Apparent diffusion coefficient of pediatric cerebellar tumors: a biomarker of tumor grade?

Deciphering Machine Learning Decisions to Distinguish between Posterior Fossa Tumor Types Using MRI Features: What Do the Data Tell Us?

Machine learning (ML) models have become capable of making critical decisions on our behalf. Nevertheless, due to complexity of these models, interpreting their decisions can be challenging, and humans cannot always control them. This paper provides explanations of decisions made by ML models in diagnosing four types of posterior fossa tumors: medulloblastoma, ependymoma, pilocytic astrocytoma, and brainstem glioma. The proposed methodology involves data analysis using kernel density estimations with Gaussian distributions to examine individual MRI features, conducting an analysis on the relationships between these features, and performing a comprehensive analysis of ML model behavior. This approach offers a simple yet informative and reliable means of identifying and validating distinguishable MRI features for the diagnosis of pediatric brain tumors. By presenting a comprehensive analysis of the responses of the four pediatric tumor types to each other and to ML models in a single source, this study aims to bridge the knowledge gap in the existing literature concerning the relationship between ML and medical outcomes. The results highlight that employing a simplistic approach in the absence of very large datasets leads to significantly more pronounced and explainable outcomes, as expected. Additionally, the study also demonstrates that the pre-analysis results consistently align with the outputs of the ML models and the clinical findings reported in the existing literature.

Imaging of pediatric brain tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee/ASPNR White Paper

Tumors of the central nervous system are the most common solid malignancies in children and the most common cause of pediatric cancer-related mortality. Imaging plays a central role in diagnosis, staging, treatment planning, and response assessment of pediatric brain tumors. However, the substantial variability in brain tumor imaging protocols across institutions leads to variability in patient risk stratification and treatment decisions, and complicates comparisons of clinical trial results. This White Paper provides consensus-based imaging recommendations for evaluating pediatric patients with primary brain tumors. The proposed brain magnetic resonance imaging protocol recommendations balance advancements in imaging techniques with the practicality of deployment across most imaging centers.

Shunt dependency in supratentorial intraventricular tumors depends on the extent of tumor resection

BACKGROUND

Supratentorial intraventricular tumors (SIVTs) are rare lesions of various entities characteristically presenting with hydrocephalus and often posing a surgical challenge due to their deep-seated localization. We aimed to elaborate on shunt dependency after tumor resection, clinical characteristics, and perioperative morbidity.

METHODS

We retrospectively searched the institutional database for patients with supratentorial intraventricular tumors treated at the Department of Neurosurgery of the Ludwig-Maximilians-University in Munich, Germany, between 2014 and 2022.

RESULTS

We identified 59 patients with over 20 different SIVT entities, most often subependymoma (8/59 patients, 14%). Mean age at diagnosis was 41 ± 3 years. Hydrocephalus and visual symptoms were observed in 37/59 (63%) and 10/59 (17%) patients, respectively. Microsurgical tumor resection was provided in 46/59 patients (78%) with complete resection in 33/46 patients (72%). Persistent postoperative neurological deficits were encountered in 3/46 patients (7%) and generally mild in nature. Complete tumor resection was associated with less permanent shunting in comparison to incomplete tumor resection, irrespective of tumor histology (6% versus 31%, p = 0.025). Stereotactic biopsy was utilized in 13/59 patients (22%), including 5 patients who received synchronous internal shunt implantation for symptomatic hydrocephalus. Median overall survival was not reached and did not differ between patients with or without open resection.

CONCLUSIONS

SIVT patients display a high risk of developing hydrocephalus and visual symptoms. Complete resection of SIVTs can often be achieved, preventing the need for long-term shunting. Stereotactic biopsy along with internal shunting represents an effective approach to establish diagnosis and ameliorate symptoms if resection cannot be safely performed. Due to the rather benign histology, the outcome appears excellent when adjuvant therapy is provided.

Application of Apparent Diffusion Coefficient Histogram Metrics for Differentiation of Pediatric Posterior Fossa Tumors : A Large Retrospective Study and Brief Review of Literature

PURPOSE

This study aimed to evaluate the application of apparent diffusion coefficient (ADC) histogram analysis to differentiate posterior fossa tumors (PFTs) in children.

METHODS

A total of 175 pediatric patients with PFT, including 75 pilocytic astrocytomas (PA), 59 medulloblastomas, 16 ependymomas, and 13 atypical teratoid rhabdoid tumors (ATRT), were analyzed. Tumors were visually assessed using DWI trace and conventional MRI images and manually segmented and post-processed using parametric software (pMRI). Furthermore, tumor ADC values were normalized to the thalamus and cerebellar cortex. The following histogram metrics were obtained: entropy, minimum, 10th, and 90th percentiles, maximum, mean, median, skewness, and kurtosis to distinguish the different types of tumors. Kruskal Wallis and Mann-Whitney U tests were used to evaluate the differences. Finally, receiver operating characteristic (ROC) curves were utilized to determine the optimal cut-off values for differentiating the various PFTs.

RESULTS

Most ADC histogram metrics showed significant differences between PFTs (p < 0.001) except for entropy, skewness, and kurtosis. There were significant pairwise differences in ADC metrics for PA versus medulloblastoma, PA versus ependymoma, PA versus ATRT, medulloblastoma versus ependymoma, and ependymoma versus ATRT (all p < 0.05). Our results showed no significant differences between medulloblastoma and ATRT. Normalized ADC data showed similar results to the absolute ADC value analysis. ROC curve analysis for normalized ADC_median values to thalamus showed 94.9% sensitivity (95% CI: 85-100%) and 93.3% specificity (95% CI: 87-100%) for differentiating medulloblastoma from ependymoma.

CONCLUSION

ADC histogram metrics can be applied to differentiate most types of posterior fossa tumors in children.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

Supratentorial Extraventricular Ependymomas: Imaging Features and the Added Value of Apparent Diffusion Coefficient

OBJECTIVE

To improve the understanding and the diagnosis of intracranial ependymal tumors.

METHODS

The clinical, radiological and prognostic features of 48 supratentorial extraventricular ependymomas and 74 intraventricular ependymomas were summarized and compared.

RESULTS

Supratentorial extraventricular ependymomas, most often located in the frontal lobe (33.3%) and classified as grade III (75.0%), had relatively large eccentric cysts (3.07 ± 2.03 cm), significant enhancement (84.8%), low apparent diffusion coefficient (ADC) values, and associated with higher mortality (41.3%). The majority of intraventricular lesions occurred in the fourth ventricle (86.5%) and classified as grade II (78.4%), had relatively small and multiple cystic changes (1.04 ± 0.87 cm), slight or moderate enhancement (76.9%), high ADC values and associated with lower mortality (20.7%). There were few significant differences between grade II and grade III tumors in these 2 groups, respectively. Young age, high grade and low ADC values are worse prognostic indicators for patients with supratentorial extraventricular ependymomas, but not for those with intraventricular ependymomas.

CONCLUSIONS

Conventional radiological features, combined with clinical manifestations and quantitative information provided by diffusion-weighted imaging, may not only enhance the diagnosis and assist in determining prognosis but also provide a better pathophysiological understanding of intracranial ependymal tumors.

The Diagnostic Value of Apparent Diffusion Coefficient and Proton Magnetic Resonance Spectroscopy in the Grading of Pediatric Gliomas

The aims of this retrospective study were to assess the value of the quantitative analysis of apparent diffusion coefficient (ADC) and proton magnetic resonance spectroscopy (¹H-MRS) metabolites in differentiating grades of pediatric gliomas.

Neuroimaging of pediatric infratentorial tumors and the value of diffusion-weighted imaging (DWI) in determining tumor grade

BACKGROUND

Diffusion-weighted imaging (DWI) provides information about the cellular density of tumors. This feature is useful in grading and identifying different tumor types.

PURPOSE

To assess the value of diffusion restriction and apparent diffusion coefficient (ADC) values in differentiating pediatric infratentorial tumors.

MATERIAL AND METHODS

This was a retrospective review of the magnetic resonance imaging (MRI) of 82 children (age range 1-16 years) with infratentorial tumors. Histopathological grading after surgical excision/biopsy was categorized as low grade (WHO grades I and II) (n = 31; 29 pilocytic astrocytomas, 2 ependymomas) and high grade (WHO grade III and IV) (n = 51; 40 medulloblastomas, 8 anaplastic ependymomas, 1 anaplastic astrocytoma, 2 atypical rhabdoid teratoid tumors [ATRT]). MRI features and ADC values were compared among tumor types and grades using a two-tailed t test, Mann-Whitney U test for continuous data and Chi-square test for categorical variables.

RESULTS

Diffusion restriction and low ADC value was a feature of high-grade tumors (P<0.001). The mean ADC values of the low-grade and high-grade tumors were 1.567 × 10^-3mm²/s and 0.661 × 10^-3mm²/s, respectively. Using 0.9 × 10^-3mm²/s as the cut-off value, the sensitivity, specificity, positive and negative predictive values for differentiating the grades was 87%, 100%, 100%, and 81.8%, respectively. Significant differences were found between the mean ADC values of the individual tumor types (P<0.05), except between medulloblastoma and ATRT.

CONCLUSION

ADC values and visual assessment of diffusion restriction are useful in tumor grading. The individual tumor types can be identified by an algorithmic approach, using DWI in conjunction with other described MRI features.

Advanced MRI Findings in Medulloblastomas: Relationship to Genetic Subtypes, Histopathology, and Immunohistochemistry

BACKGROUND AND PURPOSE

For diagnosis of medulloblastoma, the updated World Health Organization classification now demands for genetic typing, defining more precisely the tumor biology, therapy, and prognosis. We investigated potential associations between magnetic resonance imaging (MRI) parameters including apparent diffusion coefficient (ADC) and neuropathologic features of medulloblastoma, focusing on genetic subtypes.

METHODS

This study was a retrospective single-center analysis of 32 patients (eight females, median age = 9 years [range, 1-57], mean 12.6 ± 11.3) from 2012 to 2019. Genetic subtypes (wingless [WNT]; sonic hedgehog [SHH]; non-WNT/non-SHH), histopathology, immunohistochemistry (p53, Ki67), and the following MRI parameters were correlated: tumor volume, location (midline, pontocerebellar, and cerebellar hemisphere), edema, hydrocephalus, metastatic disease (presence/absence and each), contrast-enhancement (minor, moderate, and distinct), cysts (none, small, and large), hemorrhage (none, minor, and major), and ADC_mean . The ADC_mean was calculated using manually set regions of interest within the solid tumor. Statistics comprised univariate and multivariate testing.

RESULTS

Out of 32 tumors, three tumors were WNT activated (9.4%), 13 (40.6%) SHH activated, and 16 (50.0%) non-WNT/non-SHH. Hemispherical location (n = 7/8, P = .003) and presence of edema (8/8; P < .001, specificity 100%, positive predictive value 100%) were significantly associated with SHH activation. The combined parameter "no edema + no metastatic disease + cysts" significantly discriminated WNT-activated from SHH-activated medulloblastoma (P = .036). ADC_mean (10^-6 mm² /s) was 484 for WNT-activated, 566 for SHH-activated, and 624 for non-WNT/non-SHH subtypes (P = .080). A significant negative correlation was found between ADC_mean and Ki67 (r = -.364, P = .040).

CONCLUSION

MRI analysis enabled noninvasive differentiation of SHH-activated medulloblastoma. ADC alone was not reliable for genetic characterization, but associated with tumor proliferation rate.

MRI Features of Intracranial Anaplastic Ependymomas: A Comparison of Supratentorial and Infratentorial Lesions

Background: Several previous reports of anaplastic ependymomas have described their imaging features, and most of these studies were case reports. However, no studies have compared the magnetic resonance imaging (MRI) features between the infratentorial and supratentorial anaplastic ependymomas.

Objective: The goal of this study was to explore MRI characteristics for intracranial anaplastic ependymomas.

Material and Methods: We retrospectively reviewed the demographics of 165 patients and MRI findings of 60 patients with supratentorial (SAEs) and infratentorial anaplastic ependymomas (IAEs) before surgery. The demographics and MRI features for SAEs and IAEs were compared and evaluated.

Results: Among the 60 patients, most SAEs (91.7%) were extraventricular, whereas most IAEs (91.7%) were intraventricular. Of sixty intracranial anaplastic ependymomas, most lesions were well-defined (n = 45) and round-like (n = 36). On T1-weighted imaging, compared with the gray matter, the SAEs exhibited heterogeneous signal intensity, whereas IAEs exhibited iso-hypointense signals. T2 signals exhibited greater associations with hyperintense signals in IAEs; however, SAEs showed hyperintense or hypointense–hyperintense. On diffusion-weighted imaging (DWI), almost all solid tissues of SAEs appeared as hyperintense, whereas IAEs exhibited iso-hypointense signals. Peritumoral edema and intratumoral hemorrhage occurred more frequently in SAEs. Almost all anaplastic ependymomas exhibited heterogeneous enhancement. Cysts or necrosis was associated with 56 anaplastic ependymomas; however, large cysts were more prevalent in SAEs. On magnetic resonance spectroscopy (MRS), the mean choline/creatine (Cho/Cr) and choline/N-acetyl-aspartate (Cho/NAA) ratio of anaplastic ependymomas were (6.58 ± 4.26) and (8.84 ± 6.34), respectively, representing typical high-grade tumors.

Conclusion: We demonstrate the conventional and functional MRI features of intracranial anaplastic ependymomas, including DWI and MRS. MRI characteristics, such as location, cyst, diffusion restriction, and peritumoral edema, differed between supratentorial and infratentorial locations. Cho/Cr and Cho/ NAA ratios of anaplastic ependymomas are increased.

Pediatric Posterior Fossa Medulloblastoma: The Role of Diffusion Imaging in Identifying Molecular Groups

BACKGROUND AND PURPOSE

The molecular groups WNT activated (WNT), Sonic hedgehog activated (SHH), group 3, and group 4 are biologically and clinically distinct forms of medulloblastoma. We evaluated apparent diffusion coefficient (ADC) values' utility in differentiating/predicting medulloblastoma groups at the initial diagnostic imaging evaluation and prior to surgery.

METHODS

We retrospectively measured the ADC values of the enhancing, solid portion of the tumor (EST) and of the whole tumor (WT) and performed Kruskal-Wallis testing to compare the absolute tumor ADC values and cerebellar and thalamic ratios of three medulloblastoma groups (WNT, SHH, and group 3/group 4 combined).

RESULTS

Ninety-three children (65 males) were included. Fifty-seven children had group 3/group 4, 27 had SHH, and 9 had WNT medulloblastomas. The median absolute ADC values in the EST and WT were .719 × 10^-3 and .864 × 10^-3 mm² /s for group 3/group 4; .660 × 10^-3 and .965 × 10^-3 mm² /s for SHH; and .594 × 10^-3 and .728 × 10^-3 mm² /s for WNT medulloblastomas (P = .02 and .13). The median ratio of ADC values in the EST or the WT to normal cerebellar tissue was highest for group 3/group 4 and lowest for WNT medulloblastomas (P = .03 and .09), with similar results in pairwise comparisons of the corresponding thalamic ADC values (P = .02 and .06).

CONCLUSION

ADC analysis of a tumor's contrast-enhancing solid portion may aid preoperative molecular classification/prediction of pediatric medulloblastomas and may facilitate optimal surgical treatment planning, reducing surgery-induced morbidity.

Diffusion Weighted and Diffusion Tensor MRI in Pediatric Neuroimaging Including Connectomics: Principles and Applications

Diffusion weighted MRI (DWI) including diffusion tensor imaging (DTI) are unique imaging techniques that render qualitative and quantitative information of the central nervous system white matter (WM) ultrastructure. It uses the Brownian movement of water molecules to probe tissue microstructure. It is a noninvasive method, with superb sensitivity to the differential mobility of water molecules within various components of the brain without the necessity to inject contrast agents. By sampling the 3 dimensional shape, direction and magnitude of the water diffusion, DWI/DTI generates unique tissue contrasts that can be used to study the axonal WM organization of the central nervous system. Its application allows to study the normal and anomalous brain development including connectivity, as well as a multitude of WM diseases. This article discusses/summarizes the principles of DWI/DTI and its applications in pediatric neuroscience research.

Arterial spin labelling and diffusion-weighted imaging in paediatric brain tumours

BACKGROUND

Diffusion- and perfusion-weighted MRI are valuable tools for measuring the cellular and vascular properties of brain tumours. This has been well studied in adult patients, however, the biological features of childhood brain tumours are unique, and paediatric-focused studies are less common. We aimed to assess the diagnostic utility of apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) and cerebral blood flow (CBF) values derived from arterial spin labelling (ASL) in paediatric brain tumours.

METHODS

We performed a meta-analysis of published studies reporting ADC and ASL-derived CBF values in paediatric brain tumours. Data were combined using a random effects model in order to define typical parameter ranges for different histological tumour subtypes and WHO grades. New data were also acquired in a 'validation cohort' at our institution, in which ADC and CBF values in treatment naïve paediatric brain tumour patients were measured, in order to test the validity of the findings from the literature in an un-seen cohort. ADC and CBF quantification was performed by two radiologists via manual placement of tumour regions of interest (ROIs), in addition to an automated approach to tumour ROI placement.

RESULTS

A total of 14 studies met the inclusion criteria for the meta-analysis, constituting data acquired in 542 paediatric patients. Parameters of interest were based on measurements from ROIs placed within the tumour, including mean and minimum ADC values (ADC_ROI-mean, ADC_ROI-min) and the maximum CBF value normalised to grey matter (nCBF_ROI-max). After combination of the literature data, a number of histological tumour subtype groups showed significant differences in ADC values, which were confirmed, where possible, in our validation cohort of 32 patients. In both the meta-analysis and our cohort, diffuse midline glioma was found to be an outlier among high-grade tumour subtypes, with ADC and CBF values more similar to the low-grade tumours. After grouping patients by WHO grade, significant differences in grade groups were found in ADC_ROI-mean, ADC_ROI-min, and nCBF_ROI-max, in both the meta-analysis and our validation cohort. After excluding diffuse midline glioma, optimum thresholds (derived from ROC analysis) for separating low/high-grade tumours were 0.95 × 10^-3 mm²/s (ADC_ROI-mean), 0.82 × 10^-3 mm²/s (ADC_ROI-min) and 1.45 (nCBF_ROI-max). These thresholds were able to identify low/high-grade tumours with 96%, 83%, and 83% accuracy respectively in our validation cohort, and agreed well with the results from the meta-analysis. Diagnostic power was improved by combining ADC and CBF measurements from the same tumour, after which 100% of tumours in our cohort were correctly classified as either low- or high-grade (excluding diffuse midline glioma).

CONCLUSION

ADC and CBF values are useful for differentiating certain histological subtypes, and separating low- and high-grade paediatric brain tumours. The threshold values presented here are in agreement with previously published studies, as well as a new patient cohort. If ADC and CBF values acquired in the same tumour are combined, the diagnostic accuracy is optimised.

Use of Apparent Diffusion Coefficient Histogram in Differentiating Between Medulloblastoma and Pilocytic Astrocytoma in Children

Background

This research aimed to investigate the value of apparent diffusion coefficient (ADC) histogram in differentiating between medulloblastoma and pilocytic astrocytoma in children.

Material/Methods

Thirty-three children with posterior cranial fossa tumor confirmed by operation and pathology participated in this retrospective study, including 18 children with medulloblastoma and 15 children with pilocytic astrocytoma. ADC images of the maximum lay of tumors were selected, and the region of interest was delineated by Mazda software and analyzed by histogram. Histogram characteristic parameters of the 2 tumors were statistically analyzed to determine the significantly different characteristic parameters between the 2 tumor types.

Results

There were significant differences in the mean value, variance, skewness, kurtosis, and 1^th, 10^th, 50^th, and 90^th percentiles of 9 characteristic parameters extracted by histogram (P<0.05). The corresponding receiver operating characteristic (ROC) curves were drawn, in which the mean value and 50^th percentile were best identified. When the maximum area under the ROC curve was 1 and the optimal threshold was 137.7 and 125.5, the specificity and sensitivity were both 100%.

Conclusions

ADC histograms can be used to differentiate between medulloblastoma and pilocytic astrocytoma in children and provide reliable and objective evidence for the differentiation.

Clinical applications of diffusion weighted imaging in neuroradiology

Abstract

Diffusion-weighted imaging (DWI) has revolutionised stroke imaging since its introduction in the mid-1980s, and it has also become a pillar of current neuroimaging. Diffusion abnormalities represent alterations in the random movement of water molecules in tissues, revealing their microarchitecture, and occur in many neurological conditions. DWI provides useful information, increasing the sensitivity of MRI as a diagnostic tool, narrowing the differential diagnosis, providing prognostic information, aiding in treatment planning and evaluating response to treatment. Recently, there have been several technical improvements in DWI, leading to reduced acquisition time and artefacts and enabling the development of diffusion tensor imaging (DTI) as a tool for assessing white matter. We aim to review the main clinical uses of DWI, focusing on the physiological mechanisms that lead to diffusion abnormalities. Common pitfalls will also be addressed.

Teaching Points

• DWI includes EPI, TSE, RESOLVE or EPI combined with reduced volume excitation.

• DWI is the most sensitive sequence in stroke diagnosis and provides information about prognosis.

• DWI helps in the detection of intramural haematomas (arterial dissection).

• In diffusion imaging, ADC is inversely proportional to tumour cellularity.

• DWI and DTI derived parameters can be used as biomarkers in different pathologies.

Pediatric Cerebellar Tumors: Emerging Imaging Techniques and Advances in Understanding of Genetic Features

Cerebellar tumors are the most common group of solid tumors in children. MR imaging provides an important role in characterization of these lesions, surgical planning, and postsurgical surveillance. Preoperative imaging can help predict the histologic subtype of tumors, which can provide guidance for surgical planning. Beyond histology, pediatric brain tumors are undergoing new classification schemes based on genetic features. Intraoperative MR imaging has emerged as an important tool in the surgical management of pediatric brain tumors. Effective understanding of the imaging features of pediatric cerebellar tumors can benefit communication with neurosurgeons and neuro-oncologists and can improve patient management.

Magnetic resonance imaging based functional imaging in paediatric oncology

Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice.

Pediatric Cerebellar Tumors: Emerging Imaging Techniques and Advances in Understanding of Genetic Features

Cerebellar tumors are the most common group of solid tumors in children. MR imaging provides an important role in characterization of these lesions, surgical planning, and postsurgical surveillance. Preoperative imaging can help predict the histologic subtype of tumors, which can provide guidance for surgical planning. Beyond histology, pediatric brain tumors are undergoing new classification schemes based on genetic features. Intraoperative MR imaging has emerged as an important tool in the surgical management of pediatric brain tumors. Effective understanding of the imaging features of pediatric cerebellar tumors can benefit communication with neurosurgeons and neuro-oncologists and can improve patient management.

Ratio of Tumor to Normal Prostate Tissue Apparent Diffusion Coefficient as a Method for Quantifying DWI of the Prostate

OBJECTIVE

The purpose of this study was to investigate the ability of the apparent diffusion coefficient (ADC) ratio of tumor to normal prostate tissue to overcome inherent variability based on choice of b values, with whole-mount histopathologic analysis as the reference standard for tumor identification.

MATERIALS AND METHODS

Thirty-nine patients with prostate cancer underwent 3-T MRI, including DWI with b values of 0, 150, 750, and 1000 s/mm(2). ADC maps were derived from four b value combinations. Histologically derived ROIs were defined for prostate tumor and benign prostate tissue to generate a ratio. The concordance correlation coefficient was used to evaluate agreement and reproducibility at different b values. Bland-Altman plots were used to evaluate the pattern of relative measurement difference between b value combinations. The relationship between ADC values and Gleason score was tested by Spearman rank correlation.

RESULTS

ADC values varied depending on the b value combination selected. The concordance correlation coefficient was higher for ADC ratios (0.883; 95% CI, 0.816-0.927) compared with absolute ADC values for normal tissue (0.873; 95% CI, 0.799-0.921) and tumor (0.792; 95% CI, 0.688-0.864). The ADC ratio concordance correlation coefficient for transition zone tumors was considerably higher than that for the peripheral zone in all cases. Bland-Altman analysis showed higher variation for ADC maps incorporating a b value of zero for both ratio and absolute values. There was a stronger inverse relationship to Gleason score for ADC ratios (rho, -0.354 to -0.456) compared with absolute ADC values (rho, -0.117 to -0.379).

CONCLUSION

The use of a simple ratio of prostate tumor ADC to normal tissue ADC improved the concordance between different b value combinations and could provide a more robust means of assessing restricted diffusion in the prostate.

Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors

BACKGROUND AND PURPOSE

Apparent diffusion coefficient (ADC) values have been shown to assist in differentiating cerebellar pilocytic astrocytomas and medulloblastomas. Previous studies have applied only ADC measurements and calculated the mean/median values. Here we investigated the value of diffusion tensor imaging (DTI) histogram characteristics of the entire tumor for differentiation of cerebellar pilocytic astrocytomas and medulloblastomas.

METHODS

Presurgical DTI data were analyzed with a region of interest (ROI) approach to include the entire tumor. For each tumor, histogram-derived metrics including the 25th percentile, 75th percentile, and skewness were calculated for fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. The histogram metrics were used as primary predictors of interest in a logistic regression model. Statistical significance levels were set at p < .01.

RESULTS

The study population included 17 children with pilocytic astrocytoma and 16 with medulloblastoma (mean age, 9.21 ± 5.18 years and 7.66 ± 4.97 years, respectively). Compared to children with medulloblastoma, children with pilocytic astrocytoma showed higher MD (P = .003 and P = .008), AD (P = .004 and P = .007), and RD (P = .003 and P = .009) values for the 25th and 75th percentile. In addition, histogram skewness showed statistically significant differences for MD between low- and high-grade tumors (P = .008).

CONCLUSIONS

The 25th percentile for MD yields the best results for the presurgical differentiation between pediatric cerebellar pilocytic astrocytomas and medulloblastomas. The analysis of other DTI metrics does not provide additional diagnostic value. Our study confirms the diagnostic value of the quantitative histogram analysis of DTI data in pediatric neuro-oncology.

Diffusion characteristics of pediatric pineal tumors

BACKGROUND

Diffusion weighted imaging (DWI) has been shown to be helpful in characterizing tumor cellularity, and predicting histology. Several works have evaluated this technique for pineal tumors; however studies to date have not focused on pediatric pineal tumors.

OBJECTIVE

We evaluated the diffusion characteristics of pediatric pineal tumors to confirm if patterns seen in studies using mixed pediatric and adult populations remain valid.

MATERIALS AND METHODS

This retrospective study was performed after Institutional Review Board approval. We retrospectively evaluated all patients 18 years of age and younger with pineal tumors from a single institution where preoperative diffusion weighted imaging as well as histologic characterization was available.

RESULTS

Twenty patients (13 male, 7 female) with pineal tumors were identified: seven with pineoblastoma, four with Primitive Neuroectodermal Tumor (PNET), two with other pineal tumors, and seven with germ cell tumors including two germinomas, three teratomas, and one mixed germinoma-teratoma. The mean apparent diffusion coefficient (ADC) values in pineoblastoma (544 ± 65 × 10⁻⁶ mm²/s) and pineoblastoma/PNET (595 ± 144 × 10⁻⁶ mm²/s) was lower than that of the germ cell tumors (1284 ± 334 × 10⁻⁶ mm²/s; p < 0.0001 vs pineoblastoma). One highly cellular germinoma had an ADC value of 694 × 10⁻⁶ mm²/s.

CONCLUSION

ADC values can aid in differentiation of pineoblastoma/PNET from germ cell tumors in a population of children with pineal masses.

Evaluating the apparent diffusion coefficient in MRI studies as a means of determining paediatric brain tumour stages

BACKGROUND

The apparent diffusion coefficient (ADC) in MRI seems to be related to cellularity in brain tumours. Its utility as a tool for distinguishing between histological types and tumour stages remains controversial.

PROCEDURES

We retrospectively evaluated children diagnosed with CNS tumours between January 2008 and December 2013. Data collected were age, sex, histological diagnosis, and location of the tumour. We evaluated the ADC and ADC ratio and correlated those values with histological diagnoses.

RESULTS

The study included 55 patients with a median age of 6 years. Histological diagnoses were pilocytic astrocytoma (40%), anaplastic ependymoma (16.4%), ganglioglioma (10.9%), glioblastoma (7.3%), medulloblastoma (5.5%), and other (20%). Tumours could also be classified as low-grade (64%) or high-grade (36%). Mean ADC was 1.3 for low-grade tumours and 0.9 for high-grade tumours (p=.004). Mean ADC ratios were 1.5 and 1.2 for low and high-grade tumours respectively (p=.025). There were no significant differences in ADC/ADC ratio between different histological types.

CONCLUSION

ADC and ADC ratio may be useful in imaging-study based differential diagnosis of low and high-grade tumours, but they are not a substitute for an anatomical pathology study.