Search

Simple Summary: Differentiating pediatric posterior fossa (PF) tumors such as medulloblastoma (MB), ependymoma (EP), and pilocytic astrocytoma (PA) remains relevant, due to important treatment and prognostic implications. Diffusion kurtosis imaging (DKI) has not been tested to date to distinguish between pediatric PF tumors. Estimating diffusion values from whole-tumor-based (VOI) segmentations may improve the repeatability of diffusion measurements compared to conventional region-of-interest (ROI) approaches. Our purpose was twofold: to assess the repeatability of VOI DKI-derived diffusion measurements and DKI accuracy in discriminating among pediatric PF tumors, by employing conventional statistical analyses and machine learning (ML) techniques. Background and purpose: Differentiating pediatric posterior fossa (PF) tumors such as medulloblastoma (MB), ependymoma (EP), and pilocytic astrocytoma (PA) remains relevant, because of important treatment and prognostic implications. Diffusion kurtosis imaging (DKI) has not yet been investigated for discrimination of pediatric PF tumors. Estimating diffusion values from whole-tumor-based (VOI) segmentations may improve diffusion measurement repeatability compared to conventional region-of-interest (ROI) approaches. Our purpose was to compare repeatability between ROI and VOI DKI-derived diffusion measurements and assess DKI accuracy in discriminating among pediatric PF tumors. Materials and methods: We retrospectively analyzed 34 children (M, F, mean age 7.48 years) with PF tumors who underwent preoperative examination on a 3 Tesla magnet, including DKI. For each patient, two neuroradiologists independently segmented the whole solid tumor, the ROI of the area of maximum tumor diameter, and a small 5 mm ROI. The automated analysis pipeline included inter-observer variability, statistical, and machine learning (ML) analyses. We evaluated inter-observer variability with coefficient of variation (COV) and Bland–Altman plots. We estimated DKI metrics accuracy in discriminating among tumor histology with MANOVA analysis. In order to account for class imbalances, we applied SMOTE to balance the dataset. Finally, we performed a Random Forest (RF) machine learning classification analysis based on all DKI metrics from the SMOTE dataset by partitioning 70/30 the training and testing cohort. Results: Tumor histology included medulloblastoma (15), pilocytic astrocytoma (14), and ependymoma (5). VOI-based measurements presented lower variability than ROI-based measurements across all DKI metrics and were used for the analysis. DKI-derived metrics could accurately discriminate between tumor subtypes (Pillai's trace: p < 0.001). SMOTE generated 11 synthetic observations (10 EP and 1 PA), resulting in a balanced dataset with 45 instances (34 original and 11 synthetic). ML analysis yielded an accuracy of 0.928, which correctly predicted all but one lesion in the testing set. Conclusions: VOI-based measurements presented improved repeatability compared to ROI-based measurements across all diffusion metrics. An ML classification algorithm resulted accurate in discriminating PF tumors on a SMOTE-generated dataset. ML techniques based on DKI-derived metrics are useful for the discrimination of pediatric PF tumors. [ABSTRACT FROM AUTHOR]

Narcolepsy, a neurologic disorder that leads to excessive daytime sleepiness, may represent a rare consequence of neoplastic lesions involving the sellar/parasellar and hypothalamic regions, the anatomical areas responsible for wakefulness. Optic pathway gliomas represent the most common neoplasm of these regions and present an excellent overall survival, while long-term neurologic impairments, such as visual loss, endocrinopathies, or sleep disorders, are the principal causes of morbidity. In this case report, we describe a non-NF1 patient suffering from a very extensive optical pathway glioma, who several years after the diagnosis in a radiological condition of stable disease, presented with severe narcolepsy, a rare complication, that led to the death of the patient. [ABSTRACT FROM AUTHOR]

Simple Summary: The most frequent brain tumors in children are solid tumors. A significant fraction of pediatric brain tumors is represented by gliomas, which are heterogeneous. Diffusion kurtosis imaging metrics (MK, AK, RK, FA, and ADC) have shown promising results for glioma grading in adult patients; however, it is unclear whether this technique is accurate for diagnosing high grade pediatric gliomas and if it is correlated with patient survival. In our study, we performed a retrospective whole-tumor analysis on 59 children affected by gliomas and tested (1) if DKI metrics are accurate for grading pediatric gliomas and (2) if DKI metrics are correlated with patient overall survival and progression-free survival. Purpose: To develop a predictive grading model based on diffusion kurtosis imaging (DKI) metrics in children affected by gliomas, and to investigate the clinical impact of the predictive model by correlating with overall survival and progression-free survival. Materials and methods: 59 patients with a histological diagnosis of glioma were retrospectively studied (33 M, 26 F, median age 7.2 years). Patients were studied on a 3T scanner with a standardized MR protocol, including conventional and DKI sequences. Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) maps were obtained. Whole tumour volumes (VOIs) were segmented semi-automatically. Mean DKI values were calculated for each metric. The quantitative values from DKI-derived metrics were used to develop a predictive grading model to develop a probability prediction of a high-grade glioma (pHGG). Three models were tested: DTI-based, DKI-based, and combined (DTI and DKI). The grading accuracy of the resulting probabilities was tested with a receiver operating characteristics (ROC) analysis for each model. In order to account for dataset imbalances between pLGG and pHGG, we applied a random synthetic minority oversampling technique (SMOTE) analysis. Lastly, the most accurate model predictions were correlated with progression-free survival (PFS) and overall survival (OS) using the Kaplan–Meier method. Results: The cohort included 46 patients with pLGG and 13 patients with pHGG. The developed model predictions yielded an AUC of 0.859 (95%CI: 0.752–0.966) for the DTI model, of 0.939 (95%CI: 0.879–1) for the DKI model, and of 0.946 (95%CI: 0.890–1) for the combined model, including input from both DTI and DKI metrics, which resulted in the most accurate model. Sample estimation with the random SMOTE analysis yielded an AUC of 0.98 on the testing set. Model predictions from the combined model were significantly correlated with PFS (25.2 months for pHGG vs. 40.0 months for pLGG, p < 0.001) and OS (28.9 months for pHGG vs. 44.9 months for pLGG, p < 0.001). Conclusions: a DKI-based predictive model was highly accurate for pediatric glioma grading. The combined model, derived from both DTI and DKI metrics, proved that DKI-based model predictions of tumour grade were significantly correlated with progression-free survival and overall survival. [ABSTRACT FROM AUTHOR]

Pediatric low-grade gliomas (pLGGs) are the most frequent brain tumor in children. Adjuvant treatment, consisting in chemotherapy and radiotherapy, is often necessary if a complete surgical resection cannot be obtained. Traditional treatment approaches result in a significant long-term morbidity, with a detrimental impact on quality of life. Dysregulation of the mitogen-activated protein kinase (MAPK) pathway is the molecular hallmark of pLGGs and hyperactivation of the downstream mammalian target of rapamycin (mTOR) pathway is frequently observed. We report clinical and radiological results of front-line treatment with everolimus in 10 consecutive patients diagnosed with m-TOR positive pLGGs at the Bambino Gesù Children's Hospital in Rome, Italy. Median duration of treatment was 19 months (range from 13-60). Brain magnetic resonance imaging showed stable disease in 7 patients, partial response in 1 and disease progression in 2. Therapy-related adverse events were always reversible after dose reduction or temporary treatment interruption. To the best of our knowledge, this is the first report of everolimus treatment for chemo- and radiotherapy-naïve children with pLGG. Our results provide preliminary support, despite low sample size, for the use of everolimus as target therapy in pLGG showing lack of progression with a manageable toxicity profile [ABSTRACT FROM AUTHOR]

Treatment-related neurotoxicity is a potentially life-threatening clinical condition that can represent a diagnostic challenge. Differentiating diagnoses between therapy-associated brain injury and recurrent disease can be difficult, and the immediate recognition of neurotoxicity is crucial to providing correct therapeutic management, ensuring damage reversibility. For these purposes, the knowledge of clinical timing and specific treatment protocols is extremely important for interpreting MRI patterns. Neuroradiologic findings are heterogeneous and sometimes overlapping, representing the compounding effect of the different treatments. Moreover, MRI patterns can be acute, subacute or delayed and involve different brain regions, depending on (1) the mechanism of action of the specific medication and (2) which brain regions are selectively vulnerable to specific toxic effects. This review illustrates the most common radiologic appearance of radiotherapy, chemotherapy and medication-associated brain injury in children, with special focus on the application of advanced MRI techniques (diffusion, perfusion and proton spectroscopy) in the diagnosis of the underlying processes leading to brain toxicity. [ABSTRACT FROM AUTHOR]

Pediatric spinal tumors are rare and account for 10% of all central nervous system tumors in children. Onset usually occurs with chronic nonspecific symptoms and may depend on the intra- or extradural neoplastic location. Meningiomas, schwannomas, and neurofibromas are the most common intradural-extramedullary lesions, while astrocytomas and ependymomas represent the majority of intramedullary tumors. The new molecular discoveries regarding pediatric spinal cancer currently contribute to the diagnostic and therapeutic processes. Moreover, some familial genetic syndromes can be associated with the development of spinal tumors. Currently, magnetic resonance imaging (MRI) is the standard reference for the evaluation of pediatric spinal tumors. Our aim in this review was to describe the imaging of the most frequent intradural intra/extramedullary pediatric spinal tumors and to investigate the latest molecular findings and genetic syndromes. [ABSTRACT FROM AUTHOR]

Chordoma in pediatric patients is very rare. Proton therapy has become a gold standard in the treatment of these neoplasms, as high dose escalation can be achieved regarding the target while maximizing the sparing of the healthy tissues near the tumor. The aim of the work was to assess the evolution of morphological sequences during treatment using T1/T2-weighted magnetic resonance imaging (MRI) for the early response assessment of a classic chordoma of the skull base in a pediatric patient who had undergone surgical excision. Our results demonstrated a significant quantitative reduction in the residual nodule component adhered to the medullary bulb junction, with an almost complete recovery of normal anatomy at the end of the irradiation treatment. This was mainly shown in the T2-weighted MRI. On the other hand, the classic component of the lesion was predominantly present and located around the tooth of the axis. The occipital condyles were morphologically and dimensionally stable for the entire irradiation period. In conclusion, the application of this type of monitoring methodology, which is unusual during the administration of a proton treatment for chordoma, highlighted the unexpected early response of the disease. At the same time, it allowed the continuous assessment of the reliability of the treatment plan. [ABSTRACT FROM AUTHOR]

Von Hippel–Lindau (VHL) disease is a heritable cancer syndrome in which benign and malignant tumors and/or cysts develop throughout the central nervous system (CNS) and visceral organs. The disease results from mutations in the VHL tumor suppressor gene located on chromosome 3 (3p25-26). A majority of individuals (60–80%) with VHL disease will develop CNS hemangioblastomas (HMG). Endolymphatic sac tumor (ELST) is an uncommon, locally aggressive tumor located in the medial and posterior petrosal bone region. Its diagnosis is based on clinical, radiological, and pathological correlation, and it can occur in the setting of VHL in up to 10–15% of individuals. We describe a 17-year-old male who presented with a chief complaint of hearing loss. Brain and spine Magnetic Resonance Imaging documented the presence of an expansive lesion in the left cerebellar hemisphere, compatible with HMG in association with a second cerebellopontine lesion compatible with ELST. The peculiarity of the reported case is due to the simultaneous presence of two typical characteristics of VHL, which led to performing comprehensive genetic testing, thus allowing for the diagnosis of VHL. Furthermore, ELST is rare before the fourth decade of life. Early detection of these tumors plays a key role in the optimal management of this condition. [ABSTRACT FROM AUTHOR]

Rosette-forming glioneuronal tumors (RGNTs) are rare, grade I, central nervous system (CNS) tumors typically localized to the fourth ventricle. We describe a 9-year-old girl with dizziness and occipital headache. A magnetic resonance imaging (MRI) revealed a large hypodense posterior fossa mass lesion in relation to the vermis, with cystic component. Surgical resection of the tumor was performed. A RGNT diagnosis was made at the histopathological examination. During follow-up, the patient experienced a first relapse, which was again surgically removed. Eight months after, MRI documented a second recurrence at the local level. She was a candidate for the proton beam therapy (PBT) program. Three years after the end of PBT, the patient had no evidence of disease recurrence. This report underlines that, although RGNTs are commonly associated with an indolent course, they may have the potential for aggressive behavior, suggesting the need for treatment in addition to surgery. Controversy exists in the literature regarding effective management of RGNTs. Chemotherapy and radiation are used as adjuvant therapy, but their efficacy management has not been adequately described in the literature. This is the first case report published in which PBT was proposed for adjuvant therapy in place of chemotherapy in RGNT relapse. [ABSTRACT FROM AUTHOR]

We present a case demonstrating the performance of different radiographical imaging modalities in the diagnostic work-up of a patient with neurofibromatosis type 1 (NF1) and plexiform neurofibroma (PN). The newborn boy showed an expansive-infiltrative cervical and facial mass presented with macrocrania, craniofacial disfigurement, exophthalmos and glaucoma. A computer tomography (CT) and a magnetic resonance imaging (MRI) were performed. The CT was fundamental to evaluate the bone dysmorphisms and the MRI was crucial to estimate the mass extension. The biopsy of the lesion confirmed the suspicion of PN, thus allowing the diagnosis of NF1. PN is a variant of neurofibromas, a peripheral nerves sheath tumor typically associated with NF1. Even through currently available improved detection techniques, NF1 diagnosis at birth remains a challenge due to a lack of pathognomonic signs; therefore congenital PN are recognized in 20% of cases. This case highlights the importance of using different radiological methods both for the correct diagnosis and the follow-up of the patient with PN. Thanks to MRI evaluation, it was possible to identify earlier the progressive increasing size of the PN and the possible life threatening evolution in order to perform a tracheostomy to avoid airways compression. [ABSTRACT FROM AUTHOR]