Intraoperative Evaluation of Brain-Tumor Microvascularization through MicroV IOUS: A Protocol for Image Acquisition and Analysis of Radiomic Features

Role of Advanced Hemodynamic Ultrasound Evaluation in the Differential Diagnosis of Middle Cerebral Artery Stenosis: Introducing Morphological Criteria

OBJECTIVE

The aim of the work described here was to determine the possible impact of the new technique advanced hemodynamic ultrasound evaluation (AHUSE) in identification of severe intracranial stenosis. Transcranial Doppler (TCD) and transcranial color-coded Doppler (TCCD) provide reliable velocimetric data, the indirect analysis of which allows us to obtain information on the patency of vessels and assumed stenosis range. However, very tight stenoses (>95%) cannot be detected with velocimetric criteria because of spectrum drops and the absence of high velocities, so that the right curve of the Spencer equation cannot be solved. Likewise, high velocities are not detected when analyzing morphologically long stenosis. Furthermore, the current classifications based on velocimetric criteria do not provide any categorization on stenoses with multiple acceleration points (MAPs).

METHODS

With this Technical Note we aim to introduce, in addition to velocimetric criteria, more morphological criteria based on TCCD with the algorithm of AHUSE to optimize the characterization of intracranial stenosis (IS). TCCD-AHUSE relies on intensity-based next-generation techniques and can be used to identify IS with MAPs and simultaneously perform a morphological assessment of the stenosis length.

RESULTS

We introduce a new technical ultrasound (U) approach that we tested in a sample of four different types of stenoses combining velocimetric data and AHUSE using Esaote Microvascularization (MicroV) technique to the M1 tract of the middle cerebral artery (MCA).

CONCLUSION

The authors believe that a multiparametric evaluation is more sensitive and supports the clinician by introducing the morphological concept, not just the velocimetric concept, to differentiate the IS pattern of MCA. The potential for developing a diagnostic/prognostic algorithm is discussed.

Forecasting Molecular Features in IDH-Wildtype Gliomas: The State of the Art of Radiomics Applied to Neurosurgery

BACKGROUND

The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS), published in 2021, marks a step forward the future diagnostic approach to these neoplasms. Alongside this, radiomics has experienced rapid evolution over the last several years, allowing us to correlate tumor imaging heterogeneity with a wide range of tumor molecular and subcellular features. Radiomics is a translational field focused on decoding conventional imaging data to extrapolate the molecular and prognostic features of tumors such as gliomas. We herein analyze the state-of-the-art of radiomics applied to glioblastoma, with the goal to estimate its current clinical impact and potential perspectives in relation to well-rounded patient management, including the end-of-life stage.

METHODS

A literature review was performed on the PubMed, MEDLINE and Scopus databases using the following search items: "radiomics and glioma", "radiomics and glioblastoma", "radiomics and glioma and IDH", "radiomics and glioma and TERT promoter", "radiomics and glioma and EGFR", "radiomics and glioma and chromosome".

RESULTS

A total of 719 articles were screened. Further quantitative and qualitative analysis allowed us to finally include 11 papers. This analysis shows that radiomics is rapidly evolving towards a reliable tool.

CONCLUSIONS

Further studies are necessary to adjust radiomics' potential to the newest molecular requirements pointed out by the 2021 WHO classification of CNS tumors. At a glance, its application in the clinical routine could be beneficial to achieve a timely diagnosis, especially for those patients not eligible for surgery and/or adjuvant therapies but still deserving palliative and supportive care.