Iterative reconstruction with boundary detection for carbon ion computed tomography

Deepak Shrestha, Nan Qin, You Zhang, Faraz Kalantari, Shanzhou Niu, Xun Jia, Arnold Pompos, Steve Jiang, Jing Wang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In heavy ion radiation therapy, improving the accuracy in range prediction of the ions inside the patient's body has become essential. Accurate localization of the Bragg peak provides greater conformity of the tumor while sparing healthy tissues. We investigated the use of carbon ions directly for computed tomography (carbon CT) to create the relative stopping power map of a patient's body. The Geant4 toolkit was used to perform a Monte Carlo simulation of the carbon ion trajectories, to study their lateral and angular deflections and the most likely paths, using a water phantom. Geant4 was used to create carbonCT projections of a contrast and spatial resolution phantom, with a cone beam of 430 MeV/u carbon ions. The contrast phantom consisted of cranial bone, lung material, and PMMA inserts while the spatial resolution phantom contained bone and lung material inserts with line pair (lp) densities ranging from 1.67 lp cm-1 through 5 lp cm-1. First, the positions of each carbon ion on the rear and front trackers were used for an approximate reconstruction of the phantom. The phantom boundary was extracted from this approximate reconstruction, by using the position as well as angle information from the four tracking detectors, resulting in the entry and exit locations of the individual ions on the phantom surface. Subsequent reconstruction was performed by the iterative algebraic reconstruction technique coupled with total variation minimization (ART-TV) assuming straight line trajectories for the ions inside the phantom. The influence of number of projections was studied with reconstruction from five different sets of projections: 15, 30, 45, 60 and 90. Additionally, the effect of number of ions on the image quality was investigated by reducing the number of ions/projection while keeping the total number of projections at 60. An estimation of carbon ion range using the carbonCT image resulted in improved range prediction compared to the range calculated using a calibration curve.

Original languageEnglish (US)
Article number055002
JournalPhysics in Medicine and Biology
Volume63
Issue number5
DOIs
StatePublished - Feb 26 2018

Fingerprint

Carbon
Tomography
Ions
Heavy Ion Radiotherapy
Bone and Bones
Lung
Polymethyl Methacrylate
Calibration
Water
Neoplasms

Keywords

  • ART-TV
  • boundary detection
  • carbon computed tomography (carbon CT)
  • Geant4
  • Monte Carlo simulation

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

Cite this

Iterative reconstruction with boundary detection for carbon ion computed tomography. / Shrestha, Deepak; Qin, Nan; Zhang, You; Kalantari, Faraz; Niu, Shanzhou; Jia, Xun; Pompos, Arnold; Jiang, Steve; Wang, Jing.

In: Physics in Medicine and Biology, Vol. 63, No. 5, 055002, 26.02.2018.

Research output: Contribution to journalArticle

Shrestha, Deepak ; Qin, Nan ; Zhang, You ; Kalantari, Faraz ; Niu, Shanzhou ; Jia, Xun ; Pompos, Arnold ; Jiang, Steve ; Wang, Jing. / Iterative reconstruction with boundary detection for carbon ion computed tomography. In: Physics in Medicine and Biology. 2018 ; Vol. 63, No. 5.
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