RESUMEN
BACKGROUND: Rejection is a major cause of mortality and morbidity in heart transplant (HTx) recipients. Current methods for diagnosing rejection have limitations. Imaging methods to map the entire left ventricle and reliably identify potential sites of rejection is lacking. Animal studies suggest FDG PET-CT (FDG PET) could have potential application in human HTx recipients. METHODS: Between December 2020 and February 2022, all HTx recipients at Harefield Hospital, London, with definite or suspected rejection underwent FDG PET in addition to routine work-up. RESULTS: Thirty HTx recipients (12 with definite and 18 with suspected rejection) underwent FDG PET scans. Overall, 12 of the 30 patients had FDG PET with increased myocardial avidity, of whom 2 died (17%). Eighteen patients of the 30 patients had FDG PET with no myocardial avidity and all are alive (100%, p = 0.15). All patients with definite rejection, scanned within 2 weeks of starting anti-rejection treatment, showed increased myocardial avidity. In 5 cases, FDG PET showed myocardial avidity beyond 6 weeks despite pulsed steroid treatment, suggesting unresolved myocardial rejection. CONCLUSION: Preliminary findings suggest FDG PET may have a role in diagnosing cardiac transplant rejection. Future blinded studies are needed to help further validate this.
RESUMEN
BACKGROUND AND AIM: The Cedars-Sinai Quantitative Gated Single Photon Emission Computed Tomography (SPECT) (QGS) program, used to quantify left ventricular function parameters from gated myocardial perfusion scintigraphy (MPS), has been extensively validated and compared with other methods of quantification. However, little is known about the reproducibility of QGS on different processing systems. This study compared the findings of QGS running on workstations provided by two different manufacturers. METHODS: Gated rest MPS studies of 50 patients were analysed retrospectively. Filtered back-projection (FBP) was performed using identical parameters on Philips Pegasys and Nuclear Diagnostics Hermes workstations to produce gated short-axis (SA) slices. In addition, the gated SA slices reconstructed on the Pegasys were transferred to the Hermes. QGS was used to calculate the end-diastolic volume (EDV), end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) in each case. RESULTS: The mean+/-standard deviation differences between the Pegasys and Hermes function parameters were -7.06+/-3.91 ml (EDV), -5.54+/-3.21 ml (ESV) and +1.14%+/-1.43% (LVEF) when data were reconstructed on different systems, and -0.16+/-1.58 ml (EDV), -0.10+/-1.02 ml (ESV) and +0.14%+/-0.73% (LVEF) when data were reconstructed on the same system. Bland-Altman plots showed definite trends for EDV and ESV for data reconstructed on different systems, but no trends were seen for data reconstructed on the same system. CONCLUSIONS: When data were reconstructed on two separate systems, the difference between the function parameters obtained from Pegasys and Hermes could be ascribed to differences in the reconstruction process on each system despite the use of identical parameters (filters, etc). However, when the same reconstructed data were analysed on both systems, no significant difference in left ventricular function parameters was observed.