Role of dynamic CT perfusion study in evaluating various intracranial space-occupying lesions

Radiomics features for the discrimination of tuberculomas from high grade gliomas and metastasis: a multimodal study

BACKGROUND

Tuberculomas are prevalent in developing countries and demonstrate variable signals on MRI resulting in the overlap of the conventional imaging phenotype with other entities including glioma and brain metastasis. An accurate MRI diagnosis is important for the early institution of anti-tubercular therapy, decreased patient morbidity, mortality, and prevents unnecessary neurosurgical excision. This study aims to assess the potential of radiomics features of regular contrast images including T1W, T2W, T2W FLAIR, T1W post contrast images, and ADC maps, to differentiate between tuberculomas, high-grade-gliomas and metastasis, the commonest intra parenchymal mass lesions encountered in the clinical practice.

METHODS

This retrospective study includes 185 subjects. Images were resampled, co-registered, skull-stripped, and zscore-normalized. Automated lesion segmentation was performed followed by radiomics feature extraction, train-test split, and features reduction. All machine learning algorithms that natively support multiclass classification were trained and assessed on features extracted from individual modalities as well as combined modalities. Model explainability of the best performing model was calculated using the summary plot obtained by SHAP values.

RESULTS

Extra tree classifier trained on the features from ADC maps was the best classifier for the discrimination of tuberculoma from high-grade-glioma and metastasis with AUC-score of 0.96, accuracy-score of 0.923, Brier-score of 0.23.

CONCLUSION

This study demonstrates that radiomics features are effective in discriminating between tuberculoma, metastasis, and high-grade-glioma with notable accuracy and AUC scores. Features extracted from the ADC maps surfaced as the most robust predictors of the target variable.

Diagnostic Algorithm for Intracranial Lesions in the Emergency Department: Effectiveness of the Relative Brain Volume and Hounsfield Unit Value Measured by Perfusion Tomography

Background Early treatment of intracranial lesions in the emergency department is crucial, but it can be challenging to differentiate between them. This differentiation is essential because the treatment of each type of lesion is different. Cerebral computed tomography perfusion (CTP) imaging can help visualize the vascularity of brain lesions and provide absolute quantification of physiological parameters. Compared to magnetic resonance imaging, CTP has several advantages, such as simplicity, wide availability, and reproducibility. Purpose This study aimed to assess the effectiveness of Hounsfield units (HU) in measuring the density of hypercellular lesions and the ability of CTP to quantify hemodynamics in distinguishing intracranial space-occupying lesions. Methods A retrospective study was conducted from March 2016 to March 2022. All patients underwent CTP and CT scans, and relative cerebral blood volume (rCBV) and HU were obtained for intracranial lesions. Results We included a total of 244 patients in our study. This group consisted of 87 (35.7%) individuals with glioblastomas (GBs), 48 (19.7%) with primary central nervous system lymphoma (PCNSL), 45 (18.4%) with metastases (METs), and 64 (26.2) with abscesses. Our study showed that the HUs for METs were higher than those for GB (S 57.4% and E 88.5%). In addition, rCBV values for PCNSL and abscesses were lower than those for GB and METs. The HU in PCNSL was higher than those in abscesses (S 94.1% and E 96.6%). Conclusion PCT parameters provide valuable information for diagnosing brain lesions. A comprehensive assessment improves accuracy. Combining rCBV and HU enhances diagnostic accuracy, making it a valuable tool for distinguishing between lesions. PCT's widespread availability allows for the use of both anatomical and functional information with high spatial resolution for diagnosing and managing brain tumor patients.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

Efficacy of Perfusion Computed Tomography (PCT) in Differentiating High-Grade Gliomas from Low Grade Gliomas, Lymphomas, Metastases and Abscess

INTRODUCTION

Tumoural angioneogenesis and its quantification are important in predicting the tumour grade and in the management with respect to the treatment available and to assess the response to treatment and the prognosis. It also plays major role in the growth and spread of tumours. Hence, a need arises for non-invasive in vivo methods to assess tumour angioneogenesis and tumour grade at the time of presentation and for monitoring the response during treatment and follow up. In this regard Perfusion Computed Tomography (PCT) can be easily added into routine CT studies to obtain such information on lesion physiology along with its morphology.

AIM

Prospective evaluation of the efficacy of PCT in differentiating high grade gliomas from low grade glioma lymphomas, metastases and abscess.

MATERIALS AND METHODS

Perfusion CT was performed in 68 patients (17 high-grade gliomas, 10 low-grade gliomas, 7 lymphomas, 27 metastases and 7 abscess). Perfusion parameters which include Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Mean Transit Time (MTT) and Time To Peak (TTP) were derived both from the lesion and the normal parenchyma and were Normalized (n) by obtaining the ratio. Statistical analysis for high grade versus low-grade gliomas, high grade gliomas versus lymphomas, metastases and abscess was performed.

RESULTS

Difference in the mean nCBV and nCBF in high grade gliomas were statistically significant from low grade gliomas with cut off of > 3.07 for nCBV and > 2.08 for nCBF yielding good sensitivity and specificity. Difference in the mean nCBV and nMTT in the lymphomas were statistically significant from high grade gliomas (p<0.05) with cut off of <3.40 for nCBV and >1.83 for nMTT yielding good sensitivity and specificity. Difference in the mean nCBV and nMTT in the metastases were statistically significant from high grade gliomas (p<0.05) with cut off of >4.95 for nCBV and >1.88 for nMTT yielding a fair sensitivity and specificity. No statistical significant difference seen among the parameters in differentiating high grade gliomas and abscess.

CONCLUSION

Cerebral PCT greatly adds to the diagnostic accuracy when the diagnosis of a common intra-axial lesion based on morphological characters becomes uncertain.