Relationship between the overall survival in glioblastomas and the radiomic features of intraoperative ultrasound: a feasibility study

Applicability and efficacy of ultrasound elastography in neurosurgery: a systematic review of the literature

INTRODUCTION

Neurosurgery is one of the fields in which intraoperative imaging is paramount. One of these main imaging tools that have been acquiring the interest of the neurosurgical community is Ultrasound elastography (USE), which is an imaging technology sensitive to tissue stiffness. Here we present a systematic review of the use of USE in neurosurgery.

EVIDENCE ACQUISITION

A systematic review of the literature has been performed, according to the PRISMA guideline, for the last 30 years on 3 different databases (MEDLINE, Scopus, and Cochrane), to gather all the studies on the use of ultrasound elastography for neurosurgical pathologies, including both clinical and laboratory studies.

EVIDENCE SYNTHESIS

A total of 15 articles met the inclusion criteria. USE has widely and safely been used especially for oncological lesions (meningiomas and gliomas) and focal cortical dysplasia. However, there are also encouraging laboratory studies about its application for the management of traumatic brain injury, and ischemic stroke.

CONCLUSIONS

This systematic review showed that, despite the lack of strong evidence, USE is a valid intraoperative tool, especially in oncological neurosurgery.

Tumor sound, auditory cues, and tissue pathology in glioma surgery: a proof-of-concept study

OBJECTIVE

Visual, tactile, and auditory cues are used during surgery to differentiate tissue type. Auditory cues in glioma surgery have not been studied previously. The objectives of this study were 1) to evaluate the feasibility of recording sound generated by the suction device during glioma surgery in matched tissue samples, and 2) to characterize the acoustic variation that occurs in different tissue samples.

METHODS

This was a prospective observational proof-of-concept study. Recordings were attempted in 20 patients in order meet the accrual target of 10 patients with matched sound and tissue data. For each patient, three 30- to 60-second recordings were made at these sites: normal white matter, infiltrative margin, and tumor. Tissue samples at each site were then reviewed by experienced neuropathologists, and agreement with surgical identification was estimated with the kappa statistic. Acoustic parameters were characterized for each sample.

RESULTS

Data from 20 patients were analyzed. Patient-related or technical issues resulted in missing data for 10 patients, but the final 10 patients had both audio and tissue data for analysis. Among all tissue samples, fair agreement was observed between surgeon identification and actual pathology (κ = 0.24, standard error 0.096, p = 0.006). Acoustic data suggested that 1) the acoustic stimulus is broadband, 2) acoustic features are somewhat consistent within cases, 3) high-entropy values indicate irregularity of sound over time, and 4) bimodal pitch distributions could differentially reflect cues of interest.

CONCLUSIONS

This study supports the feasibility of collecting intraoperative data on acoustic features during glioma surgery, and it provides an example of how an analysis could be performed to compare different types of tissues.

Artificial intelligence - based ultrasound elastography for disease evaluation - a narrative review

Ultrasound elastography (USE) provides complementary information of tissue stiffness and elasticity to conventional ultrasound imaging. It is noninvasive and free of radiation, and has become a valuable tool to improve diagnostic performance with conventional ultrasound imaging. However, the diagnostic accuracy will be reduced due to high operator-dependence and intra- and inter-observer variability in visual observations of radiologists. Artificial intelligence (AI) has great potential to perform automatic medical image analysis tasks to provide a more objective, accurate and intelligent diagnosis. More recently, the enhanced diagnostic performance of AI applied to USE have been demonstrated for various disease evaluations. This review provides an overview of the basic concepts of USE and AI techniques for clinical radiologists and then introduces the applications of AI in USE imaging that focus on the following anatomical sites: liver, breast, thyroid and other organs for lesion detection and segmentation, machine learning (ML) - assisted classification and prognosis prediction. In addition, the existing challenges and future trends of AI in USE are also discussed.

Applications of elastography in operative neurosurgery: A systematic review

Elastography is an imaging technology capable of measuring tissue stiffness and consistency. The technology has achieved widespread use in the workup and management of diseases of the liver, breast, thyroid, and prostate. Although elastography is increasingly being applied in neurosurgery, it has not yet achieved widespread adoption and many clinicians remain unfamiliar with the technology. Therefore, we sought to summarize the range of applications and elastography modalities available for neurosurgery, report its effectiveness in comparison with conventional imaging methods, and offer recommendations. All full-text English-language manuscripts on the use of elastography for neurosurgical procedures were screened using the PubMed/MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science databases. Thirty-two studies were included with 990 patients, including 21 studies on intracranial tumors, 5 on hydrocephalus, 4 on epilepsy, 1 on spinal cord compression, and 1 on adolescent scoliosis. Twenty studies used ultrasound elastography (USE) whereas 12 used magnetic resonance elastography (MRE). MRE studies were mostly used in the preoperative setting for assessment of lesion stiffness, tumor-brain adherence, diagnostic workup, and operative planning. USE studies were performed intraoperatively to guide resection of lesions, determine residual microscopic abnormalities, assess the tumor-brain interface, and study mechanical properties of tumors. Elastography can assist with resection of brain tissue, detection of microscopic lesions, and workup of hydrocephalus, among other applications under investigation. Its sensitivity often exceeds that of conventional MRI and ultrasound for identifying abnormal tissue and lesion margins.