EVALUATION OF THE SPATIAL RESOLUTION IN MONTE CARLO-BASED SPECT/CT RECONSTRUCTION OF 111IN-OCTREOTIDE IMAGES

Feasibility of internal-source tracking with C-arm CT/SPECT imaging with limited-angle projection data for online in vivo dose verification in brachytherapy: A Monte Carlo simulation study

PURPOSE

The current protocol for use of the image-guided adaptive brachytherapy (IGABT) procedure entails transport of a patient between the treatment room and the 3-D tomographic imaging room after implantation of the applicators in the body, which movement can cause position displacement of the applicator. Moreover, it is not possible to track 3-D radioactive source movement inside the body, even though there can be significant inter- and intra-fractional patient-setup changes. In this paper, therefore, we propose an online single-photon emission computed tomography (SPECT) imaging technique with a combined C-arm fluoroscopy X-ray system and attachable parallel-hole collimator for internal radioactive source tracking of every source position in the applicator.

METHODS AND MATERIALS

In the present study, using Geant4 Monte Carlo (MC) simulation, the feasibility of high-energy gamma detection with a flat-panel detector for X-ray imaging was assessed. Further, a parallel-hole collimator geometry was designed based on an evaluation of projection image quality for a 192Ir point source, and 3-D limited-angle SPECT-image-based source-tracking performances were evaluated for various source intensities and positions.

RESULTS

The detector module attached to the collimator could discriminate the 192Ir point source with about 3.4% detection efficiency when including the total counts in the entire deposited energy region. As the result of collimator optimization, hole size, thickness, and length were determined to be 0.5, 0.2, and 45 mm, respectively. Accordingly, the source intensities and positions also were successfully tracked with the 3-D SPECT imaging system when the C-arm was rotated within 110° in 2 seconds.

CONCLUSIONS

We expect that this system can be effectively implemented for online IGABT and in vivo patient dose verification.

Evaluation of reconstruction methods and image noise levels concerning visual assessment of simulated liver lesions in 111In-octreotide SPECT imaging

BACKGROUND

Early cancer detection is crucial for patients' survival. The image quality in ¹¹¹In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-based ordered subset expectation maximization (OSEM) reconstruction compared to conventional attenuation-corrected OSEM reconstruction.

METHODS

Thirty-seven SPECT/CT examinations with ¹¹¹In-octreotide were randomly selected. The inclusion criterion was no liver lesions at the time of examination and for the following 3 years. SPECT images of spheres representing lesions were simulated using MC. The raw data of the spheres were added to the raw data of the established healthy patients in 26 of the examinations, and the remaining 11 examinations were not modified. The images were reconstructed using conventional OSEM reconstruction with attenuation correction and post filtering (fAC OSEM) and MC-based OSEM reconstruction without and with post filtering (MC OSEM and fMC OSEM, respectively). The images were visually and blindly evaluated by a nuclear medicine specialist. The criteria evaluated were liver lesion yes or no, including coordinates if yes, with confidence level 1-3. The percentage of detected lesions and accuracy (percentage of correctly classified cases), as well as tumor-to-normal tissue concentration (TNC) ratios and signal-to-noise ratios (SNRs), were evaluated.

RESULTS

The detection rates were 30.8% for fAC OSEM, 42.3% for fMC OSEM, and 50.0% for MC OSEM. The accuracies were 45.9% for fAC OSEM, 45.9% for fMC OSEM, and 54.1% for MC OSEM. The number of false positives was higher for fMC and MC OSEM. The observer's confidence level was higher in filtered images than in unfiltered images. TNC ratios were significantly higher, statistically, with MC OSEM and fMC OSEM than with AC OSEM, but SNRs were similar due to higher noise with MC OSEM.

CONCLUSION

One in two lesions were found using MC OSEM versus one in three using conventional reconstruction. TNC ratios were significantly improved, statistically, using MC-based reconstruction, but the noise levels increased and consequently the confidence level of the observer decreased. For further improvements, image noise needs to be suppressed.