One-tissue compartment model for myocardial perfusion quantification with N-13 ammonia PET provides matching results: A cross-comparison between Carimas, FlowQuant, and PMOD

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.

Myocardial perfusion quantification by CMR for detection of obstructive coronary artery disease in patients with previous coronary artery bypass surgery

Funding Acknowledgements Type of funding sources: Other. Main funding source(s): British Heart Foundation Background Coronary artery bypass grafting (CABG) is an established treatment for patients with advanced coronary artery disease (CAD). A subsequent recurrence of symptoms can cause the need for re-assessment of the coronary circulation. The accuracy of visually assessed stress perfusion cardiovascular magnetic resonance (CMR) for the detection of obstructive CAD is reduced in patients with prior CABG. In patients with complex multi-vessel CAD, myocardial perfusion quantification by CMR is superior to visual assessment (VA) for detection of obstructive disease however patients with CABG have been absent from previous studies. Purpose This study sought to assess the performance of myocardial perfusion quantification by CMR against invasive coronary angiography (ICA) for detecting obstructive CAD in patients with previous CABG. Methods Twenty-nine patients with a history of previous CABG and subsequent clinically indicated perfusion CMR study and invasive coronary angiography were recruited. Patients underwent a dual bolus stress perfusion CMR with late gadolinium enhancement (LGE) imaging at 3 Tesla. Stress myocardial blood flow (MBF) was estimated at the coronary territory level according to the AHA 16 segment model using Fermi function-constrained deconvolution. Segments with transmural LGE were excluded from MBF analysis. Stress perfusion images were analysed visually alongside LGE images and matched perfusion-LGE defects were considered negative. On ICA, coronary territories with lumen stenosis &gt;70% without an unobstructed bypass graft (&lt;70% stenosis) were considered positive. Results 86/87 coronary territories were suitable for analysis. Sixty-five territories had at least one bypass graft including 32 territories with arterial grafts. 28/86 territories (33%) had obstructive disease on angiography. Territories with obstructive CAD had significantly lower stress MBF than unobstructed territories (1.21 [IQR: 0.96–1.45] vs 1.58 [1.40–1.84] ml/g/min, p &lt; 0.001, Figure 1). Stress MBF had good accuracy to detect coronary territories with obstructive CAD (sensitivity 71%, specificity 84%, area under the curve (AUC) 0.83, p &lt; 0.001, Figure 2A). For visual assessment, sensitivity was 79%, specificity 78% and diagnostic accuracy 78%. When analysis was confined to only territories with bypass grafts, stress MBF had 78% sensitivity, 81% specificity and AUC of 0.85, p &lt; 0.001 (Figure 2B).. In this subgroup, VA had a sensitivity of 78%, specificity of 76% and a 77% diagnostic accuracy. Conclusions In patients with previous surgical revascularisation, quantification of stress myocardial blood flow by CMR offers good diagnostic accuracy for the detection and localisation of anatomically significant stenoses. Accuracy is reduced compared with published data in patients without coronary grafts but remains comparable to expert visual assessment.

Choroid plexus perfusion in sickle cell disease and moyamoya vasculopathy: Implications for glymphatic flow

Cerebrospinal fluid (CSF) and interstitial fluid exchange have been shown to increase following pharmacologically-manipulated increases in cerebral arterial pulsatility, consistent with arterial pulsatility improving CSF circulation along perivascular glymphatic pathways. The choroid plexus (CP) complexes produce CSF, and CP activity may provide a centralized indicator of perivascular flow. We tested the primary hypothesis that elevated cortical cerebral blood volume and flow, present in sickle cell disease (SCD), is associated with fractionally-reduced CP perfusion relative to healthy adults, and the supplementary hypothesis that reduced arterial patency, present in moyamoya vasculopathy, is associated with elevated fractional CP perfusion relative to healthy adults. Participants (n = 75) provided informed consent and were scanned using a 3-Tesla arterial-spin-labeling MRI sequence for CP and cerebral gray matter (GM) perfusion quantification. ANOVA was used to calculate differences in CP-to-GM perfusion ratios between groups, and regression analyses applied to evaluate the dependence of the CP-to-GM perfusion ratio on group after co-varying for age and sex. ANOVA yielded significant (p < 0.001) group differences, with CP-to-GM perfusion ratios increasing between SCD (ratio = 0.93 ± 0.28), healthy (ratio = 1.04 ± 0.32), and moyamoya (ratio = 1.29 ± 0.32) participants, which was also consistent with regression analyses. Findings are consistent with CP perfusion being inversely associated with cortical perfusion.

Intraoperative Perfusion Assessment in Enhanced Reality Using Quantitative Optical Imaging: An Experimental Study in a Pancreatic Partial Ischemia Model

To reduce the risk of pancreatic fistula after pancreatectomy, a satisfactory blood flow at the pancreatic stump is considered crucial. Our group has developed and validated a real-time computational imaging analysis of tissue perfusion, using fluorescence imaging, the fluorescence-based enhanced reality (FLER). Hyperspectral imaging (HSI) is another emerging technology, which provides tissue-specific spectral signatures, allowing for perfusion quantification. Both imaging modalities were employed to estimate perfusion in a porcine model of partial pancreatic ischemia. Perfusion quantification was assessed using the metrics of both imaging modalities (slope of the time to reach maximum fluorescence intensity and tissue oxygen saturation (StO2), for FLER and HSI, respectively). We found that the HSI-StO2 and the FLER slope were statistically correlated using the Spearman analysis (R = 0.697; p = 0.013). Local capillary lactate values were statistically correlated to the HSI-StO2 and to the FLER slope (R = −0.88; p < 0.001 and R = −0.608; p = 0.0074). HSI-based and FLER-based lactate prediction models had statistically similar predictive abilities (p = 0.112). Both modalities are promising to assess real-time pancreatic perfusion. Clinical translation in human pancreatic surgery is currently underway.

Quantitative perfusion-CMR is significantly influenced by the placement of the arterial input function

The aim of this study is to provide a systematic assessment of the influence of the position on the arterial input function (AIF) for perfusion quantification. In 39 patients with a wide range of left ventricular function the AIF was determined using a diluted contrast bolus of a cardiac magnetic resonance imaging in three left ventricular levels (basal, mid, apex) as well as aortic sinus (AoS). Time to peak signal intensities, baseline corrected peak signal intensity and upslopes were determined and compared to those obtained in the AoS. The error induced by sampling the AIF in a position different to the AoS was determined by Fermi deconvolution. The time to peak signal intensity was strongly correlated (r2 > 0.9) for all positions with a systematic earlier arrival in the basal (− 2153 ± 818 ms), the mid (− 1429 ± 928 ms) and the apical slice (− 450 ± 739 ms) relative to the AoS (all p < 0.001). Peak signal intensity as well as upslopes were strongly correlated (r2 > 0.9 for both) for all positions with a systematic overestimation in all positions relative to the AoS (all p < 0.001 and all p < 0.05). Differences between the positions were more pronounced for patients with reduced ejection fraction. The error of averaged MBF quantification was 8%, 13% and 27% for the base, mid and apex. The location of the AIF significantly influences core parameters for perfusion quantification with a systematic and ejection fraction dependent error. Full quantification should be based on obtaining the AIF as close as possible to the myocardium to minimize these errors.