Biomedical subjects

Yuni K Dewaraja

Publications and source records attributed to Yuni K Dewaraja.

3 recordsLinked to original sources

PubMed2007

Recovery of total I-131 activity within focal volumes using SPECT and 3D OSEM.

We experimentally investigated the SPECT recovery of I-131 activity in multiple spheres located simultaneously at different locations within a cylindrical phantom that had an elliptical cross section. The sphere volumes ranged from 209 cc down to 4.2 cc. A Prism 3000 camera and two types of parallel-hexagonal-hole collimation were employed: high energy (HE) and ultra high energy (UHE). Using appropriately-different 3D models of the point source response function for the two types of collimation, approximately the same recovery of activity could be achieved with either collimation by 3D OSEM reconstruction. The recovery coefficient was greater with no background activity in the phantom by 0.10, on average, compared to that with background. In the HE collimation case, the activity recovery was considerably better for all volumes using 3D OSEM reconstruction than it had been in the past using 1D SAGE reconstruction. Recovery-coefficient-based correction in a simulated patient case involving spherical tumours moderately improved the activity estimates (average error reduced from 14% to 9% for UHE collimation, and from 15% to 11% for HE collimation). For a test case with HE collimation, increasing the projection-image sampling density while decreasing the image voxel size increased the recovery coefficient by 0.075 on average, and, if used in a full set of calibration measurements of recovery coefficient versus volume, might lead to further improvement in accuracy for the patient case.

Biophysical Phenomena↗

PubMed2005

Accurate dosimetry in 131I radionuclide therapy using patient-specific, 3-dimensional methods for SPECT reconstruction and absorbed dose calculation.

UNLABELLED: (131)I radionuclide therapy studies have not shown a strong relationship between tumor absorbed dose and response, possibly due to inaccuracies in activity quantification and dose estimation. The goal of this work was to establish the accuracy of (131)I activity quantification and absorbed dose estimation when patient-specific, 3-dimensional (3D) methods are used for SPECT reconstruction and for absorbed dose calculation. METHODS: Clinically realistic voxel-phantom simulations were used in the evaluation of activity quantification and dosimetry. SPECT reconstruction was performed using an ordered-subsets expectation maximization (OSEM) algorithm with compensation for scatter, attenuation, and 3D detector response. Based on the SPECT image and a patient-specific density map derived from CT, 3D dosimetry was performed using a newly implemented Monte Carlo code. Dosimetry was evaluated by comparing mean absorbed dose estimates calculated directly from the defined phantom activity map with those calculated from the SPECT image of the phantom. Finally, the 3D methods were applied to a radioimmunotherapy patient, and the mean tumor absorbed dose from the new calculation was compared with that from conventional dosimetry obtained from conjugate-view imaging. RESULTS: Overall, the accuracy of the SPECT-based absorbed dose estimates in the phantom was >12% for targets down to 16 mL and up to 35% for the smallest 7-mL tumor. To improve accuracy in the smallest tumor, more OSEM iterations may be needed. The relative SD from multiple realizations was <3% for all targets except for the smallest tumor. For the patient, the mean tumor absorbed dose estimate from the new Monte Carlo calculation was 7% higher than that from conventional dosimetry. CONCLUSION: For target sizes down to 16 mL, highly accurate and precise dosimetry can be obtained with 3D methods for SPECT reconstruction and absorbed dose estimation. In the future, these methods can be applied to patients to potentially establish correlations between tumor regression and the absorbed dose statistics from 3D dosimetry.

Abdominal Neoplasms↗

PubMed2002

A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in (131)I SPECT.

This paper reports the implementation of the SIMIND Monte Carlo code on an IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. Our parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For (131)I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.

Computer Simulation↗