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Eric Visser

Publications and source records attributed to Eric Visser.

3 recordsLinked to original sources
PubMed2006

Software package for integrated data processing for internal dose assessment in nuclear medicine (SPRIND).

PURPOSE: Internal radiation dose calculations are normally carried out using the Medical Internal Radiation Dose (MIRD) schema. This requires residence times of radiopharmaceutical activity and S-values for all organs of interest. Residence times can be obtained by quantitative nuclear imaging modalities. For dealing with S-values, the freeware packages MIRDOSE and, more recently, OLINDA/EXM are available. However, these software packages do not calculate residence times from image data. METHODS AND RESULTS: For this purpose, we developed an IDL-based software package for integrated data processing for internal dose assessment in nuclear medicine (SPRIND). SPRIND allows reading and viewing of planar whole-body scintigrams. Organ and background regions of interest (ROIs) can be drawn and are automatically mirrored from the anterior to the posterior view. ROI statistics are used to obtain anterior-posterior averaged counts for each organ, corrected for background activity and attenuation. Residence times for each organ are calculated based on effective decay. The total body biological half-time is calculated for use in the voiding bladder model. Red bone marrow absorbed dose can be calculated using bone regions in the scintigrams or by a blood-derived method. Finally, the results are written to a file in MIRDOSE-OLINDA/EXM format. Using scintigrams in DICOM, the complete analysis is gamma camera vendor independent, and can be performed on any computer using an IDL virtual machine. CONCLUSION: SPRIND is an easy-to-use software package for radiation dose assessment studies. It has made these studies less time consuming and less error prone.

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PubMed2006

Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters.

PURPOSE: Standardised uptake values (SUVs) depend on acquisition, reconstruction and region of interest (ROI) parameters. SUV quantification in multi-centre trials therefore requires standardisation of acquisition and analysis protocols. However, standardisation is difficult owing to the use of different scanners, image reconstruction and data analysis software. In this study we evaluated whether SUVs, obtained at three different institutes, may be directly compared after calibration and correction for inter-institute differences. METHODS: First, an anthropomorphic thorax phantom containing variously sized spheres and activities, simulating tumours, was scanned and processed in each institute to evaluate differences in scanner calibration. Secondly, effects of image reconstruction and ROI method on recovery coefficients were studied. Next, SUVs were derived for tumours in 23 subjects. Of these 23 patients, four and ten were scanned in two institutes on an HR+ PET scanner and nine were scanned in one institute on an ECAT EXACT PET scanner. All phantom and clinical data were reconstructed using iterative reconstruction with various iterations, with both measured (MAC) and segmented attenuation correction (SAC) and at various image resolutions. Activity concentrations (AC) or SUVs were derived using various ROI isocontours. RESULTS: Phantom data revealed differences in SUV quantification of up to 30%. After application-specific calibration, recovery coefficients obtained in each institute were equal to within 15%. Varying the ROI isocontour value resulted in a predictable change in SUV (or AC) for both phantom and clinical data. Variation of image resolution resulted in a predictable change in SUV quantification for large spheres/tumours (>5 cc) only. For smaller tumours (<2 cc), differences of up to 40% were found between high (7 mm) and low (10 mm) resolution images. Similar differences occurred when data were reconstructed with a small number of iterations. Finally, no significant differences between MAC and SAC reconstructed data were observed, except for tumours near the diaphragm. CONCLUSION: Standardisation of acquisition, reconstruction and ROI methods is preferred for SUV quantification in multi-centre trials. Small unavoidable differences in methodology can be accommodated by performing a phantom study to assess inter-institute correction factors.

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