SU-E-I-58: Detecting Tumors with Extremely Low Contrast in CT Images

Authors


Abstract

Purpose:

Tumors such as the prostate focal lesions and the brain metastases have extremely low CT contrast and MRI is usually used for target delineation. The target contours are propagated to the CT for treatment planning and patient positioning. We have employed an advanced denoising method eliminating the noise and allow magnification of subtle contrast of these focal lesions on CT.

Methods:

Five prostate and two brain metastasis patients with MRI T2, diffusion or dynamic contrast enhanced (DCE) images confirmed focal lesions were included. One brain patients had 5 metastases. A block matching 3D (BM3D) algorithm was adapted to reduce the noise of kVCT images used for treatment planning. The gray-level range of the resultant images was narrowed to magnify the tumor-normal tissue contrast.

Results:

For the prostate patients, denoised kVCT images showed focal regions at 5, 8,11-1, 2, and 8–10 oclock for the 5 patients, this is highly consistent to the radiologist confirmed focal lesions based on MRI at 5, 7, 11-1, 2 and 8–10 oclock in the axial plane. These CT focal regions matched well with the MRI focal lesions in the cranio-caudal position. The average increase in density compared to background prostate glands was 0.86%, which corresponds to ∼50% increase in cellularity and is lower than the average CT noise level of 2.4%. For the brain patients, denoised kVCT showed 5/6 metastases. The high CT-density region of a metastasis is 2-mm off from its corresponding elevated MRI perfusion center. Overall the detecting sensitivity was 91%.

Conclusion:

It has been preliminarily demonstrated that the higher tumor cellularity can be detected using kVCT. The low contrast-to-noise information requires advanced denoising to reveal. The finding is significant to radiotherapy by providing an additional tool to locate focal lesions for confirming MRI-CT registration and providing a highly accessible outcome assessment tool.

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