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CT texture analysis for differentiating between peritoneal carcinomatosis and peritoneal tuberculosis: a
Muhammad Awais1, Noman Khan2, Ayimen Khalid Khan2
1Department of Radiology, Aga Khan University Hospital, Stadium Road, P.O. Box 3500, Karachi, 74800, Sindh, Pakistan. awais_aku@yahoo.com.
Abdominal Radiology (New York)
|November 23, 2023
Summary
Computer tomography (CT) texture analysis can differentiate between peritoneal carcinomatosis (PC) and peritoneal tuberculosis (PTB) by examining omental lesions. Key differences in radiodensity, entropy, energy, homogeneity, and dissimilarity aid in distinguishing these conditions.
Area of Science:
- Radiology
- Oncology
- Infectious Diseases
Background:
- Peritoneal carcinomatosis (PC) and peritoneal tuberculosis (PTB) present similar clinical and imaging findings, complicating diagnosis.
- Accurate differentiation is crucial for appropriate patient management and treatment strategies.
Purpose of the Study:
- To investigate if computed tomography (CT) textural parameters of omental lesions differ between patients with PC and PTB.
- To assess the potential of CT texture analysis in distinguishing between these two challenging conditions.
Main Methods:
- Retrospective analysis of 66 patients with histologically confirmed PC (38) or PTB (28).
- Extraction of radiomic features from omental lesions using LIFEx software on contrast-enhanced CT scans.
- Statistical comparison of CT texture parameters, including radiodensity, entropy, energy, GLCM homogeneity, and dissimilarity, between the PC and PTB groups.
Main Results:
- Omental lesions in PC showed significantly higher mean radiodensity (+32.4), entropy (+0.11), and GLCM dissimilarity (+0.480) compared to PTB.
- Conversely, PC lesions exhibited lower mean energy (-0.024) and GLCM homogeneity (-0.073) than PTB lesions.
- All observed differences were statistically significant (p < 0.001).
Conclusions:
- CT texture parameters of omental lesions are significantly different between patients with PC and PTB.
- These quantitative imaging features hold promise as a tool to aid clinicians in differentiating between PC and PTB, potentially improving diagnostic accuracy.
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