Role of Sonoelastography in Evaluation of Lymph Node Metastasis in Head and Neck Keeping Histopathology as Gold Standard

Objective: To determine the diagnostic accuracy of sonoelastography in the evaluation of lymph node metastasis in head and neck cancer, using histopathology as the gold standard. Research Design: A study of cross-sectional validation. Duration and Place of Study: This research was carried out in the Diagnostic Radiology Department, Shaikh Zayed Hospital, Lahore, from May 2024 to November 2024. Methodology: A total of 138 patients aged 18 to 70 years, with enlarged cervical lymph nodes (≥1 cm), were included. Participants were evaluated using sonoelastography, a high-resolution ultrasound-based technique, performed by an experienced radiologist. Elastographic tissue stiffness was scored from 1 to 4, with scores 1 and 2 indicating benign nodes and scores 3 and 4 indicating malignancy. The reference standard for biopsy sample analysis was histopathological analysis. The following metrics were computed: diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: The mean age of participants was 55.19 ± 5.67 years, with a mean lymph node size of 2.16 ± 0.22 cm. Sonoelastography identified 38.4% of lymph nodes as malignant and 61.6% as benign, compared to histopathological findings of 30.4% malignant and 69.6% benign. Diagnostic performance metrics for sonoelastography included sensitivity of 86%, specificity of 82%, PPV of 68%, NPV of 93%, and an overall diagnostic accuracy of 83%. Conclusion: Sonoelastography demonstrates high sensitivity and diagnostic accuracy in evaluating cervical lymph nodes, making it a valuable, non-invasive adjunct to conventional imaging methods.

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Publication Details

Journal
Indus journal of bioscience research.
Published
2025-05-18
DOI
https://doi.org/10.70749/ijbr.v3i5.1086
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Role of Sonoelastography in Evaluation of Lymph Node Metastasis in Head and Neck Keeping Histopathology as Gold Standard

Sidra Javed, Muhammad Awais Javed, Abdullah Javed, Humera Mahmood et al.
Indus journal of bioscience research.
Radiomics and Machine Learning in Medical Imaging
article

Role of Sonoelastography in Evaluation of Lymph Node Metastasis in Head and Neck Keeping Histopathology as Gold Standard

Sidra Javed, Muhammad Awais Javed, Abdullah Javed, Humera Mahmood, Saulat Sarfraz, Nawal Naseem
article en

Abstract

Objective: To determine the diagnostic accuracy of sonoelastography in the evaluation of lymph node metastasis in head and neck cancer, using histopathology as the gold standard. Research Design: A study of cross-sectional validation. Duration and Place of Study: This research was carried out in the Diagnostic Radiology Department, Shaikh Zayed Hospital, Lahore, from May 2024 to November 2024. Methodology: A total of 138 patients aged 18 to 70 years, with enlarged cervical lymph nodes (≥1 cm), were included. Participants were evaluated using sonoelastography, a high-resolution ultrasound-based technique, performed by an experienced radiologist. Elastographic tissue stiffness was scored from 1 to 4, with scores 1 and 2 indicating benign nodes and scores 3 and 4 indicating malignancy. The reference standard for biopsy sample analysis was histopathological analysis. The following metrics were computed: diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: The mean age of participants was 55.19 ± 5.67 years, with a mean lymph node size of 2.16 ± 0.22 cm. Sonoelastography identified 38.4% of lymph nodes as malignant and 61.6% as benign, compared to histopathological findings of 30.4% malignant and 69.6% benign. Diagnostic performance metrics for sonoelastography included sensitivity of 86%, specificity of 82%, PPV of 68%, NPV of 93%, and an overall diagnostic accuracy of 83%. Conclusion: Sonoelastography demonstrates high sensitivity and diagnostic accuracy in evaluating cervical lymph nodes, making it a valuable, non-invasive adjunct to conventional imaging methods.

Indus journal of bioscience research.Vol. 3(5)
Allama Iqbal Medical College (PK), Shaikh Zayed Hospital (PK), Army Medical College (PK)
Openalex Percentile: Top 84%
Radiomics and Machine Learning in Medical Imaging
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