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Implementation and experimental evaluation of Mega-voltage fan-beam CT using a linear accelerator.
Hao Gong1, Shengzhen Tao1, Justin D Gagneur2
1Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Radiation Oncology (London, England)
|July 29, 2021
Summary
Mega-voltage fan-beam CT (MV-FBCT) shows promise for accurate relative electron density (RED) and proton stopping power ratio (SPR) determination. This study demonstrates the feasibility of MV-FBCT using a medical linear accelerator, improving RED estimation accuracy compared to conventional CT.
Area of Science:
- Medical Physics
- Radiological Imaging
- Radiation Therapy Physics
Background:
- Mega-voltage fan-beam Computed Tomography (MV-FBCT) offers potential for precise relative electron density (RED) and proton stopping power ratio (SPR) determination.
- However, MV-FBCT is not yet widely implemented in clinical practice.
Purpose of the Study:
- To demonstrate the feasibility of implementing MV-FBCT using a medical linear accelerator (LINAC) with a 2.5 MV imaging beam.
- To evaluate the accuracy of RED estimation using MV-FBCT compared to conventional CT.
Main Methods:
- Utilized multileaf collimators (MLCs) to collimate a 2.5 MV MV beam into a 1 cm fan-beam.
- Acquired projection data within one gantry rotation, applying in-house artifact correction algorithms.
- Established Hounsfield Unit (HU) to RED calibration curves using a CIRS phantom with tissue-mimicking inserts, comparing results with kilovoltage CT (TP-CT).
Main Results:
- In-house algorithms effectively reduced artifacts like ring and cupping.
- MV-FBCT demonstrated superior prediction accuracy for HU-RED calibration curves (R² > 0.9994) compared to TP-CT (R² < 0.9990).
- MV-FBCT accurately measured CT numbers for blood-iodine inserts, unlike TP-CT, and dose reduction to 30 MU did not impact accuracy.
Conclusions:
- Successfully demonstrated the feasibility of MV-FBCT using a LINAC, EPID, and MLCs.
- MV-FBCT shows significant potential for more accurate RED estimation in radiological imaging and radiation therapy planning.

