy changes, and longitudinal trends for all metrics were evaluated for associations with survival and pseudoprogression.

RESULTS

Fifty children were evaluable for survival analyses. Higher baseline relative CBV was associated with shorter progression-free survival (P = .02, Q = 0.089) and overall survival (P = .006, Q = 0.055). Associations of higher baseline mean transfer constant from the blood plasma into the extravascular extracellular space with shorter progression-free survival (P = .03, Q = 0.105) and overall survival (P = .03, Q = 0.102) trended toward significance. An increase in relative CBV with time was associated with shorter progression-free survival (P < .001, Q < 0.001) and overall survival (P = .004, Q = 0.043). Associations of longitudinal mean extravascular extracellular volume fraction with progression-free survival (P = .03, Q = 0.104) and overall survival (P = .03, Q = 0.105) and maximum transfer constant from the blood plasma into the extravascular extracellular space with progression-free survival (P = .03, Q = 0.102) trended toward significance. Greater increases with time were associated with worse outcomes. True radiologic progression showed greater post-radiation therapy decreases in mode_ADC_FLAIR compared with pseudoprogression (means, -268.15 versus -26.11, P = .01.) CONCLUSIONS: ADC histogram, perfusion, and permeability MR imaging metrics in diffuse intrinsic pontine glioma are useful in predicting survival and pseudoprogression.

Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings

We applied machine learning algorithms for differentiation of posterior fossa tumors using apparent diffusion coefficient (ADC) histogram analysis and structural MRI findings. A total of 256 patients with intra-axial posterior fossa tumors were identified, of whom 248 were included in machine learning analysis, with at least 6 representative subjects per each tumor pathology. The ADC histograms of solid components of tumors, structural MRI findings, and patients' age were applied to construct decision models using Classification and Regression Tree analysis. We also compared different machine learning classification algorithms (i.e., naïve Bayes, random forest, neural networks, support vector machine with linear and polynomial kernel) for dichotomized differentiation of the 5 most common tumors in our cohort: metastasis (n = 65), hemangioblastoma (n = 44), pilocytic astrocytoma (n = 43), ependymoma (n = 27), and medulloblastoma (n = 26). The decision tree model could differentiate seven tumor histopathologies with terminal nodes yielding up to 90% accurate classification rates. In receiver operating characteristics (ROC) analysis, the decision tree model achieved greater area under the curve (AUC) for differentiation of pilocytic astrocytoma (p = 0.020); and atypical teratoid/rhabdoid tumor ATRT (p = 0.001) from other types of neoplasms compared to the official clinical report. However, neuroradiologists' interpretations had greater accuracy in differentiating metastases (p = 0.001). Among different machine learning algorithms, random forest models yielded the highest accuracy in dichotomized classification of the 5 most common tumor types; and in multiclass differentiation of all tumor types random forest yielded an averaged AUC of 0.961 in training datasets, and 0.873 in validation samples. Our study demonstrates the potential application of machine learning algorithms and decision trees for accurate differentiation of brain tumors based on pretreatment MRI. Using easy to apply and understandable imaging metrics, the proposed decision tree model can help radiologists with differentiation of posterior fossa tumors, especially in tumors with similar qualitative imaging characteristics. In particular, our decision tree model provided more accurate differentiation of pilocytic astrocytomas from ATRT than by neuroradiologists in clinical reads.

MRI Patterns of Extrapontine Lesion Extension in Diffuse Intrinsic Pontine Gliomas

BACKGROUND AND PURPOSE

Diffuse intrinsic pontine glioma is a devastating childhood cancer that despite being primarily diagnosed by MR imaging alone, lacks robust prognostic imaging features. This study investigated patterns and quantification of extrapontine lesion extensions as potential prognostic imaging biomarkers for survival in children with newly diagnosed diffuse intrinsic pontine glioma.

MATERIALS AND METHODS

Volumetric analysis of baseline MR imaging studies was completed in 131 patients with radiographically defined typical diffuse intrinsic pontine gliomas. Extrapontine tumor extension was classified according to the direction of extension: midbrain, medulla oblongata, and right and left middle cerebellar peduncles; various extrapontine lesion extension patterns were evaluated. The Kaplan-Meier method was used to estimate survival differences; linear regression was used to evaluate clinical-radiographic variables prognostic of survival.

RESULTS

At least 1 extrapontine lesion extension was observed in 125 patients (95.4%). Of the 11 different extrapontine lesion extension patterns encountered in our cohort, 2 were statistically significant predictors of survival. Any extension into the middle cerebellar peduncles was prognostic of shorter overall survival (P = .01), but extension into both the midbrain and medulla oblongata but without extension into either middle cerebellar peduncle was prognostic of longer overall survival compared with those having no extension (P = .04) or those having any other pattern of extension (P < .001).

CONCLUSIONS

Within this large cohort of patients with typical diffuse intrinsic pontine gliomas, 2 specific extrapontine lesion extension patterns were associated with a significant overall survival advantage or disadvantage. Our findings may be valuable for risk stratification and radiation therapy planning in future clinical trials.

Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study

The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and perfusion imaging are commonly used to aid the non-invasive diagnosis of children's brain tumours, but are usually evaluated by expert qualitative review. Quantitative studies are mainly single centre and single modality. The aim of this work was to combine multi-centre diffusion and perfusion imaging, with machine learning, to develop machine learning based classifiers to discriminate between three common paediatric tumour types. The results show that diffusion and perfusion weighted imaging of both the tumour and whole brain provide significant features which differ between tumour types, and that combining these features gives the optimal machine learning classifier with >80% predictive precision. This work represents a step forward to aid in the non-invasive diagnosis of paediatric brain tumours, using advanced clinical imaging.

Diffusion Characteristics of Pediatric Diffuse Midline Gliomas with Histone H3-K27M Mutation Using Apparent Diffusion Coefficient Histogram Analysis

BACKGROUND AND PURPOSE

Diffuse midline gliomas with histone H3 K27M mutation are biologically aggressive tumors with poor prognosis defined as a new diagnostic entity in the 2016 World Health Organization Classification of Tumors of the Central Nervous System. There are no qualitative imaging differences (enhancement, border, or central necrosis) between histone H3 wildtype and H3 K27M-mutant diffuse midline gliomas. Herein, we evaluated the utility of diffusion-weighted imaging to distinguish H3 K27M-mutant from histone H3 wildtype diffuse midline gliomas.

MATERIALS AND METHODS

We identified 31 pediatric patients (younger than 21 years of age) with diffuse gliomas centered in midline structures that had undergone assessment for histone H3 K27M mutation. We measured ADC within these tumors using a voxel-based 3D whole-tumor measurement method.

RESULTS

Our cohort included 18 infratentorial and 13 supratentorial diffuse gliomas centered in midline structures. Twenty-three (74%) tumors carried H3-K27M mutations. There was no difference in ADC histogram parameters (mean, median, minimum, maximum, percentiles) between mutant and wild-type tumors. Subgroup analysis based on tumor location also did not identify a difference in histogram descriptive statistics. Patients who survived <1 year after diagnosis had lower median ADC (1.10 × 10^-3mm²/s; 95% CI, 0.90-1.30) compared with patients who survived >1 year (1.46 × 10^-3mm²/s; 95% CI, 1.19-1.67; P < .06). Average ADC values for diffuse midline gliomas were 1.28 × 10^-3mm²/s (95% CI, 1.21-1.34) and 0.86 × 10^-3mm²/s (95% CI, 0.69-1.01) for hemispheric glioblastomas with P < .05.

CONCLUSIONS

Although no statistically significant difference in diffusion characteristics was found between H3-K27M mutant and H3 wildtype diffuse midline gliomas, lower diffusivity corresponds to a lower survival rate at 1 year after diagnosis. These findings can have an impact on the anticipated clinical course for this patient population and offer providers and families guidance on clinical outcomes.

Differentiation of pilocytic and pilomyxoid astrocytomas using dynamic susceptibility contrast perfusion and diffusion weighted imaging

PURPOSE

Pilocytic (PA) and pilomyxoid astrocytomas (PMA) are related low-grade tumors which occur predominantly in children. PMAs have a predilection for a supratentorial location in younger children with worse outcomes. However, the two have similar imaging characteristics. Quantitative MR sequences such as dynamic susceptibility contrast (DSC) perfusion and diffusion (DWI) were assessed for significant differences between the two tumor types and locations.

METHODS

A retrospective search for MRI with DSC and DWI on pathology-proven cases of PMA and PA in children was performed. Tumors were manually segmented on anatomic images registered to rCBV, K2, and ADC maps. Tumors were categorized as PA or PMA, with subclassification of supratentorial and infratentorial locations. Mean values were obtained for tumor groups and locations compared with Student's t test for significant differences with post hoc correction for multiple comparisons. ROC analysis for significant t test values was performed. Histogram evaluation was also performed.

RESULTS

A total of 49 patients met inclusion criteria. This included 30 patients with infratentorial PA, 8 with supratentorial PA, 6 with supratentorial PMA, and 5 with infratentorial PMA. Mean analysis showed significantly increased rCBV for infratentorial PMA (2.39 ± 1.1) vs PA (1.39 ± 0.16, p = 0.0006). ROC analysis for infratentorial PA vs PMA yielded AUC = 0.87 (p < 0.001). Histogram analysis also demonstrated a higher ADC peak location for PMA (1.8 ± 0.2) vs PA (1.56 ± 0.28).

CONCLUSION

PMA has a significantly higher rCBV than PA in the infratentorial space. DSC perfusion and diffusion MR imaging may be helpful to distinguish between the two tumor types in this location.

Survival prediction of high-grade glioma patients with diffusion kurtosis imaging

PURPOSE

To evaluate the prognostic value of diffusion kurtosis imaging (DKI) for survival prediction of patients with high-grade glioma (HGG).

MATERIALS AND METHODS

DKI was performed for fifty-eight patients with pathologically proven HGG by using a 3-T scanner. The mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) values in the solid part of the tumor were measured and normalized. Univariate Cox regression analysis was used to evaluate the association between overall survival (OS) and sex, age, Karnofsky performance status (KPS), tumor grade, Ki-67 labeling index (LI), extent of resection, use of chemoradiotherapy, MK, MD, and FA. Multivariate Cox regression analysis including sex, age, KPS, extent of resection, use of chemoradiotherapy, MK, MD, and FA was subsequently performed. Spearman's correlation coefficient for OS and the area under receiver operating characteristic curve (AUC) for predicting 2-year survival were calculated for each DKI parameter and further compared.

RESULTS

In univariate Cox regression analyses, OS was significantly associated with the tumor grade, Ki-67 LI, extent of resection, use of chemoradiotherapy, MK, and MD (P < 0.05 for all). Multivariate Cox regression analyses indicated that MK, MD (hazard ratio = 1.582 and 0.828, respectively, for each 0.1 increase in the normalized value), extent of resection and use of chemoradiotherapy were independent predictors of OS. The absolute value of the correlation coefficient for OS and AUC for predicting 2-year survival by MK (rho = -0.565, AUC = 0.841) were higher than those by MD (rho = 0.492, AUC = 0.772), but the difference was not significant.

CONCLUSION

DKI is a promising tool to predict the survival of HGG patients. MK and MD are independent predictors. MK is potentially better associated with OS than MD, which may lead to a more accurate evaluation of HGG patient survival.

Real-Time, in Vivo Correlation of Molecular Structure with Drug Distribution in the Brain Striatum Following Convection Enhanced Delivery

The blood-brain barrier (BBB) represents a major obstacle in delivering therapeutics to brain lesions. Convection-enhanced delivery (CED), a method that bypasses the BBB through direct, cannula-mediated drug delivery, is one solution to maintaining increased, effective drug concentration at these lesions. CED was recently proven safe in a phase I clinical trial against diffuse intrinsic pontine glioma (DIPG), a childhood cancer. Unfortunately, the exact relationship between drug size, charge, and pharmacokinetic behavior in the brain parenchyma are difficult to observe in vivo. PET imaging of CED-delivered agents allows us to determine these relationships. In this study, we label different modifications of the PDGFRA inhibitor dasatinib with fluorine-18 or via a nanofiber-zirconium-89 system so that the effect of drug structure on post-CED behavior can accurately be tracked in vivo, via PET. Relatively unchanged bioactivity is confirmed in patient- and animal-model-derived cell lines of DIPG. In naïve mice, significant individual variability in CED drug clearance is observed, highlighting a need to accurately understand drug behavior during clinical translation. Generally, the half-life for a drug to clear from a CED site is short for low molecular weight dasatinib analogs that bare different charge; 1-3 (1, 32.2 min (95% CI: 27.7-37.8), 2, 44.8 min (27.3-80.8), and 3, 71.7 min (48.6-127.6) minutes) and is much longer for a dasatinib-nanofiber conjugate, 5, (42.8-57.0 days). Positron emission tomography allows us to accurately measure the effect of drug size and charge in monitoring real-time drug behavior in the brain parenchyma of live specimens.

Direct Involvement of Cranial Nerve V at Diagnosis in Patients With Diffuse Intrinsic Pontine Glioma: A Potential Magnetic Resonance Predictor of Short-Term Survival

Background: Diffuse intrinsic pontine glioma (DIPG) has a dismal prognosis. Magnetic resonance imaging (MRI) remains the gold standard for non-invasive DIPG diagnosis. MRI features have been tested as surrogate biomarkers. We investigated the direct involvement of cranial nerve V (CN V) in DIPG at diagnosis and its utility as predictor of poor overall survival.

Materials and Methods: We examined MRI scans of 35 consecutive patients with radiological diagnosis of DIPG. Direct involvement of CN V was assessed on the diagnostic scans. Differences in overall survival (OS) and time to progression (TTP) were analyzed for involvement of CN V, sex, age, tumor size, ring enhancement, and treatment regimen. Correlations between involvement of CN V and disease dissemination, magnet strength and slice thickness were analyzed. Statistical analyses included Kaplan-Meier curves, log-rank test and Spearman's Rho.

Results: After excluding six long-term survivors, 29 patients were examined (15 M, 14 F). Four patients presented direct involvement of CN V. Histological data were available in 12 patients. Median OS was 11 months (range 3–23 months). Significant differences in OS were found for direct involvement of CN V (median OS: 7 months, 95% CI 1.1–12.9 months for involvement of CN V vs. 13 months, 95% CI 10.2–15.7 for lack of involvement of CN V, respectively, p < 0.049). Significant differences in TTP were found for the two treatment regimens (median TTP: 4 months, 95% CI 2.6–5.3 vs. 7 months, 95% CI 5.9–8.1, respectively, p < 0.027). No significant correlation was found between involvement of CN V and magnet strength or slice thickness (r = −0.201; p = NS). A trend toward positive correlation was found between direct involvement of CN V at diagnosis and dissemination of disease at follow-up (r = 0.347; p < 0.065).

Conclusions: In our cohort, direct involvement of CN V correlated with poor prognosis. Based on our data, we suggest that in DIPG direct involvement of CN V should be routinely evaluated on diagnostic scans.

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.

Volumetric voxelwise apparent diffusion coefficient histogram analysis for differentiation of the fourth ventricular tumors

PURPOSE

We applied voxelwise apparent diffusion coefficient (ADC) histogram analysis in addition to structural magnetic resonance imaging (MRI) findings and patients' age for differentiation of intraaxial posterior fossa tumors involving the fourth ventricle.

PARTICIPANTS AND METHODS

Pretreatment MRIs of 74 patients with intraaxial brain neoplasm involving the fourth ventricle, from January 1, 2004 to December 31, 2015, were reviewed. The tumor solid components were segmented and voxelwise ADC histogram variables were determined. Histogram-driven variables, structural MRI findings, and patient age were combined to devise a differential diagnosis algorithm.

RESULTS

The most common neoplasms were ependymomas ( n = 21), medulloblastoma ( n = 17), and pilocytic astrocytomas ( n = 13). Medulloblastomas followed by atypical teratoid/rhabdoid tumors had the lowest ADC histogram percentile values; whereas pilocytic astrocytomas and choroid plexus papillomas had the highest ADC histogram percentile values. In a multivariable multinominal regression analysis, the ADC 10th percentile value from voxelwise histogram was the only independent predictor of tumor type ( p < 0.001). In separate binary logistic regression analyses, the 10th percentile ADC value, tumor morphology, enhancement pattern, extension into Luschka/Magendie foramina, and patient age were predictors of different tumor types. Combining these variables, we devised a stepwise diagnostic model yielding 71% to 82% sensitivity, 91% to 95% specificity, 75% to 78% positive predictive value, and 89% to 95% negative predictive value for differentiation of ependymoma, medulloblastoma, and pilocytic astrocytoma.

CONCLUSION

We have shown how the addition of quantitative voxelwise ADC histogram analysis of the tumor solid component to structural findings and patient age can help with accurate differentiation of intraaxial posterior fossa neoplasms involving the fourth ventricle based on pretreatment MRI.

A phase I trial of the MEK inhibitor selumetinib (AZD6244) in pediatric patients with recurrent or refractory low-grade glioma: a Pediatric Brain Tumor Consortium (PBTC) study

Background

Activation of the mitogen-activated protein kinase pathway is important for growth of pediatric low-grade gliomas (LGGs). The aim of this study was to determine the recommended phase II dose (RP2D) and the dose-limiting toxicities (DLTs) of the MEK inhibitor selumetinib in children with progressive LGG.

Methods

Selumetinib was administered orally starting at 33 mg/m2/dose b.i.d., using the modified continual reassessment method. Pharmacokinetic analysis was performed during the first course. BRAF aberrations in tumor tissue were determined by real-time polymerase chain reaction and fluorescence in situ hybridization.

Results

Thirty-eight eligible subjects were enrolled. Dose levels 1 and 2 (33 and 43 mg/m2/dose b.i.d.) were excessively toxic. DLTs included grade 3 elevated amylase/lipase (n = 1), headache (n = 1), mucositis (n = 2), and grades 2-3 rash (n = 6). At dose level 0 (25 mg/m2/dose b.i.d, the RP2D), only 3 of 24 subjects experienced DLTs (elevated amylase/lipase, rash, and mucositis). At the R2PD, the median (range) area under the curve (AUC0-∞) and apparent oral clearance of selumetinib were 3855 ng*h/mL (1780 to 7250 ng × h/mL) and 6.5 L × h-1 × m-2 (3.4 to 14.0 L × h-1 × m-2), respectively. Thirteen of 19 tumors had BRAF abnormalities. Among the 5 (20%) of 25 subjects with sustained partial responses, all at the RP2D, 4 had BRAF aberrations, 1 had insufficient tissue. Subjects received a median of 13 cycles (range: 1-26). Fourteen (37%) completed all protocol treatment (26 cycles [n = 13], 13 cycles [n = 1]) with at least stable disease; 2-year progression-free survival at the RP2D was 69 ± SE 9.8%.

Conclusion

Selumetinib has promising antitumor activity in children with LGG. Rash and mucositis were the most common DLTs.

T2-weighted images are superior to other MR image types for the determination of diffuse intrinsic pontine glioma intratumoral heterogeneity

PURPOSE

Diffuse intrinsic pontine glioma (DIPG) remains the main cause of death in children with brain tumors. Given the inefficacy of numerous peripherally delivered agents to treat DIPG, convection enhanced delivery (CED) of therapeutic agents is a promising treatment modality. The purpose of this study was to determine which MR imaging type provides the best discrimination of intratumoral heterogeneity to guide future stereotactic implantation of CED catheters into the most cellular tumor regions.

METHODS

Patients ages 18 years or younger with a diagnosis of DIPG from 2000 to 2015 were included. Radiographic heterogeneity index (HI) of the tumor was calculated by measuring the standard deviation of signal intensity of the tumor (SD_Tumor) normalized to the genu of the corpus callosum (SD_{Corpus Callosum}). Four MR image types (T2-weighted, contrast-enhanced T1-weighted, FLAIR, and ADC) were analyzed at several time points both before and after radiotherapy and chemotherapy. HI values across these MR image types were compared and correlated with patient survival.

RESULTS

MR images from 18 patients with DIPG were evaluated. The mean survival ± standard deviation was 13.8 ± 13.7 months. T2-weighted images had the highest HI (mean ± SD, 5.1 ± 2.5) followed by contrast-enhanced T1-weighted images (3.7 ± 1.5), FLAIR images (3.0 ± 1.1), and ADC maps (1.6 ± 0.4). ANOVA demonstrated that HI values were significantly higher for T2-weighted images than FLAIR (p < 0.01) and ADC (p < 0.0001). Following radiotherapy, T2-weighted and contrast-enhanced T1-weighted image HI values increased, while FLAIR and ADC HI values decreased. Univariate and multivariate analyses did not reveal a relationship between HI values and patient survival (p > 0.05).

CONCLUSIONS

For children with DIPG, T2-weighted MRI demonstrates the greatest signal intensity variance suggesting tumor heterogeneity. Within this heterogeneity, T2-weighted signal hypointensity is known to correlate with increased cellularity and thus may represent a putative target for CED catheter placement in future clinical trials.

Multiparametric Analysis of Permeability and ADC Histogram Metrics for Classification of Pediatric Brain Tumors by Tumor Grade

BACKGROUND AND PURPOSE

Accurate tumor grading is essential for treatment planning of pediatric brain tumors. We hypothesized that multiparametric analyses of a combination of permeability metrics and ADC histogram metrics would differentiate high- and low-grade tumors with high accuracy.

MATERIALS AND METHODS

DTI and dynamic contrast-enhanced MR imaging using T1-mapping with flip angles of 2°, 5°, 10°, and 15°, followed by a 0.1-mmol/kg body weight gadolinium-based bolus was performed on all patients in addition to standard MR imaging. Permeability data were processed and transfer constant from the blood plasma into the extracellular extravascular space, rate constant from the extracellular extravascular space back into blood plasma, extravascular extracellular volume fraction, and fractional blood plasma volume were calculated from 3D tumor volumes. Apparent diffusion coefficient histogram metrics were calculated for 3 separate tumor volumes derived from T2-FLAIR sequences, T1 contrast-enhanced sequences, and permeability maps, respectively.

RESULTS

Results from 41 patients (0.3-16.76 years of age; mean, 6.22 years) with newly diagnosed contrast-enhancing brain tumors (16 low-grade; 25 high-grade) were included in the institutional review board-approved retrospective analysis. Wilcoxon tests showed a higher transfer constant from blood plasma into extracellular extravascular space and rate constant from extracellular extravascular space back into blood plasma, and lower extracellular extravascular volume fraction (P < .001) in high-grade tumors. The mean ADCs of FLAIR and enhancing tumor volumes were significantly lower in high-grade tumors (P < .001). ROC analysis showed that a combination of extravascular volume fraction and mean ADC of FLAIR volume differentiated high- and low-grade tumors with high accuracy (area under receiver operating characteristic curve = 0.918).

CONCLUSIONS

ADC histogram metrics combined with permeability metrics differentiate low- and high-grade pediatric brain tumors with high accuracy.

Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs)

PURPOSE

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features.

METHODS

Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared.

RESULTS

Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10-25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50-78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18-0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004).

CONCLUSION

Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

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.

Posterior Fossa Tumors

Pediatric brain tumors are the leading cause of death from solid tumors in childhood. The most common posterior fossa tumors in children are medulloblastoma, atypical teratoid/rhabdoid tumor, cerebellar pilocytic astrocytoma, ependymoma, and brainstem glioma. Location, and imaging findings on computed tomography (CT) and conventional MR (cMR) imaging may provide important clues to the most likely diagnosis. Moreover, information obtained from advanced MR imaging techniques increase diagnostic confidence and help distinguish between different histologic tumor types. Here we discuss the most common posterior fossa tumors in children, including typical imaging findings on CT, cMR imaging, and advanced MR imaging studies.