Mohamed Eldesouky

Mr. Mohamed Eldesouky


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 January 2026 in Cancers
Verified
Journal Article
Open access
PDF file
Walid ShaalanWalid Shaalan
Walid Shaalan
MEMohamed Eldesouky
Mohamed Eldesouky
TMTheresa Mokry
Theresa Mokry
ABArved Bischoff
Arved Bischoff
Hans-Peter SinnHans-Peter Sinn
Hans-Peter Sinn
Fabian RiedelFabian Riedel
Fabian Riedel
Background: Accurate intraoperative assessment of sentinel lymph node (SLN) status is critical for staging and guiding surgical management in gynaecological malignancies. Frozen-section histopathology remains the gold standard, but it is time-consuming and resource-intensive. Shear-wave elastography (SWE) quantifies tissue stiffness in real time and may offer a rapid alternative. Methods: In this prospective single-centre study, 63 women (median age 62 years) undergoing primary surgery with sentinel lymph node biopsy (SLNB) for endometrial, cervical, vulvar, or early ovarian carcinoma were enrolled. A total of 172 SLNs were excised, submerged in coupling gel, and scanned ex vivo using a 9 MHz linear probe. Results: A total of 172 SLNs underwent SWE (mean 2.7 nodes/patient). Endometrial primaries accounted for 58% of nodes, mostly retrieved by robotic-assisted surgery (71.8%). Node dimensions were significantly larger in malignant lesions for sonographic (long-axis: 13.02 ± 3.31 mm vs. 10.80 ± 3.28 mm; p = 0.002) and pathological long-axis measurements (11.45 ± 2.83 mm vs. 9.75 ± 2.61 mm; p = 0.004). Mean SWE velocities were similar between groups (1.381 ± 0.307 vs. 1.343 ± 0.236 m/s; p = 0.541). Histopathology identified metastases in 18% of SLNs, comprising macrometastases (7%), micrometastases (5%), and isolated tumour cells (6%). Conclusions: Although ex vivo SWE is rapid, reproducible, and integrates seamlessly into the sterile field, stiffness measurements alone lack sufficient discriminatory power for SLN staging in gynaecological cancers. Future research should focus on three-dimensional SWE, advanced radiomic analyses, and machine-learning algorithms to improve the detection of low-volume metastatic disease.