Objective To compare myocardial blood flow (MBF) and myocardial flow reserve (MFR) estimates from 82Rb PET data using ten software packages (SPs): Carimas, Corridor4DM, FlowQuant, HOQUTO, ImagenQ, MunichHeart, PMOD, QPET, syngo MBF, and UW-QPP. Background It is unknown how MBF and MFR values from existing SPs agree for 82Rb PET. Methods Rest and stress 82Rb PET scans of 48 patients with suspected or known coronary artery disease (CAD) were analyzed in 10 centers. Each center used one of the 10 SPs to analyze global and regional MBF using the different kinetic models implemented. Values were considered to agree if they simultaneously had an intraclass correlation coefficient (ICC) > 0.75 and a difference < 20% of the median across all programs. Results The most common model evaluated was the one-tissue compartment model (1TCM) by Lortie et al. (2007). MBF values from seven of the eight software packages implementing this model agreed best (Carimas, Corridor4DM, FlowQuant, PMOD, QPET, syngoMBF, and UW-QPP). Values from two other models (El Fakhri et al. in Corridor4DM and Alessio et al. in UW-QPP) also agreed well, with occasional differences. The MBF results from other models (Sitek et al. 1TCM in Corridor4DM, Katoh et al. 1TCM in HOQUTO, Herrero et al. 2TCM in PMOD, Yoshida et al. retention in ImagenQ, and Lautamäki et al. retention in MunichHeart) were less in agreement with Lortie 1TCM values. Conclusions SPs using the same kinetic model, as described in Lortie et al. (2007), provided consistent results in measuring global and regional MBF values, suggesting they may be used interchangeably to process data acquired with a common imaging protocol.
Purpose To cross-compare three software packages (SPs)—Carimas, FlowQuant, and PMOD—to quantify myocardial perfusion at global, regional, and segmental levels. Materials and Methods Stress N-13 ammonia PET scans of 48 patients with HCM were analyzed in three centers using Carimas, FlowQuant, and PMOD. Values agreed if they had an ICC > 0.75 and a difference < 20% of the median across all observers. Results When using 1TCM on the global level, the agreement was good, and the maximum difference between 1TCM MBF values was 17.2% (ICC = 0.83). On the regional level, the agreement was acceptable except in the LCx region (25.5% difference, ICC = 0.74) between FlowQuant and PMOD. Carimas-1TCM agreed well with PMOD-1TCM and FlowQuant-1TCM. Values obtained with FlowQuant-1TCM had a somewhat lesser agreement with PMOD-1TCM, especially at the segmental level. Conclusions The global and regional MBF values (with one exception) agree well between the different software packages. There is significant variability in segmental values, mainly located in the LCx region and segments. Out of the studied tools, Carimas can be used interchangeably with both PMOD and FlowQuant for 1TCM implementation on all levels—global, regional, and segmental.
Purpose The prognostic meaning of a post-stress ejection fraction (EF) decrease detected by perfusion gated SPECT is still unclear. We therefore followed up patients with post-stress EF decrease in the absence of stress-induced perfusion abnormalities. Methods We prospectively enrolled 57 consecutive patients with post-stress EF drop ≥5 EF units and summed difference score (SDS)≤1. They were followed up for more than 1 year and their outcome was compared with a group of sex-and agematched controls with the same SDS but without EF decrease. Results During follow-up there were 13 events (1 cardiac death, 1 non-fatal myocardial infarction, 1 congestive heart failure and 10 late revascularizations). In the control group we registered six events. There was a significant difference (p<0.0001) between the event-free survival curves of the two groups. ConclusionThe event rate of patients with post-stress EF decrease≥5 EF units is relatively high and is significantly worse than that of a control group of patients with similarly normal SDS but without EF changes. Therefore, a post-stress EF decrease without stress-induced perfusion abnormalities should be cautiously interpreted.
Purpose To estimate the interobserver agreement of the Carimas software package (SP) on global, regional, and segmental levels for the most widely used myocardial perfusion PET tracer—Rb-82. Materials and methods Rest and stress Rb-82 PET scans of 48 patients with suspected or known coronary artery disease (CAD) were analyzed in four centers using the Carimas SP. We considered values to agree if they simultaneously had an intraclass correlation coefficient (ICC) > 0.75 and a difference < 20% of the median across all observers. Results The median values on the segmental level were 1.08 mL/min/g for rest myocardial blood flow (MBF), 2.24 mL/min/g for stress MBF, and 2.17 for myocardial flow reserve (MFR). For the rest MBF and MFR, all the values at all the levels fulfilled were in excellent agreement. For stress MBF, at the global and regional levels, all the 24 comparisons showed excellent agreement. Only 1 out of 102 segmental comparisons (seg. 14) was over the adequate agreement limit—23.5% of the median value (ICC = 0.95). Conclusion Interobserver agreement for Rb-82 PET myocardial perfusion quantification analyzed with Carimas is good at any LV segmentation level—global, regional, and segmental. It is good for all the estimates—rest MBF, stress MBF, and MFR.
In patients submitted to gated SPECT for suspect CAD, SBPR appears poorly effective for the detection of significant CAD, and does not show any valuable relationship with exercise-induced functional abnormalities.
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