Errors, limitations, and pitfalls in the diagnosis of central and peripheral nervous system lesions in intraoperative cytology and frozen sections

A Multi-Center, Multi-Parametric MRI Dataset of Primary and Secondary Brain Tumors

Brain metastases (BMs) and high-grade gliomas (HGGs) are the most common and aggressive types of malignant brain tumors in adults, with often poor prognosis and short survival. As their clinical symptoms and image appearances on conventional magnetic resonance imaging (MRI) can be astonishingly similar, their accurate differentiation based solely on clinical and radiological information can be very challenging, particularly for "cancer of unknown primary", where no systemic malignancy is known or found. Non-invasive multiparametric MRI and radiomics offer the potential to identify these distinct biological properties, aiding in the characterization and differentiation of HGGs and BMs. However, there is a scarcity of publicly available multi-origin brain tumor imaging data for tumor characterization. In this paper, we introduce a multi-center, multi-origin brain tumor MRI (MOTUM) imaging dataset obtained from 67 patients: 29 with high-grade gliomas, 20 with lung metastases, 10 with breast metastases, 2 with gastric metastasis, 4 with ovarian metastasis, and 2 with melanoma metastasis. This dataset includes anonymized DICOM files alongside processed FLAIR, T1-weighted, contrast-enhanced T1-weighted, T2-weighted sequences images, segmentation masks of two tumor regions, and clinical data. Our data-sharing initiative is to support the benchmarking of automated tumor segmentation, multi-modal machine learning, and disease differentiation of multi-origin brain tumors in a multi-center setting.

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparametric MRI to differentiate the pathological subtypes of brain metastasis (BM) in lung cancer patients. This retrospective analysis collected 246 patients (456 BMs) from five medical centers from July 2016 to June 2022. The BMs were from small-cell lung cancer (SCLC, n = 230) and non-small-cell lung cancer (NSCLC, n = 226; 119 adenocarcinoma and 107 squamous cell carcinoma). Patients from four medical centers were assigned to training set and internal validation set with a ratio of 4:1, and we selected another medical center as an external test set. An attention-guided residual fusion network (ARFN) model for T1WI, T2WI, T2-FLAIR, DWI, and contrast-enhanced T1WI based on the ResNet-18 basic network was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. Compared with models based on five single-sequence and other combinations, a multiparametric MRI model based on five sequences had higher specificity in distinguishing BMs from different types of lung cancer. In the internal validation and external test sets, AUCs of the model for the classification of SCLC and NSCLC brain metastasis were 0.796 and 0.751, respectively; in terms of differentiating adenocarcinoma from squamous cell carcinoma BMs, the AUC values of the prediction models combining the five sequences were 0.771 and 0.738, respectively. DL together with multiparametric MRI has discriminatory feasibility in identifying pathology type of BM from lung cancer.

Advancements in Neurosurgical Intraoperative Histology

Despite their relatively low incidence globally, central nervous system (CNS) tumors remain amongst the most lethal cancers, with only a few other malignancies surpassing them in 5-year mortality rates. Treatment decisions for brain tumors heavily rely on histopathological analysis, particularly intraoperatively, to guide surgical interventions and optimize patient outcomes. Frozen sectioning has emerged as a vital intraoperative technique, allowing for highly accurate, rapid analysis of tissue samples, although it poses challenges regarding interpretive errors and tissue distortion. Raman histology, based on Raman spectroscopy, has shown great promise in providing label-free, molecular information for accurate intraoperative diagnosis, aiding in tumor resection and the identification of neurodegenerative disease. Techniques including Stimulated Raman Scattering (SRS), Coherent Anti-Stokes Raman Scattering (CARS), Surface-Enhanced Raman Scattering (SERS), and Tip-Enhanced Raman Scattering (TERS) have profoundly enhanced the speed and resolution of Raman imaging. Similarly, Confocal Laser Endomicroscopy (CLE) allows for real-time imaging and the rapid intraoperative histologic evaluation of specimens. While CLE is primarily utilized in gastrointestinal procedures, its application in neurosurgery is promising, particularly in the context of gliomas and meningiomas. This review focuses on discussing the immense progress in intraoperative histology within neurosurgery and provides insight into the impact of these advancements on enhancing patient outcomes.

Virtual Staining of Nonfixed Tissue Histology

Surgical pathology workflow involves multiple labor-intensive steps, such as tissue removal, fixation, embedding, sectioning, staining, and microscopic examination. This process is time-consuming and costly and requires skilled technicians. In certain clinical scenarios, such as intraoperative consultations, there is a need for faster histologic evaluation to provide real-time surgical guidance. Currently, frozen section techniques involving hematoxylin and eosin (H&E) staining are used for intraoperative pathology consultations. However, these techniques have limitations, including a turnaround time of 20 to 30 minutes, staining artifacts, and potential tissue loss, negatively impacting accurate diagnosis. To address these challenges, researchers are exploring alternative optical imaging modalities for rapid microscopic tissue imaging. These modalities differ in optical characteristics, tissue preparation requirements, imaging equipment, and output image quality and format. Some of these imaging methods have been combined with computational algorithms to generate H&E-like images, which could greatly facilitate their adoption by pathologists. Here, we provide a comprehensive, organ-specific review of the latest advancements in emerging imaging modalities applied to nonfixed human tissue. We focused on studies that generated H&E-like images evaluated by pathologists. By presenting up-to-date research progress and clinical utility, this review serves as a valuable resource for scholars and clinicians, covering some of the major technical developments in this rapidly evolving field. It also offers insights into the potential benefits and drawbacks of alternative imaging modalities and their implications for improving patient care.

Intraoperative Integrated Diagnostic System for Malignant Central Nervous System Tumors

PURPOSE

The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors uses an integrated approach involving histopathology and molecular profiling. Because majority of adult malignant brain tumors are gliomas and primary CNS lymphomas (PCNSL), rapid differentiation of these diseases is required for therapeutic decisions. In addition, diffuse gliomas require molecular information on single-nucleotide variants (SNV), such as IDH1/2. Here, we report an intraoperative integrated diagnostic (i-ID) system to classify CNS malignant tumors, which updates legacy frozen-section (FS) diagnosis through incorporation of a qPCR-based genotyping assay.

EXPERIMENTAL DESIGN

FS evaluation, including GFAP and CD20 rapid IHC, was performed on adult malignant CNS tumors. PCNSL was diagnosed through positive CD20 and negative GFAP immunostaining. For suspected glioma, genotyping for IDH1/2, TERT SNV, and CDKN2A copy-number alteration was routinely performed, whereas H3F3A and BRAF SNV were assessed for selected cases. i-ID was determined on the basis of the 2021 WHO classification and compared with the permanent integrated diagnosis (p-ID) to assess its reliability.

RESULTS

After retrospectively analyzing 153 cases, 101 cases were prospectively examined using the i-ID system. Assessment of IDH1/2, TERT, H3F3AK27M, BRAFV600E, and CDKN2A alterations with i-ID and permanent genomic analysis was concordant in 100%, 100%, 100%, 100%, and 96.4%, respectively. Combination with FS and intraoperative genotyping assay improved diagnostic accuracy in gliomas. Overall, i-ID matched with p-ID in 80/82 (97.6%) patients with glioma and 18/19 (94.7%) with PCNSL.

CONCLUSIONS

The i-ID system provides reliable integrated diagnosis of adult malignant CNS tumors.

Application of a Novel Miniaturized Histopathologic Microscope for Ex Vivo Identifying Cerebral Glioma Margins Rapidly During Surgery: A Parallel Control Study

PURPOSE

The purpose of our study is to assess the clinical performance of the DiveScope, a novel handheld histopathologic microscope in rapidly differentiating glioma from normal brain tissue during neurosurgery.

METHODS

Thirty-two ex vivo specimens from 18 patients were included in the present study. The excised suspicious tissue was sequentially stained with sodium fluorescein and methylene blue and scanned with DiveScope during surgery. The adjacent tissue was sent to the department of pathology for frozen section examination. They would eventually be sent to the pathology department later for hematoxylin and eosin staining for final confirmation. The positive likelihood ratio, negative likelihood ratio, sensitivity, specificity, and area under the curve of the device were calculated. In addition, the difference in time usage between DiveScope and frozen sections was compared for the initial judgment.

RESULTS

The sensitivity and specificity of the DiveScope after analyzing hematoxylin and eosin -staining sections, were 88.29% and 100%, respectively. In contrast, the sensitivity and specificity of the frozen sections histopathology were 100% and 75%, respectively. The area under the curve of the DiveScope and the frozen sections histopathology was not significant ( P =0.578). Concerning time usage, DiveScope is significantly much faster than the frozen sections histopathology no matter the size of tissue.

CONCLUSION

Compared with traditional pathological frozen sections, DiveScope was faster and displayed an equal accuracy for judging tumor margins intraoperatively.

In situ detection of human glioma based on tissue optical properties using diffuse reflectance spectroscopy

Safely maximizing brain cancer removal without injuring adjacent healthy tissue is crucial for optimal treatment outcomes. However, it is challenging to distinguish cancer from noncancer intraoperatively. This study aimed to explore the feasibility of diffuse reflectance spectroscopy (DRS) as a label-free and real-time detection technology for discrimination between brain cancer and noncancer tissues. Fifty-five fresh cancer and noncancer specimens from 19 brain surgeries were measured with DRS, and the results were compared with co-registered clinical standard histopathology. Tissue optical properties were quantitatively obtained from the diffuse reflectance spectra and compared among different types of brain tissues. A machine learning-based classifier was trained to differentiate cancerous versus noncancerous tissues. Our method could achieve a sensitivity of 93% and specificity of 95% for discriminating high-grade glioma from normal white matter. Our results showed that DRS has the potential to be used for label-free, real-time in vivo cancer detection during brain surgery.

Unveiling the potential application of intraoperative brain smear for brain tumor diagnosis in low-middle-income countries: A comprehensive systematic review

Background

Immediate intraoperative histopathological examination of tumor tissue is indispensable for a neurosurgeon to track surgical resection. A brain smear is a simple, rapid, and cost-effective technique, particularly important in the diagnosis of brain tumors. The study aims to determine the effectiveness of intraoperative brain smear in the diagnosis of brain tumors in low- and middle-income countries (LMICs), while also evaluating its sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy.

Methods

A comprehensive search of the literature was conducted using PubMed, Scopus, and Google Scholar. The retrieved articles were independently screened by two reviewers. The data was extracted, processed, and organized using Microsoft Excel.

Results

A total of 59 out of 553 articles screened were included in the final analysis. The sensitivity and specificity of the intraoperative smear of brain tumors were found to be over 90% in most studies. The PPV was consistently above 90% in 11 studies, reaching 100% in one study and the NPV varied, ranging from 63% to 100%, and the accuracy was found to be >80% in most studies. One recurrent theme in the majority of the included studies was that an intraoperative brain smear is a cost-effective, quick, accessible, and accurate method of diagnosing brain tumors, requiring minimal training and infrastructure.

Conclusion

Intraoperative brain smear is a simple, rapid, cost-effective, and highly sensitive diagnostic modality for brain tumors. It can be a viable and accessible alternative to more traditional methods such as frozen sections and can be incorporated into neurosurgical practice in LMICs as a reliable and efficient diagnostic tool.

Intraoperative shear-wave elastography and superb microvascular imaging contribute to the glioma grading

BACKGROUND

To explore the diagnostic value and feasibility of shear wave elastography and superb microvascular imaging in the grading diagnosis of glioma intraoperatively.

MATERIALS AND METHODS

Forty-nine patients with glioma were included in this study. B-mode ultrasonography, Young's modulus in shear-wave elastography (SWE) and vascular architecture in superb microvascular imaging(SMI) of tumor tissue and peritumoral tissue were analyzed. Receiver operating characteristic(ROC) curve analysis was used to evaluate the diagnostic effect of SWE. Logistic regression model was used to calculate the prediction probability of HGG diagnosis.

RESULTS

Compared with LGG, HGG was often characterized by peritumoral edema in B mode (P < 0.05). There was a significant difference in Young's modulus between HGG and LGG; the diagnostic threshold of HGG and LGG was 13.05 kPa, the sensitivity was 78.3%, and the specificity was 76.9%. The vascular architectures of the tumor tissue and peritumoral tissues of HGG and LGG were significantly different (P < 0.05). The vascular architectures of peritumoral tissue in HGG often characterized by distorted blood flow signals surrounding the tumor (14/26,53.8%); in the tumor tissue, HGG often presents as dilated and bent vessels(19/26,73.1%). The elasticity value of SWE and the tumor vascular architectures of SMI were correlated with the diagnosis of HGG.

CONCLUSION

Intraoperative ultrasound (ioUS), especially SWE, and SMI are beneficial for the differentiation of HGG and LGG and may help optimize clinical surgical procedures.

Clinical feasibility of miniaturized Lissajous scanning confocal laser endomicroscopy for indocyanine green-enhanced brain tumor diagnosis

Background

Intraoperative real-time confocal laser endomicroscopy (CLE) is an alternative modality for frozen tissue histology that enables visualization of the cytoarchitecture of living tissues with spatial resolution at the cellular level. We developed a new CLE with a "Lissajous scanning pattern" and conducted a study to identify its feasibility for fluorescence-guided brain tumor diagnosis.

Materials and methods

Conventional hematoxylin and eosin (H&E) histological images were compared with indocyanine green (ICG)-enhanced CLE images in two settings (1): experimental study with in vitro tumor cells and ex vivo glial tumors of mice, and (2) clinical evaluation with surgically resected human brain tumors. First, CLE images were obtained from cultured U87 and GL261 glioma cells. Then, U87 and GL261 tumor cells were implanted into the mouse brain, and H&E staining was compared with CLE images of normal and tumor tissues ex vivo. To determine the invasion of the normal brain, two types of patient-derived glioma cells (CSC2 and X01) were used for orthotopic intracranial tumor formation and compared using two methods (CLE vs. H&E staining). Second, in human brain tumors, tissue specimens from 69 patients were prospectively obtained after elective surgical resection and were also compared using two methods, namely, CLE and H&E staining. The comparison was performed by an experienced neuropathologist.

Results

When ICG was incubated in vitro, U87 and GL261 cell morphologies were well-defined in the CLE images and depended on dimethyl sulfoxide. Ex vivo examination of xenograft glioma tissues revealed dense and heterogeneous glioma cell cores and peritumoral necrosis using both methods. CLE images also detected invasive tumor cell clusters in the normal brain of the patient-derived glioma xenograft model, which corresponded to H&E staining. In human tissue specimens, CLE images effectively visualized the cytoarchitecture of the normal brain and tumors. In addition, pathognomonic microstructures according to tumor subtype were also clearly observed. Interestingly, in gliomas, the cellularity of the tumor and the density of streak-like patterns were significantly associated with tumor grade in the CLE images. Finally, panoramic view reconstruction was successfully conducted for visualizing a gross tissue morphology.

Conclusion

In conclusion, the newly developed CLE with Lissajous laser scanning can be a helpful intraoperative device for the diagnosis, detection of tumor-free margins, and maximal safe resection of brain tumors.

Differentiating Primary Tumors for Brain Metastasis with Integrated Radiomics from Multiple Imaging Modalities

Objectives. To differentiate the primary site of brain metastases (BMs) is of high clinical value for the successful management of patients with BM. The purpose of this study is to investigate a combined radiomics model with computer tomography (CT) and magnetic resonance imaging (MRI) images in differentiating BMs originated from lung and breast cancer. Methods. Pretreatment cerebral contrast enhanced CT and T1-weighted MRI images of 78 patients with 179 BMs from primary lung and breast cancer were retrospectively analyzed. Radiomic features were extracted from contoured BM lesions and selected using the Mann–Whitney $U$ test and the least absolute shrinkage and selection operator (LASSO) logistic regression. Binary logistic regression (BLR) and support vector machine (SVM) models were built and evaluated based on selected radiomic features from CT alone, MRI alone, and combined images to differentiate BMs originated from lung and breast cancer. Results. A total of 10 and 6 optimal radiomic features were screened out of 1288 CT and 1197 MRI features, respectively. The mean area under the curves (AUCs) of the BLR and SVM models using fivefolds cross-validation were 0.703 vs. 0.751, 0.718 vs. 0.754, and 0.781 vs. 0.803 in the training dataset and 0.708 vs. 0.763, 0.715 vs. 0.717, and 0.771 vs. 0.805 in the testing dataset for models with CT alone, MRI alone, and combined CT and MRI radiomic features, respectively. Conclusions. Radiomics model based on combined CT and MRI features is feasible and accurate in the differentiation of the primary site of BMs from lung and breast cancer.

An Audit of Diagnostic Disparity between Intraoperative Frozen Section Diagnosis and Final Histopathological Diagnosis of Central Nervous System Lesions at a Tertiary Care Center

Introduction Evaluation of intraoperative squash smear and frozen section (FS) in central nervous system (CNS) neoplasms is consistently practiced for rapid assessment and has several advantages to its credence. It is an invaluable tool to ensure adequacy of tissue obtained to establish the diagnosis. Moreover, it aids in guiding the surgeon for critical decisions regarding the extent of resection. Although molecular markers have been integrated with morphology in the revised 2016 World Health Organization classification of brain tumors, precise morphological assessment still remains the foundation for the diagnosis and rapid intraoperative assessment of morphological details is equally critical and rewarding.

Objective This study aims to audit the diagnostic disparity between intraoperative diagnoses based on a combination of squash cytology and FS in cases of CNS lesions with gold standard, final diagnosis based on examination of formalin fixed paraffin embedded hematoxylin, and eosin-stained tissue sections.

Materials and Methods All intraoperative squash cytology and FS reported for CNS lesions from January 2017 to December 2020 were reviewed. The cases were categorized into three groups—group 1: when diagnosis of intraoperative diagnosis based on a combination of squash cytology and FS was same as the final histopathological diagnosis (concordant), group 2: partially concordant, and group 3: discordant cases.

Statistical Analysis Descriptive statistics was used to classify the data and diagnostic accuracy was calculated.

Results Complete concordance was present in 69.96% (191/273) cases, 20.1% (55/273) cases showed partial concordance, and 9.89% (27/273) cases were discordant with histopathological diagnosis. Out of the 27 discordant cases, misclassification of tumor type was the most common category (11 cases, 40%), followed by grading mismatch (7 cases, 25.9%), and misdiagnosis of tumor versus nontumor conditions (9 cases, 33.3%).

Conclusion Our study shows that combination of intraoperative squash cytology and FS shows a high percentage of accuracy in arriving at intraoperative diagnosis in cases of intracranial lesions. Regular audits of discordant cases should be conducted by surgeons and pathologists as part of a quality assurance measure to sensitize themselves with the potential pitfalls, minimizing misinterpretation and helping in providing a more conclusive opinion to the operating surgeons.

Primary germinoma of the medulla oblongata: illustrative case

BACKGROUND

Primary central nervous system germinomas of the medulla oblongata are extremely rare and usually have been found in young female Asian patients. The authors present an illustrative case of a patient who presented with severe medullary and posterior cord syndrome, the first South American case published to date, to the authors’ knowledge.

OBSERVATIONS

Initially, the radiological differential diagnosis did not include this entity. The lesion was located at the obex and exhibited a well-delineated contrast enhancement without hydrocephalus. An emergency decompressive partial resection following functional limits was performed. After histological confirmation, radiotherapy was indicated, with complete remission achieved at a 6-month follow-up. The patient, however, continued to have a severe proprioceptive disorder. The literature review identified 21 other such patients. The mean age for this location was 23 years, with a strong female and Asian origin predilection. All tumors exhibited contrast enhancement, and only one presented with hydrocephalus.

LESSONS

In the absence of elevated tumor markers, radiological clues such as a well-delineated, contrast-enhanced lesion arising from the obex, without hydrocephalus, associated with demographic features such as young age, female sex, and Asian heritage, should evoke a high level of suspicion for this diagnosis. Gross total resection must not be attempted, because this tumor is potentially curable with high-dose radiotherapy.

Differentiating solitary brain metastases from glioblastoma by radiomics features derived from MRI and 18F-FDG-PET and the combined application of multiple models

This study aimed to explore the ability of radiomics derived from both MRI and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) images to differentiate glioblastoma (GBM) from solitary brain metastases (SBM) and to investigate the combined application of multiple models. The imaging data of 100 patients with brain tumours (50 GBMs and 50 SBMs) were retrospectively analysed. Three model sets were built on MRI, 18F-FDG-PET, and MRI combined with 18F-FDG-PET using five feature selection methods and five classification algorithms. The model set with the highest average AUC value was selected, in which some models were selected and divided into Groups A, B, and C. Individual and joint voting predictions were performed in each group for the entire data. The model set based on MRI combined with 18F-FDG-PET had the highest average AUC compared with isolated MRI or 18F-FDG-PET. Joint voting prediction showed better performance than the individual prediction when all models reached an agreement. In conclusion, radiomics derived from MRI and 18F-FDG-PET could help differentiate GBM from SBM preoperatively. The combined application of multiple models can provide greater benefits.

Strategy of De Novo Design toward First-In-Class Imaging Agents for Simultaneously Differentiating Glioma Boundary and Grades

The extent of resection and tumor grade are two predominant prognostic factors for glioma. Fluorescent imaging is promising to facilitate accurate resection and simultaneous tumor grading. However, no probe fulfilling this task has been reported. Herein, we proposed a strategy of de novo design toward first-in-class fluorescent probes for simultaneously differentiating glioma boundary and grades. By bioinformatics analysis in combination with experimental validation, platelet-derived growth factor receptor β (PDGFRβ) was revealed as a promising biomarker for glioma imaging and grading. Then, fluorogenic probe PDGFP 1 was designed, guided by the structure-activity relationship study. Finally, the probe was demonstrated to stain glioma cells and tissues in the mice orthotopic glioma model with high selectivity over normal brain cells or tissues. Meanwhile, ex vivo experiments using patient-derived samples indicated that the fluorescence was significantly positively correlated with the tumor grades. This result highlighted the feasibility of the three-step de novo probe design strategy and suggested PDGFP 1 as a promising probe for simultaneously differentiating glioma boundary and grades, showing prospects of clinical translation.

Intraoperative squash Cytology of diffuse glioma not otherwise specified, of the Cerebellum

OBJECTIVE

Diffuse glioma arises anywhere in the CNS, but most frequent in the cerebral hemispheres. The tumor tends to be seen in children and in younger adults aged 20-30. We report one such case in an older female patient presenting the intraoperative cytology of the tumor.

CASE REPORT

A 48-year-old female was diagnosed by MRI with a tumor of cerebellum. Cytologic material was obtained during the resection of the tumor and diagnosed cytologically as glioma.

CONCLUSION

This case is presented to focus the ability of the intraoperative cytology in diagnosis of the glioma, using immunocytology and confirmed by histo- immunohistology.

Deep Neural Network for Differentiation of Brain Tumor Tissue Displayed by Confocal Laser Endomicroscopy

Background

Reliable on site classification of resected tumor specimens remains a challenge. Implementation of high-resolution confocal laser endoscopic techniques (CLEs) during fluorescence-guided brain tumor surgery is a new tool for intraoperative tumor tissue visualization. To overcome observer dependent errors, we aimed to predict tumor type by applying a deep learning model to image data obtained by CLE.

Methods

Human brain tumor specimens from 25 patients with brain metastasis, glioblastoma, and meningioma were evaluated within this study. In addition to routine histopathological analysis, tissue samples were stained with fluorescein ex vivo and analyzed with CLE. We trained two convolutional neural networks and built a predictive level for the outputs.

Results

Multiple CLE images were obtained from each specimen with a total number of 13,972 fluorescein based images. Test accuracy of 90.9% was achieved after applying a two-class prediction for glioblastomas and brain metastases with an area under the curve (AUC) value of 0.92. For three class predictions, our model achieved a ratio of correct predicted label of 85.8% in the test set, which was confirmed with five-fold cross validation, without definition of confidence. Applying a confidence rate of 0.999 increased the prediction accuracy to 98.6% when images with substantial artifacts were excluded before the analysis. 36.3% of total images met the output criteria.

Conclusions

We trained a residual network model that allows automated, on site analysis of resected tumor specimens based on CLE image datasets. Further in vivo studies are required to assess the clinical benefit CLE can have.

Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis

Background

The differential diagnosis of glioblastomas (GBM) from solitary brain metastases (SBM) is essential because the surgical strategy varies according to the histopathological diagnosis. Intraoperative ultrasound elastography (IOUS-E) is a relatively novel technique implemented in the surgical management of brain tumors that provides additional information about the elasticity of tissues. This study compares the discriminative capacity of intraoperative ultrasound B-mode and strain elastography to differentiate GBM from SBM.

Methods

We performed a retrospective analysis of patients who underwent craniotomy between March 2018 to June 2020 with glioblastoma (GBM) and solitary brain metastases (SBM) diagnoses. Cases with an intraoperative ultrasound study were included. Images were acquired before dural opening, first in B-mode, and then using the strain elastography module. After image pre-processing, an analysis based on deep learning was conducted using the open-source software Orange. We have trained an existing neural network to classify tumors into GBM and SBM via the transfer learning method using Inception V3. Then, logistic regression (LR) with LASSO (least absolute shrinkage and selection operator) regularization, support vector machine (SVM), random forest (RF), neural network (NN), and k-nearest neighbor (kNN) were used as classification algorithms. After the models’ training, ten-fold stratified cross-validation was performed. The models were evaluated using the area under the curve (AUC), classification accuracy, and precision.

Results

A total of 36 patients were included in the analysis, 26 GBM and 10 SBM. Models were built using a total of 812 ultrasound images, 435 of B-mode, 265 (60.92%) corresponded to GBM and 170 (39.8%) to metastases. In addition, 377 elastograms, 232 (61.54%) GBM and 145 (38.46%) metastases were analyzed. For B-mode, AUC and accuracy values of the classification algorithms ranged from 0.790 to 0.943 and from 72 to 89%, respectively. For elastography, AUC and accuracy values ranged from 0.847 to 0.985 and from 79% to 95%, respectively.

Conclusion

Automated processing of ultrasound images through deep learning can generate high-precision classification algorithms that differentiate glioblastomas from metastases using intraoperative ultrasound. The best performance regarding AUC was achieved by the elastography-based model supporting the additional diagnostic value that this technique provides.

Evaluation Study of Intraoperative Cytology Smear and Frozen Section of Glioma

Objective:

Glioma is the commonest primary malignant brain tumour. Diagnosis is made based on cytology smear, frozen section and histopathological examination. Intraoperative pathological diagnosis using either cytology smear, frozen section or combination of both, plays a crucial role in patient’s future management and prognosis. This study aims to determine the accuracy of cytology smear and frozen section in glioma, and to compare the difference between both techniques.

Methods:

A cross-sectional study was conducted involving 22 cases of glioma diagnosed intraoperatively from January 2013 until August 2019 in Hospital Universiti Sains Malaysia. The selected tissues were processed for cytology smear and frozen section. The remaining tissues were proceeded for paraffin section. The diagnosis was categorized as either low-grade or high-grade glioma based on cellularity, nuclear pleomorphism, mitotic count, microvascular proliferation and necrosis. The sensitivity and specificity of frozen section and cytology smears were determined based on paraffin section being as the gold standard. The accuracy of both techniques was compared using statistical analysis.

Results:

The overall sensitivity and specificity of cytology smear were 100% and 76.9%, respectively. Meanwhile, the sensitivity and specificity of frozen section were 100% and 84.6%. There was no significant difference in diagnostic accuracy between cytology smear and frozen section in glioma (p>0.05).

Conclusion:

Cytology smears provides an alternative method for frozen section due to good cellularity and morphology on smear. Cytology smear is rapid, inexpensive, small amount of tissue requirement and less technical demand. This finding may benefit to the hospital or treatment centres where frozen section facility is unavailable.

Squash smear cytology of pituitary granular cell tumor: A case report and review of literature with special emphasis on cytological differential diagnosis in pituitary region

Neurohypophysis granular cell tumor (NGCT) is a rare entity and is classified under thyroid transcription factor 1 (TTF-1) expressing tumors of pituitary. It is considered as an uncommon differential during sellar and suprasellar mass evaluation. Its intraoperative squash cytology is distinct and has rarely been reported in literature. A 65-year-old female presented with reduced vision of right eye and history of seizures. Radiological findings revealed a sellar/suprasellar mass with mass effect on optic chiasma. Intraoperative squash neurocytology examination showed a spindle cell lesion with abundant granular cytoplasm in tumor cells. Subsequent histopathology and immunohistochemistry confirmed the diagnosis of granular cell tumor. Granular cell tumor remains one of the sellar/suprasellar surprises. Its intraoperative neurocytology is unique and should be considered while evaluating a sellar/suprasellar mass. A case of sellar granular cell tumor with its intraoperative squash cytology, histopathology along with a review of literature is being presented with special emphasis on cytological differential diagnosis in pituitary region.

Diagnostic yield of fluorescence-assisted frame-based stereotactic biopsies of intracerebral lesions in comparison with frozen-section analysis

PURPOSE

Stereotactic biopsies are routinely used to establish a histological diagnosis of unclear cerebral pathologies. Intraoperatively, frozen-section analysis often confirms diagnostic tissue but also exhibits methodological pitfalls. Intraoperative five-aminolevulinic acid (5-ALA)-fluorescence has been described not only in gliomas but also in other cerebral pathologies. In this study, we assessed the 5-ALA contribution to the intraoperative confirmation of diagnostic tissue in frame-based stereotactic biopsies of unclear intracerebral lesions in direct comparison with frozen-section analysis.

METHODS

Patients scheduled for stereotactic biopsies of unclear intracerebral pathologies received 5-ALA preoperatively. Obtained samples were intraoperatively analyzed for the presence of 5-ALA-fluorescence. One sample was used for frozen-section and a second one for permanent histopathological analysis. The diagnostic yield of frozen-section and intraoperative 5-ALA-fluorescence was calculated. The inclusion criteria for this retrospective analysis were unclear intracerebral lesions with inconclusive imaging findings and several differential diagnoses.

RESULTS

A total of 39 patients with 122 obtained specimens were included. The overall diagnostic yield was 92.3%. 5-ALA-positive samples were obtained in 74.3% (29/39) of patients and all these samples contained diagnostic tissue. 5-ALA-fluorescence confirmed diagnostic tissue with a sensitivity of 100%, a specificity of 27%, a positive predictive value (PPV) of 78%, and a negative predictive value (NPV) of 100%. A clear diagnosis could be predicted by frozen section with a sensitivity of 80%, a specificity of 100%, a PPV of 100%, and NPV of 30%; Fisher's exact test p = 0.01.

CONCLUSION

The 5-ALA-fluorescence in stereotactic biopsies of unclear intracerebral pathologies exhibits a high PPV/NPV for intraoperative confirmation of diagnostic tissue and might increase the diagnostic yield of the procedure by overcoming some of the limitations of frozen-section.

Differentiating the pathological subtypes of primary lung cancer for patients with brain metastases based on radiomics features from brain CT images

OBJECTIVES

It is of high clinical importance to identify the primary lesion and its pathological types for patients with brain metastases (BM). The purpose of this study is to investigate the feasibility and accuracy of differentiating the primary adenocarcinoma (AD) and squamous cell carcinoma (SCC) of non-small-cell lung cancer (NSCLC) for patients with BM based on radiomics from brain contrast-enhanced computer tomography (CECT) images.

METHODS

A total of 144 BM patients (94 male, 50 female) were enrolled in this study with 102 with primary lung AD and 42 with SCC, respectively. Radiomics features from manually contoured tumors were extracted using python. Mann-Whitney U test and the least absolute shrinkage and selection operator (LASSO) logistic regression were applied to select relative radiomics features. Binary logistic regression and support vector machines (SVM) were applied to build models with radiomics features alone and with radiomics features plus age and sex.

RESULTS

Fourteen features were selected from a total of 105 radiomics features for the final model building. The area under the curves (AUCs) and accuracy of SVM and binary logistic regression models were 0.765 vs. 0.769, 0.795 vs.0.828, and 0.716 vs. 0.726, 0.768 vs. 0.758, respectively, for models with radiomics features alone and models with radiomics features plus sex and age.

CONCLUSIONS

Brain CECT radiomics are promising in differentiating primary AD and SCC to achieve optimal therapeutic management in patients with BM from NSCLC.

KEY POINTS

• It is of high clinical importance to identify the primary lesion and its pathological types for patients with brain metastases (BM) to define the prognosis and treatment. • Few studies had investigated the feasibility and accuracy of differentiating the pathological subtypes of primary non-small-cell lung cancer between adenocarcinoma (AD) and squamous cell carcinoma (SCC) for patients with BM based on radiomics from brain contrast-enhanced CT (CECT) images, although CECT images are often the initial imaging modality to screen for metastases and are recommended on equal footing with MRI for the detection of cerebral metastases. • Brain CECT radiomics are promising in differentiating primary AD and SCC to achieve optimal therapeutic management in patients with BM from NSCLC with a highest area under the curve (AUC) of 0.828 and an accuracy of 0.758, respectively.

Provision of rapid and specific ex vivo diagnosis of central nervous system lymphoma from rodent xenograft biopsies by a fluorescent aptamer

OBJECTIVE

Differentiating central nervous system (CNS) lymphoma from other intracranial malignancies remains a clinical challenge in surgical neuro-oncology. Advances in clinical fluorescence imaging contrast agents and devices may mitigate this challenge. Aptamers are a class of nanomolecules engineered to bind cellular targets with antibody-like specificity in a fraction of the staining time. Here, the authors determine if immediate ex vivo fluorescence imaging with a lymphoma-specific aptamer can rapidly and specifically diagnose xenografted orthotopic human CNS lymphoma at the time of biopsy.

METHODS

The authors synthesized a fluorescent CNS lymphoma-specific aptamer by conjugating a lymphoma-specific aptamer with Alexa Fluor 488 (TD05-488). They modified human U251 glioma cells and Ramos lymphoma cells with a lentivirus for constitutive expression of red fluorescent protein and implanted them intracranially into athymic nude mice. Three to 4 weeks postimplantation, acute slices (biopsies, n = 28) from the xenografts were collected, placed in aptamer solution, and imaged with a Zeiss fluorescence microscope. Three aptamer staining concentrations (0.3, 1.0, and 3.0 μM) and three staining times (5, 10, and 20 minutes) followed by a 1-minute wash were tested. A file of randomly selected images was distributed to neurosurgeons and neuropathologists, and their ability to distinguish CNS lymphoma from negative controls was assessed.

RESULTS

The three staining times and concentrations of TD05-488 were tested to determine the diagnostic accuracy of CNS lymphoma within a frozen section time frame. An 11-minute staining protocol with 1.0-μM TD05-488 was most efficient, labeling 77% of positive control lymphoma cells and less than 1% of negative control glioma cells (p < 0.001). This protocol permitted clinicians to positively identify all positive control lymphoma images without misdiagnosing negative control images from astrocytoma and normal brain.

CONCLUSIONS

Ex vivo fluorescence imaging is an emerging technique for generating rapid histopathological diagnoses. Ex vivo imaging with a novel aptamer-based fluorescent nanomolecule could provide an intraoperative tumor-specific diagnosis of CNS lymphoma within 11 minutes of biopsy. Neurosurgeons and neuropathologists interpreted images generated with this molecular probe with high sensitivity and specificity. Clinical application of TD05-488 may permit specific intraoperative diagnosis of CNS lymphoma in a fraction of the time required for antibody staining.

Intraoperative Imprint-squash Methods in Central Nervous System Tumors

OBJECTIVES

Central nervous system (CNS) tumors constitute 1.3% of all cancers in adults and are the seventh leading cause of death in developed countries. CNS tumors are very soft and have a gelatin-like texture. Smear technique is a very simple and fast method for the diagnosis of brain tumors.

METHODS

In this study, we evaluated the imprint and squash cytology of 100 cases sent to the pathology clinic. The sections of the paraffin blocks were prepared after the operation in the neurosurgery clinic of the SBU Hamidiye Şişli Efal Training and Research Hospital. The accuracy rate was 90% in the differential diagnosis of malignant tumors from the benign ones.

CONCLUSION

Cytological samples were taken from 100 cases of intracranial tumors that were operated in the neurosurgery clinic of Şişli Etfal Hospital, and the paraffin sections prepared from the biopsy materials were examined. The cases with misdiagnosis were usually differentiated from solid-hard tumors, epithelial-grade cystic structures, and medulloblastoma localized in the posterior fossa, medulloblastoma and ependymoma. However, this method has been found to be very convenient in practice due to its ease technically, low cost and equipment savings.

Utility of Squash Cytology in Spinal Lesions with Special Reference to Ki67 Immunostain

BACKGROUND

Squash cytology is of significant importance in intraoperative consultation of central nervous system (CNS) pathology. There are several studies on squash cytology of CNS lesions, and only a few of them deal with spinal lesions alone.

AIMS

(1) To evaluate intraoperative squash cytology of spinal lesions. (2) To correlate cytological diagnosis with histopathological diagnosis and assess the diagnostic accuracy. (3) To study Ki67 expression on squash smears and determine whether it can assist in grading spinal tumours on cytology.

MATERIALS AND METHODS

A prospective study was conducted on 68 patients with clinico-radiologically diagnosed lesions of the spine. Intraoperative squash smears were stained with haematoxylin-eosin (H&amp;E) stain, Papanicolaou (Pap) stain, and May-Grünwald-Giemsa (MGG) stain. Subsequently, histological diagnosis was made. Ki67 immunostaining was performed on squash smears and histology sections.

RESULTS

The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of squash cytology in spinal lesions were 84.6, 100, 100, 23.1, and 80.88%, respectively. On immunocytochemistry, the mean Ki67 labelling indices for grade I, II, and III tumours were 0, 0.33 and 9%, respectively.

CONCLUSION

Squash smear cytology is a rapid intraoperative technique for diagnosing spinal lesions, with high specificity and high positive predictive value. It is more effective in diagnosing neoplasms than non-neoplastic lesions. Ki67 immunostaining can be done on cytology smears to effectively differentiate between WHO grade I and grade II spinal tumours.

Texture Analysis in Cerebral Gliomas: A Review of the Literature

Texture analysis is a continuously evolving, noninvasive radiomics technique to quantify macroscopic tissue heterogeneity indirectly linked to microscopic tissue heterogeneity beyond human visual perception. In recent years, systemic oncologic applications of texture analysis have been increasingly explored. Here we discuss the basic concepts and methodologies of texture analysis, along with a review of various MR imaging texture analysis applications in glioma imaging. We also discuss MR imaging texture analysis limitations and the technical challenges that impede its widespread clinical implementation. With continued advancement in computational processing, MR imaging texture analysis could potentially develop into a valuable clinical tool in routine oncologic imaging.

Accuracy of Intraoperative Examination in Central Nervous System Lesions: A Study of 133 Cases

OBJECTIVE

Intraoperative examination is a highly valuable tool for the evaluation of central nervous system (CNS) lesions, helping the neurosurgeon to determine the best surgical management. This study aimed to evaluate the accuracy and to analyze the diagnostic disagreements and pitfalls of the intraoperative examinations through correlation with the final histopathological diagnosis in CNS lesions.

STUDY DESIGN

Retrospective analysis of intraoperative examination of CNS lesions and their final diagnosis obtained during 16 consecutive years. All diagnoses were reviewed and classified according to World Health Organization (WHO) grading for CNS tumors. Squash was performed in 119 cases, while frozen section and both methods were done in 7 cases each.

RESULTS

Among the 133 intraoperative examinations considered, 114 (85.7%) presented concordance and 19 (14.3%) diagnostic disagreement when compared with subsequent histopathological examinations. The sensitivity and specificity for the detection of neoplasia in intraoperative examination was 98 and 94%, respectively. The positive and negative predictive values were 99 and 88%, respectively. The accuracy for neoplastic and nonneoplastic disease was 85.7%. Disagreements were more frequent among low-grade (WHO grades I and II) neoplasms and nonmalignant cases.

CONCLUSIONS

Our results showed good accuracy of the intraoperative assessments for diagnosis of CNS lesions, particularly in high-grade (grades III and IV) lesions and metastatic neoplasms.

Diagnostic Accuracy of Cytology Smear and Frozen Section in Glioma

Glioma is the commonest primary intracranial tumour and it has been the most predominant tumour in many studies. It accounts for 24.7% of all primary brain tumour and 74.6% of malignant brain tumour. Intraoperative diagnosis plays a crucial role in determining the patient management. Frozen section has been the established technique in providing rapid and accurate intraoperative diagnosis. However due to some disadvantages like ice crystal artefact, high expenditure and requirement of skilled technician, there is increase usage of cytology smear either replacing or supplementing frozen section technique. The aim of this review is to determine the diagnostic accuracy of cytology smear and frozen section in glioma and to see whether there is significant difference between those techniques. The overall diagnostic accuracy for frozen section in glioma ranging from 78.4% to 95% while for cytology smear, the diagnostic accuracy ranging from 50% to 100%. Based on certain literatures, no statistically difference was observed in diagnostic accuracy of cytology smear and frozen section. Thus, cytology smear provides an alternative method in establishing intraoperative diagnosis. Both cytology smear and frozen section are complimentary to each other. It is recommended to use both techniques to improve the diagnostic accuracy in addition with adequate knowledge, clinical history, neuroimaging and intraoperative findings.

Intraoperative Frozen Cytology of Central Nervous System Neoplasms: An Ancillary Tool for Frozen Diagnosis

BACKGROUND

Pathologic diagnosis of central nervous system (CNS) neoplasms is made by comparing light microscopic, immunohistochemical, and molecular cytogenetic findings with clinicoradiologic observations. Intraoperative frozen cytology smears can improve the diagnostic accuracy for CNS neoplasms. Here, we evaluate the diagnostic value of cytology in frozen diagnoses of CNS neoplasms.

METHODS

Cases were selected from patients undergoing both frozen cytology and frozen sections. Diagnostic accuracy was evaluated.

RESULTS

Four hundred and fifty-four cases were included in this retrospective single-center review study covering a span of 10 years. Five discrepant cases (1.1%) were found after excluding 53 deferred cases (31 cases of tentative diagnosis, 22 cases of inadequate frozen sampling). A total of 346 cases of complete concordance and 50 cases of partial concordance were classified as not discordant cases in the present study. Diagnostic accuracy of intraoperative frozen diagnosis was 87.2%, and the accuracy was 98.8% after excluding deferred cases. Discrepancies between frozen and permanent diagnoses (n = 5, 1.1%) were found in cases of nonrepresentative sampling (n = 2) and misinterpretation (n = 3). High concordance was observed more frequently in meningeal tumors (97/98, 99%), metastatic brain tumors (51/52, 98.1%), pituitary adenomas (86/89, 96.6%), schwannomas (45/47, 95.8%), high-grade astrocytic tumors (47/58, 81%), low grade astrocytic tumors (10/13, 76.9%), non-neoplastic lesions (23/36, 63.9%), in decreasing frequency.

CONCLUSIONS

Using intraoperative cytology and frozen sections of CNS tumors is a highly accurate diagnostic ancillary method, providing subtyping of CNS neoplasms, especially in frequently encountered entities.

Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis

BACKGROUND

Differentiation between glioblastoma and brain metastasis is highly important due to differing medical treatment strategies. While MRI is the modality of choice for the assessment of patients with brain tumors, differentiation between glioblastoma and solitary brain metastasis may be challenging due to their similar appearance on MRI.

PURPOSE

To differentiate between glioblastoma and brain metastasis subtypes using radiomics analysis based on conventional post-contrast T₁ -weighted (T₁ W) MRI.

STUDY TYPE

Retrospective.

SUBJECTS

Data were acquired from 439 patients: 212 patients with glioblastoma and 227 patients with brain metastasis (breast, lung, and others).

FIELD STRENGTH/SEQUENCE

Post-contrast 3D T₁ W gradient echo images, acquired with 1.5 and 3.0 T MR systems.

ASSESSMENT

Analysis included image preprocessing, segmentation of tumor area, and features extraction including: patients' clinical information, tumor location, first- and second-order statistical, morphological, wavelet features, and bag-of-features. Following dimension reduction, classification was performed using various machine-learning algorithms including support-vector machine (SVM), k-nearest neighbor, decision trees, and ensemble classifiers.

STATISTICAL TESTS

For classification, the data were divided into training (80%) and testing datasets (20%). Following optimization of the classifiers, mean sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated.

RESULTS

For the testing dataset, the best results for differentiation of glioblastoma from brain metastasis were obtained using the SVM classifier with mean accuracy = 0.85, sensitivity = 0.86, specificity = 0.85, and AUC = 0.96. The best classification results between glioblastoma and brain metastasis subtypes were obtained using SVM classifier with mean accuracy = 0.85, 0.89, 0.75, 0.90; sensitivity = 1.00, 0.60, 0.57, 0.11; specificity = 0.76, 0.92, 0.87, 0.99; and AUC = 0.98, 0.81, 0.83, 0.57 for the glioblastoma, breast, lung, and other brain metastases, respectively.

DATA CONCLUSION

Differentiation between glioblastoma and brain metastasis showed a high success rate based on postcontrast T₁ W MRI. Classification between glioblastoma and brain metastasis subtypes may require additional MR sequences with other tissue contrasts.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:519-528.

Isolated Tuberculoma Mimicking Foramen Magnum Meningioma in the Absence of Primary Tuberculosis: A Case Report

Central nervous system tuberculosis is a devastating complication of systemic tuberculosis. Intradural extramedullary (IDEM) tuberculoma at the foramen magnum is rare, and mimics en plaque meningioma. We report the case of a 53-year-old woman who presented with dysesthesia of the tongue and lower cranial nerve (CN) palsy, with onset 4 months prior to admission. The neurologic examination revealed left upper-limb weakness and hypoesthesia on the sole and dorsum of the left foot. Other physical examinations revealed no features of tubercular infection. Laboratory investigations likewise showed no signs of infection or inflammation. Magnetic resonance imaging of the brain showed an IDEM mass originating from the left intradural surface at the foramen magnum extending to the C2 segment and compressing the brainstem and upper cervical cord. The mass was isointense/hypointense on T1- and T2-weighted images and homogeneously-enhanced on postcontrast images. The lesion also exhibited the dural-tail sign and was preoperatively diagnosed as en plaque meningioma. The patient underwent surgery via the left transcondylar fossa approach with partial laminectomy of the atlas. Intraoperatively, the mass exhibited a dural origin and encased the vertebral artery and lower CNs, with strong adhesions. While the histopathological study of the mass was strongly suggestive of tuberculoma with multifocal granulomas, caseous necrosis, and Langerhans giant cells, extensive diagnostic studies failed to detect Mycobacterium tuberculosis itself. Although the patient had recurrence with multisystem involvement, she responded well to antitubercular treatment. IDEM tuberculoma of the foramen magnum may present as en plaque meningioma. Histopathology is required for a definitive diagnosis. Prompt surgical resection and decompression with adequate antitubercular treatment yield better neurological outcomes.