Apparent diffusion coefficient mapping in medulloblastoma predicts non-infiltrative surgical planes

Differentiating between adult intracranial medulloblastoma and ependymoma using MRI

AIM

To investigate the value of routine magnetic resonance imaging (MRI) examination combined with diffusion-weighted imaging (DWI) in the differential diagnosis of adult intracranial medulloblastomas and ependymomas.

MATERIALS AND METHODS

MRI images of 18 medulloblastomas and 18 ependymomas in adult patients were analysed retrospectively, and the differences in MRI features of lesions and apparent diffusion coefficient (ADC) of solid lesions between the two groups were recorded. Independent sample t-tests and χ2 tests were used to analyse the differences in MRI signs and maximum ADC (ADC_max), minimum ADC (ADC_min), and mean ADC (ADC_mean) values between the two groups. The receiver operating characteristic (ROC) curve was used to determine the differential diagnostic efficacy and optimal threshold for each ADC value.

RESULTS

Age, tumour location, and tumour enhancement were significantly different between adult medulloblastoma and ependymoma (p<0.05). The ADC_max (0.69 ± 0.11 versus 1.04 ± 0.20 × 10^-3 mm²/s, p<0.001), ADC_min (0.57 ± 0.12 versus 0.96 ± 0.21 × 10^-3 mm²/s, p<0.001), and ADC_mean (0.62 ± 0.11 versus 1.00 ± 0.20 × 10^-3 mm²/s, p<0.001) values were significantly lower in adult medulloblastoma than in ependymoma. The areas under the ROC curves of ADC_max, ADC_min, and ADC_mean were 0.951, 0.957, and 0.966, respectively. The optimal ADC_mean threshold was 0.75 × 10^-3 mm²/s, with a sensitivity of 88.9% and a specificity of 88.9%.

CONCLUSION

Routine MRI examination combined with DWI helps differentiate between intracranial infratentorial medulloblastoma and ependymoma in adults.

Differentiation Between Ependymoma and Medulloblastoma in Children with Radiomics Approach

RATIONALE AND OBJECTIVES

Ependymoma (EP) and medulloblastoma (MB) of children are similar in age, location, manifestations and symptoms. Therefore, it is difficult to differentiate them through visual observation in clinical diagnosis. The aim of this study is to investigate the effectiveness of radiomics and machine-learning techniques on multimodal magnetic resonance imaging (MRI) in distinguish EP from MB.

MATERIALS AND METHODS

Three dimensional (3D) tumors were semi-automatic segmented by radiologists from postcontrast T1-weighted images and apparent diffusion coefficient maps in 51 patients (24 EPs, 27 MBs). Then, we extracted radiomics features and further reduced them by three feature selection methods. For each feature selection method, 4 classifiers were adopted which yield 12 different models. After extensive crossvalidation, pairwise test were carried out in receiver operating characteristic curves to explore performance of these models.

RESULTS

The radiomics model built with multivariable logistic regression as feature selection method and random forests as classifier had the best performance, area under the curve achieved 0.91 (95 % confidence interval 0.787-0.968). Five relevant features were highly correlated to discriminate EP and MB, which may used as imaging biomarkers to predict the kinds of tumors.

CONCLUSION

The combination of radiomics and machine-learning approach on 3D multimodal MRI could well distinguish EP and MB of childhood, which assistant doctors in clinical diagnosis. Since there is no uniform model to obtained best performance for every specific data set, it is necessary to try different combination methods.

The predictive value of preoperative apparent diffusion coefficient (ADC) for facial nerve outcomes after vestibular schwannoma resection: clinical study

OBJECT

Diffusion MRI has been used to predict intraoperative consistency of tumors. Apparent diffusion coefficient (ADC) has shown predictive value as an imaging biomarker in many CNS tumors but has not been studied in a large cohort of patients with vestibular schwannoma. In this study, we examine the utility of ADC as a predictive biomarker for intraoperative tumor characteristics and postoperative facial nerve outcome.

METHODS

A retrospective review of patients who underwent vestibular schwannoma resection at our institution from 2008 to 2018 yielded 87 patients, of which 72 met inclusion criteria. Operative reports and clinical records were reviewed for clinical data; MRI data were interpreted in a blinded fashion for qualitative and quantitative biomarkers, including tumor ADC.

RESULTS

Mean tumor ADC values did not predict intraoperative consistency or adherence (p = 0.63). Adherent tumors were associated with worse facial nerve outcomes (p = 0.003). Regression tree analysis identified 3 ADC categories with statistically different facial nerve outcomes. The categories identified were ADC < 1006.04 × 10^-6 mm^2/s; ADC 1006.04-1563.93 × 10^-6 mm^2/s and ADC ≥ 1563.94 × 10^-6 mm^2/s. Postoperative and final House-Brackmann (HB) scores were significantly higher in the intermediate ADC group (2.3, p = 0.0038). HB outcomes were similar between the group with ADC < 1006.04 × 10^-6 mm^2/s and ≥ 1563.94 × 10^-6 mm^2/s (1.3 vs 1.3).

CONCLUSIONS

Middle-range preoperative ADC in vestibular schwannoma suggests a less favorable postoperative HB score. Preoperative measurement of ADC in vestibular schwannoma may provide additional information regarding prognostication of facial nerve outcomes.

Diagnostic accuracy of apparent diffusion coefficient ratio in distinguishing common pediatric CNS posterior fossa tumors

Background

Pilocytic astrocytoma, medulloblastoma, and ependymoma are the most common pediatric CNS tumors seen at posterior cranial fossa and final diagnosis obtained by histopathology after surgical excision. Routine MRI study gives an idea about site and extension of the tumors but provide a little information about type and grade of tumors. ADC ratio had high sensitivity and specificity in differentiation between these tumors as regard type and grade according to tumor cellularity.

Patients and methods

Prospective study conducted on thirty pediatric patients (11 males and 19 females) with CNS posterior fossa masses, their ages ranged from 2 to 17 years (mean age of 8.7 years), conventional MRI, DWI, ADC value, and ADC ratio were done for all patients.

Results

ADC values were significantly different between pilocytic astrocytomas (1.43 ± 0.28 × 10−3) and medulloblastomas (0.71 ± 0. 21 × 10−3) with a P value < 0.001, also there was a significant difference when comparing medulloblastomas (0.71 ± 0.21 × 10−3) with ependymomas (1.04 × 10−3 ± 0.21) with a P value < 0.001. ADC ratio at a cutoff > 1.7 showed significant good power of discrimination of astrocytoma (AUC = 0.85) from ependymoma with 87.5% sensitivity and 93.3% specificity. Similarly, at cutoff ≤ 1.6-> 1.2 was a significant good predictor of ependymoma (AUC = 0.85) with 87.8% sensitivity and 99.5% specificity. While, ADC ratio ≤ 1.2 was significant excellent discriminator of medulloblastoma (AUC = 0.99) with 100% sensitivity and 90% specificity.

Conclusion

ADC ratio is a simple way used in distinguishing juvenile pilocytic astrocytoma, ependymoma, and medulloblastoma, which are the most frequent pediatric posterior fossa tumors. Cutoff ADC ratio of more than 1.7 characteristic of JPA with 87.5% sensitivity and 93.3% specificity, ADC ratio less than 1.1 characteristic of medulloblastoma with 100% sensitivity and 90% specificity. ADC ratios more than 1.1 and less than 1.7 characteristic of ependymoma with 87.8% sensitivity and 99.5% specificity. We recommended ADC ratio as a routine study in evaluation of pediatric CNS posterior fossa tumors.

Hyperacute Infarct on Intraoperative Diffusion Imaging of Pediatric Brain Tumor Surgery

BACKGROUND

Brain neoplasms are the second-most prevalent cancer of childhood for which surgical resection remains the main treatment. Intraoperative MRI is a useful tool to optimize brain tumor resection. It is, however, not known whether intraoperative MRI can detect complications such as hyperacute ischemic infarcts.

METHODS

A retrospective analysis of pre- and intraoperative MRIs including DWI sequence and correlation with early and 3-month postoperative MRIs was conducted to evaluate the incidence of hyperacute arterial infarct during pediatric brain tumor resection. Patient demographics, pathological type, tumor location, resection type as well as preoperative tumoral vessel encasement, evolution of the area of restricted diffusion were collected and analyzed comparatively between the group with acute infarct and the control group. Extent of the hyperacute infarct was compared to both early postsurgical and 3-month follow-up MRIs.

RESULTS

Of the 115 cases, 13 (11%) developed a hyperacute arterial ischemic infarct during brain tumor resection. Tumoral encasement of vessels was more frequent in the infarct group (69%) compared to 25.5% in the control group. Four cases showed additional vessel irregularities on intraoperative MRI. On early follow-up, the infarcted brain area had further progressed in six cases and was stable in seven cases. No further progression was noted after the first week post-surgery.

CONCLUSIONS

Hyperacute infarcts are not rare events to complicate pediatric brain tumor resection. Tumoral encasement of the circle of Willis vessels appears to be the main risk factor. Intraoperative DWI underestimates the final extent of infarcted tissue compared to early postsurgical MRI.

Imaging features of medulloblastoma: Conventional imaging, diffusion-weighted imaging, perfusion-weighted imaging, and spectroscopy: From general features to subtypes and characteristics

Medulloblastoma is a frequent high-grade neoplasm among pediatric brain tumours. Its classical imaging features are a midline tumour growing into the fourth ventricle, hyperdense on CT-scan, displaying a hypersignal when using diffusion-weighted imaging, with a variable contrast enhancement. Nevertheless, atypical imaging features have been widely reported, varying according to the age of the patient, and histopathological subtype. In this study, we review the classical and atypical imaging features of medulloblastomas, with emphasis on advanced MRI techniques, histopathological and molecular subtypes and characteristics, and follow-up modalities.