Due to the shortage of kidneys donated for transplantation, surgeons are forced to use the organs with an elevated risk of poor function or even failure. Although the existing methods for pre-transplant quality evaluation have been validated over decades in population cohort studies across the world, new methods are needed as long as delayed graft function or failure in a kidney transplant occurs. In this study, we explored the potential of utilizing photoacoustic (PA) imaging during normothermic machine perfusion (NMP) as a means of evaluating kidney quality. We closely monitored twenty-two porcine kidneys using 3D PA imaging during a two-hour NMP session. Based on biochemical analyses of perfusate and produced urine, the kidneys were categorized into ‘non-functional’ and ‘functional’ groups. Our primary focus was to quantify oxygenation (sO₂) within the kidney cortical layer of depths 2 mm, 4 mm, and 6 mm using two-wavelength PA imaging. Next, receiver operating characteristic (ROC) analysis was performed to determine an optimal cortical layer depth and time point for the quantification of sO₂ to discriminate between functional and non-functional organs. Finally, for each depth, we assessed the correlation between sO₂ and creatinine clearance (CrCl), oxygen consumption (VO₂), and renal blood flow (RBF). We found that hypoxia of the renal cortex is associated with poor renal function. In addition, the determination of sO₂ within the 2 mm depth of the renal cortex after 30 min of NMP effectively distinguishes between functional and non-functional kidneys. The non-functional kidneys can be detected with the sensitivity and specificity of 80% and 85% respectively, using the cut-off point of sO₂ < 39%. Oxygenation significantly correlates with RBF and VO₂ in all kidneys. In functional kidneys, sO₂ correlated with CrCl, which is not the case for non-functional kidneys. We conclude that the presented technique has a high potential for supporting organ selection for kidney transplantation.

Objectives: Normothermic machine perfusion (NMP) provides a platform for pre-transplant kidney quality assessment that is essential for the use of marginal donor kidneys. Laser speckle contrast imaging (LSCI) presents distinct advantages as a real-time and noncontact imaging technique for measuring microcirculation. In this study, we aimed to assess the value of LSCI in visualizing renal cortical perfusion and investigate the additional value of dual-side LSCI measurements compared to single aspect measurement during NMP. Methods: Porcine kidneys were obtained from a slaughterhouse and then underwent NMP. LSCI was used to measure one-sided cortical perfusion in the first 100 min of NMP. Thereafter, the inferior renal artery branch was occluded to induce partial ischemia and LSCI measurements on both ventral and dorsal sides were performed. Results: LSCI fluxes correlated linearly with the renal blood flow (R² = 0.90, p < 0.001). After renal artery branch occlusion, absence of renal cortical perfusion could be visualized and semiquantified by LSCI. The overall ischemic area percentage of the ventral and dorsal sides was comparable (median interquartile range [IQR], 38 [24−43]% vs. 29 [17−46]%, p = 0.43), but heterogenous patterns between the two aspects were observed. There was a significant difference in oxygen consumption (mean ± standard deviation [SD], 2.57 ± 0.63 vs. 1.83 ± 0.49 mLO₂/min/100 g, p < 0.001), urine output (median [IQR], 1.3 [1.1−1.7] vs. 0.8 [0.6−1.3] mL/min, p < 0.05), lactate dehydrogenase (mean ± SD, 768 ± 370 vs. 905 ± 401 U/L, p < 0.05) and AST (mean ± SD, 352 ± 285 vs. 462 ± 383 U/L, p < 0.01) before and after renal artery occlusion, while no significant difference was found in creatinine clearance, fractional excretion of sodium, total sodium reabsorption and histological damage. Conclusions: LSCI fluxes correlated linearly with renal blood flow during NMP. Renal cortical microcirculation and absent perfusion can be visualized and semiquantified by LSCI. It provides a relative understanding of perfusion levels, allowing for a qualitative comparison between regions in the kidney. Dual-side LSCI measurements are of added value compared to single aspect measurement and renal function markers.

Background & aims: Low skeletal muscle mass and density have recently been discovered as prognostic and predictive parameters to guide interventions in various populations, including cancer patients. The gold standard for body composition analysis in cancer patients is computed tomography (CT). To date, the effect of contrast-enhancement on muscle composition measurements has not been established. The aim of this study was to determine the effect of contrast-enhancement on skeletal muscle mass and density measurements on four-phase CT studies. Design: In this observational study, two observers measured cross-sectional skeletal muscle area corrected for patients' height (skeletal muscle index [SMI]) and density (SMD) at the level of the third lumbar vertebra on 50 randomly selected CT examinations with unenhanced, arterial, and portal-venous phases. The levels of agreement between enhancement phases for SMI and SMD were calculated using intra-class correlation coefficients (ICCs). Results: Mean SMI was 42.5 (±9.9) cm²/m² on the unenhanced phase, compared with 42.8 (±9.9) and 43.6 (±9.9) cm²/m² for the arterial and portal-venous phase, respectively (both p < 0.01). Mean SMD was lower for the unenhanced phase (30.9 ± 8.0 Hounsfield units [HU]) compared with the arterial (38.0 ± 9.9 HU) and portal-venous (38.7 ± 9.2 HU) phase (both p < 0.001). No significant difference was found between SMD in the portal-venous and arterial phase (p = 0.161). The ICCs were excellent (≥0.992) for all SMIs and for SMD between the contrast-enhanced phases (0.949). The ICCs for the unenhanced phase compared with the arterial (0.676) and portal-venous (0.665) phase were considered fair to good. Conclusions: Statistically significant differences in SMI were observed between different enhancement phases. However, further work is needed to assess the clinical relevance of these small differences. Contrast-enhancement strongly influenced SMD values. Studies using this measure should therefore use the portal-venous phase of contrast-enhanced CT examinations.

Background: The association between body composition (e.g. sarcopenia or visceral obesity) and treatment outcomes, such as survival, using single-slice computed tomography (CT)-based measurements has recently been studied in various patient groups. These studies have been conducted with different software programmes, each with their specific characteristics, of which the inter-observer, intra-observer, and inter-software correlation are unknown. Therefore, a comparative study was performed. Methods: Fifty abdominal CT scans were randomly selected from 50 different patients and independently assessed by two observers. Cross-sectional muscle area (CSMA, i.e. rectus abdominis, oblique and transverse abdominal muscles, paraspinal muscles, and the psoas muscle), visceral adipose tissue area (VAT), and subcutaneous adipose tissue area (SAT) were segmented by using standard Hounsfield unit ranges and computed for regions of interest. The inter-software, intra-observer, and inter-observer agreement for CSMA, VAT, and SAT measurements using FatSeg, OsiriX, ImageJ, and sliceOmatic were calculated using intra-class correlation coefficients (ICCs) and Bland–Altman analyses. Cohen's κ was calculated for the agreement of sarcopenia and visceral obesity assessment. The Jaccard similarity coefficient was used to compare the similarity and diversity of measurements. Results: Bland–Altman analyses and ICC indicated that the CSMA, VAT, and SAT measurements between the different software programmes were highly comparable (ICC 0.979–1.000, P < 0.001). All programmes adequately distinguished between the presence or absence of sarcopenia (κ = 0.88–0.96 for one observer and all κ = 1.00 for all comparisons of the other observer) and visceral obesity (all κ = 1.00). Furthermore, excellent intra-observer (ICC 0.999–1.000, P < 0.001) and inter-observer (ICC 0.998–0.999, P < 0.001) agreement for all software programmes were found. Accordingly, excellent Jaccard similarity coefficients were found for all comparisons (mean ≥ 0.964). Conclusions: FatSeg, OsiriX, ImageJ, and sliceOmatic showed an excellent agreement for CSMA, VAT, and SAT measurements on abdominal CT scans. Furthermore, excellent inter-observer and intra-observer agreement were achieved. Therefore, results of studies using these different software programmes can reliably be compared.