Perfusion defect size predicts engraftment but not early retention of intra-myocardially injected cardiosphere-derived cells after acute myocardial infarction

Therapeutic cell retention and engraftment are critical for myocardial regeneration. Underlying mechanisms, including the role of tissue perfusion, are not well understood. In Wistar Kyoto rats, syngeneic cardiosphere-derived cells (CDCs) were injected intramyocardially, after experimental myocardial infarction. CDCs were labeled with [18F]-FDG (n = 7), for quantification of 1-h retention, or with sodium-iodide-symporter gene (NIS; n = 8), for detection of 24-h engraftment by reporter imaging. Perfusion was imaged simultaneously. Infarct size was 37 ± 9 and 38 ± 9% of LV in FDG and NIS groups. Cell signal was located in the infarct border zone in all animals. No significant relationship was observed between infarct size and 1-h CDC retention (r = −0.65; P = 0.11). However, infarct size correlated significantly with 24-h engraftment (r = 0.75; P = 0.03). Residual perfusion at the injection site was not related to cell retention/engraftment. Larger infarcts are associated with improved CDC engraftment. This observation encourages further investigation of microenvironmental conditions after ischemic damage and their role in therapeutic cell survival

PET imaging of the autonomic myocardial function: methods and interpretation.

Cardiac positron emission tomography (PET) is mainly applied in myocardial perfusion and viability detection. Noninvasive imaging of myocardial innervation using PET is a valuable additional methodology in cardiac imaging. Novel methods and different PET ligands have been developed to measure presynaptic and postsynaptic function of the cardiac neuronal system. Obtained PET data can be analysed quantitatively or interpreted qualitatively. Thus far, PET is not a widely used clinical application in autonomic heart imaging; however, due to its technical advantages, the excellent properties of the imaging agents, and the availability of tools for quantification, it deserves a better position in the clinic. From a historical point of view, the focus of PET software packages for image analysis was mainly oncology and neurology driven. Actually, commercially available software for cardiac PET image analysis is still only available for the quantification of myocardial blood flow. Thus far, no commercial software package is available for the interpretation and quantification of PET innervation scans. However, image data quantification and analysis of kinetic data can be performed using adjusted generic tools. This paper gives an overview of different neuronal PET ligands, interpretation and quantification of acquired PET data

Hybrid PET- and MR-driven attenuation correction for enhanced ¹⁸F-NaF and ¹⁸F-FDG quantification in cardiovascular PET/MR imaging

Background: The standard MR Dixon-based attenuation correction (AC) method in positron emission tomography/magnetic resonance (PET/MR) imaging segments only the air, lung, fat and soft-tissues (4-class), thus neglecting the highly attenuating bone tissues and affecting quantification in bones and adjacent vessels. We sought to address this limitation by utilizing the distinctively high bone uptake rate constant Ki expected from ¹⁸F-Sodium Fluoride (¹⁸F-NaF) to segment bones from PET data and support 5-class hybrid PET/MR-driven AC for ¹⁸F-NaF and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG) PET/MR cardiovascular imaging. Methods: We introduce 5-class Ki/MR-AC for (i) ¹⁸F-NaF studies where the bones are segmented from Patlak Ki images and added as the 5th tissue class to the MR Dixon 4-class AC map. Furthermore, we propose two alternative dual-tracer protocols to permit 5-class Ki/MR-AC for (ii) ¹⁸F-FDG-only data, with a streamlined simultaneous administration of ¹⁸F-FDG and ¹⁸F-NaF at 4:1 ratio (R4:1), or (iii) for ¹⁸F-FDG-only or both ¹⁸F-FDG and ¹⁸F-NaF dual-tracer data, by administering ¹⁸F-NaF 90 minutes after an equal ¹⁸F-FDG dosage (R1:1). The Ki-driven bone segmentation was validated against computed tomography (CT)-based segmentation in rabbits, followed by PET/MR validation on 108 vertebral bone and carotid wall regions in 16 human volunteers with and without prior indication of carotid atherosclerosis disease (CAD). Results: In rabbits, we observed similar (< 1.2% mean difference) vertebral bone ¹⁸F-NaF SUVmean scores when applying 5-class AC with Ki-segmented bone (5-class Ki/CT-AC) vs CT-segmented bone (5-class CT-AC) tissue. Considering the PET data corrected with continuous CT-AC maps as gold-standard, the percentage SUVmean bias was reduced by 17.6% (¹⁸F-NaF) and 15.4% (R4:1) with 5-class Ki/CT-AC vs 4-class CT-AC. In humans without prior CAD indication, we reported 17.7% and 20% higher ¹⁸F-NaF target-to-background ratio (TBR) at carotid bifurcations wall and vertebral bones, respectively, with 5- vs 4-class AC. In the R4:1 human cohort, the mean ¹⁸F-FDG:¹⁸F-NaF TBR increased by 12.2% at carotid bifurcations wall and 19.9% at vertebral bones. For the R1:1 cohort of subjects without CAD indication, mean TBR increased by 15.3% (¹⁸F-FDG) and 15.5% (¹⁸F-NaF) at carotid bifurcations and 21.6% (¹⁸F-FDG) and 22.5% (¹⁸F-NaF) at vertebral bones. Similar TBR enhancements were observed when applying the proposed AC method to human subjects with prior CAD indication. Conclusions: Ki-driven bone segmentation and 5-class hybrid PET/MR-driven AC is feasible and can significantly enhance ¹⁸F-NaF and ¹⁸F-FDG contrast and quantification in bone tissues and carotid walls

Registration of myocardial PET and SPECT for viability assessment using mutual information RID A-6953-2008

Purpose: The combination of sequentially acquired cardiac PET and SPECT data integrating metabolic and perfusion information allows the assessment of myocardial viability, a relevant clinical parameter for the management of patients who have suffered myocardial infarction and are now candidates for complex and cost intensive therapies such as bypass surgery. However, registration of cardiac functional datasets acquired on different imaging systems is limited by the difficulty to define anatomical landmarks and by the relatively poor inherent spatial resolution. In this article, the authors sought to evaluate whether it is possible to automatically register FDG-PET and sestamibi-SPECT cardiac data. Methods: Automatic rigid registration was implemented with the ITK framework using Mattes mutual information as the similarity measure and a quaternion to represent the rotational component. The goodness of the alignment was evaluated by computing the mean target registration error (mTRE) at the myocardial wall. The registration parameters were optimized for robustness and speed using the data from 11 cardiac patients undergoing both PET and SPECT examinations (training datasets). The optimized algorithm was applied on the PET and SPECT data from 11 further patients (evaluation datasets). Quantitative (mTRE calculation) and visual (scoring method) comparisons were performed between automatic and manual registrations. Moreover, the automatic registration was also compared to the registration implicitly defined in the standard clinical analysis. Results: The registration parameters were successfully optimized and resulted in a mean mTRE of 1.13 mm and 1.2 s average runtime on standard computer hardware for the training datasets. Automatic registration in the 11 validation datasets resulted in an average mTRE of 2.3 mm, with 7.5 mm mTRE in the worst case and an average runtime of 1.6 s. Automatic registration outperformed manual registrations both for the mTRE and for the visual assessment. Automatic registration also resulted in higher accuracy and better visual assessment as compared to the registration implicitly performed in the standard clinical analysis. Conclusions: The results demonstrate the possibility to successfully perform mutual information based registration of PET and SPECT cardiac data, allowing an improved workflow for the sequentially acquired cardiac datasets, in general, and specifically for the assessment of myocardial viability. (C) 2010 American Association of Physicists in Medicine. [DOI: 10.1118/1.3395554