Can laboratory x-ray virtual histology provide intraoperative 3D tumor resection margin assessment?
William TwengströmCarlos F MoroJenny RomellJakob C LarssonErnesto SparrelidMikael BjörnstedtHans Martin HertzPublished in: Journal of medical imaging (Bellingham, Wash.) (2022)
Purpose: Surgery is an essential part of the curative plan for most patients affected with solid tumors. The outcome of such surgery, e.g., recurrence rates and ultimately patient survival, depends on several factors where the resection margin is of key importance. Presently, the resection margin is assessed by classical histology, which is time-consuming (several days), destructive, and basically only gives two-dimensional information. Clearly, it would be advantageous if immediate feedback on tumor extension in all three dimensions were available to the surgeon intraoperatively. Approach: We investigate a laboratory propagation-based phase-contrast x-ray computed tomography system that provides the resolution, the contrast, and, potentially, the speed for this purpose. The system relies on a liquid-metal jet microfocus source and a scintillator-coated CMOS detector. Our study is performed on paraffin-embedded non-stained samples of human pancreatic neuroendocrine tumors, liver intrahepatic cholangiocarcinoma, and pancreatic serous cystic neoplasm (benign). Results: We observe tumors with distinct and sharp edges having cellular resolution ( ∼ 10 μ m ) as well as many assisting histological landmarks, allowing for resection margin assessment. All x-ray data are compared with classical histology. The agreement is excellent. Conclusion: We conclude that the method has potential for intraoperative three-dimensional virtual histology.
Keyphrases
- dual energy
- computed tomography
- minimally invasive
- high resolution
- neuroendocrine tumors
- end stage renal disease
- coronary artery bypass
- magnetic resonance
- prognostic factors
- contrast enhanced
- newly diagnosed
- endothelial cells
- chronic kidney disease
- patients undergoing
- magnetic resonance imaging
- ejection fraction
- positron emission tomography
- single molecule
- healthcare
- electronic health record
- image quality
- surgical site infection
- big data
- free survival
- high frequency
- coronary artery disease
- low grade
- ionic liquid
- patient reported outcomes
- deep learning