Related Experiment Video
Updated: Jun 19, 2025
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In Vivo, Percutaneous, Needle Based, Optical Coherence Tomography of Renal Masses
Published on: March 30, 2015
8.9K
Tumor morphology evaluation using 3D-morphometric features of renal masses
Fiev Dmitry1, Sirota Evgeniy1, Kozlov Vasiliy2
1Institute for Urology and Human Reproductive Health, Sechenov University, Moscow, Russia.
Urologia
|July 26, 2024
Summary
This study correlates general and 3D imaging features of kidney tumors with their histology. A predictive equation using gender and tumor shape accurately assesses kidney malignancy risk.
Area of Science:
- Urology
- Radiology
- Oncology
Background:
- Renal tumors require accurate assessment for appropriate treatment.
- Distinguishing between benign and malignant renal masses preoperatively is crucial.
- Multidetector-row computed tomography (MSCT) and 3D modeling offer detailed tumor visualization.
Purpose of the Study:
- To correlate general (gender, age, tumor size) and 3D morphotopometric features of renal tumors with histological findings.
- To develop a predictive equation for kidney malignancy based on these features.
Main Methods:
- Analysis of 304 patients with unilateral solitary renal neoplasms.
- Preoperative contrast-enhanced MSCT and 3D tumor modeling.
- Evaluation of tumor morphotopometric features (side, location, surface, depth, shape) and histological structure.
Main Results:
- Out of 304 patients, 83.6% had malignant tumors.
- Malignant tumors were more common in men.
- Specific tumor shapes were associated with benign or malignant diagnoses.
- A logistic regression model was developed for malignancy prediction.
Conclusions:
- A predictive equation incorporating gender and tumor shape demonstrated 87.6% accuracy in predicting kidney tumor malignancy.
- This model aids in assessing the risk of kidney cancer.
