Intraoperative Squash Smear in Central Nervous System Tumors and Its Correlation with Histopathology: 1 Year Study at a Tertiary Care Centre

Jindal, Ankur; Diwan, Himanshi; Kaur, Kanwalpreet; Sinha, Virendra Deo

doi:10.4103/0976-3147.203811

Cited by 10 publications

(19 citation statements)

References 9 publications

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“…A speci c study diagnosing malignant vs non-malignant breast cancer based on Computer-aided histological diagnosis could achieve an accuracy of 88.3%. [14] In the present study, sensitivity for detection of high-grade glioma and low-grade glioma by CNN AI agent was 91% and 77% which were comparable to conventional detection methods by human pathologists (83-95%) 6,11 and 77-80% [15] in various studies.…”

Section: Discussionsupporting

confidence: 66%

“…Images in the training set were only used to train the network and the rest of the images were only used for validation/testing. Of the total 10,000 images collected, 6,000 belonged to High Grade Glioma and 4,000 belonged to Low Grade Glioma. Amongst them, 3,200 were used for training and rest for testing/validation.…”

Section: Image Acquisition and Data Collectionmentioning

confidence: 99%

“…[6] Diagnostic accuracies of squash smears range from 76 -96 % in different studies. [6] Typically, this procedure takes around 30 minutes to 2 hours at various centers. At our center the typical turnaround time for diagnosis is in-between 30 to 45 mins.…”

Section: Introductionmentioning

confidence: 99%

“…Intraoperative squash smear cytological preparation was rst introduced by Eisenhardt and Cushing in the early 1930 and Badt in 1937. [6] Diagnostic accuracies of squash smears range from 76 -96 % in different studies. [6] Typically, this procedure takes around 30 minutes to 2 hours at various centers.…”

Section: Introductionmentioning

confidence: 99%

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Deep Learning Use for Differentiation of Low-grade vs High-Grade Glioma in Intraoperative Squash Smears

Thombre

Nandeesh

Vazhayil

et al. 2021

Preprint

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ObjectiveAutomated diagnosis using Artificial Intelligence (AI) techniques would be a useful addition to the intraoperative squash smear diagnosis. A robust diagnostic tool would enhance capabilities in centres where there is limited expertise for the diagnosis of intracranial lesions. The study aims to explore possibilities of deep learning technique-based models to classify squash smear images of glioma into high- and low-grade tumors.Methods500 Scanned images of squash smear were obtained intraoperatively and dataset was built. Image dataset was then pre-processed and fed into a CNN (Convolutional Neural Network) model for training and validation. The dataset consisted of 10,000 images of high (6000) and low (4000) grade gliomas, divided into three sets of training, validation and testing. ResultsCNN model based on deep learning algorithm was built and trained on training dataset to get accuracy of 96.2%. On a testing dataset which contains images previously unseen by trained model, it could achieve accuracies of 91% for diagnosing high grade glioma and 77% for low grade glioma. A positive predictive value of 86.6% and F1-score of 0.887 was achieved. Feature visualization technique was applied at the end to visualize regions of interest.ConclusionDeep Learning techniques can be applied as diagnostic tool if proper standardized images are obtained for reporting of squash smears of gliomas. The diagnostic accuracies of such tools can reach up to current standard diagnostic accuracies by conventional ways of reporting. Feature visualization techniques applied which can be used for rapid screening of slides or section of slide to assist in rapid diagnosis.

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Section: Discussionsupporting

confidence: 66%

Section: Image Acquisition and Data Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deep Learning Use for Differentiation of Low-grade vs High-Grade Glioma in Intraoperative Squash Smears

Thombre

Nandeesh

Vazhayil

et al. 2021

Preprint

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“…Role of squash cytology in intraoperative diagnosis (IOD) of central nervous system (CNS) lesions has been well established. [1][2][3][4][5] Some centres use frozen section biopsy while some resort to both squash cytology and frozen section biopsy for higher diagnostic accuracy. [6][7][8][9] In resource constrained settings, often the only modality available for IOD is squash cytology.…”

Section: Introductionmentioning

confidence: 99%

Utility of intraoperative squash cytology in diagnosis of paediatric central nervous system lesions

Maity

Sengupta

Jain

et al. 2018

Diagnostic Cytopathology

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Background Role of squash cytology in intraoperative diagnosis of central nervous system lesions has been well established. Intraoperative diagnosis is especially important in paediatric CNS lesions as decision regarding gross total resection or near total resection or subtotal resection is crucial and radiotherapy and chemotherapy are best avoided in this age group. The aim of this study was to evaluate the utility of squash cytology of CNS lesions in paediatric age group and to assess its diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value. Materials and methods A prospective study was conducted on 42 paediatric patients with clinico‐radiologically diagnosed CNS lesions. Intraoperative squash smears were stained with haematoxylin and eosin (H&E) stain. Diagnosis made subsequently on paraffin sections was taken as gold standard. Results The overall diagnostic accuracy of intraoperative squash cytology of CNS lesions in paediatric age group was 73.80%. The sensitivity, specificity, positive predictive value and negative predictive value of this modality were 92.31%, 87.50%, 96.00% and 77.78%, respectively. Conclusions The spectrum of CNS lesions in paediatric age group is different from that in adults. Though the sensitivity and specificity of squash cytology in paediatric tumours are less than that of adults, it is an important tool for intraoperative diagnosis that guides regarding the extent of resection.

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A study of squash smear cytology in intraoperative diagnosis of CNS tumors and its histopathological correlation

Tejaswi¹,

Shirisha²,

D³

2020

IJPO

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Intra operative cytology is an important diagnostic modality especially central nervous system tumors. Squash smears most widely used cytological technique is rapid, accurate and relatively uses little tissue. It also helps the surgeon to plan the extent of surgery. To assess the accuracy of squash smear by comparing with the histopathological diagnosis. A study of 52 cases at our institute. Complete clinical, demographic and radiological findings were recorded. The smears were stained by rapid haematoxylin and eosin and toluidine blue stain. The cytomorphological features were studied and were compared with the tissue sections. Glial tumors formed the largest category of tumors constitutes 40.3%. A total 47 cases showed complete concordance with histodiagnosis with a diagnostic accuracy of 95.9%. Conclusion: Squash smear cytology proved to be a simple, inexpensive, rapid intraoperative neuropathological technique particularly useful in astrocytomas.

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Intraoperative Squash Smear in Central Nervous System Tumors and Its Correlation with Histopathology: 1 Year Study at a Tertiary Care Centre

Cited by 10 publications

References 9 publications

Deep Learning Use for Differentiation of Low-grade vs High-Grade Glioma in Intraoperative Squash Smears

Deep Learning Use for Differentiation of Low-grade vs High-Grade Glioma in Intraoperative Squash Smears

Utility of intraoperative squash cytology in diagnosis of paediatric central nervous system lesions

A study of squash smear cytology in intraoperative diagnosis of CNS tumors and its histopathological correlation

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