Synthesis and Evaluation of 99mTc-Labeled PSMA-Targeted Tracers Based on the Lys-Urea-Aad Pharmacophore for Detecting Prostate Cancer with Single Photon Emission Computed Tomography.

Prostate-specific membrane antigen (PSMA) is a well-validated prostate cancer marker but reported PSMA-targeted tracers derived from the Lys-urea-Glu pharmacophore including the clinically validated [99mTc]Tc-EDDA/HYNIC-iPSMA have high off-target uptake in kidneys, spleen, and salivary glands. In this study, we synthesized and evaluated three novel 99mTc-labeled PSMA-targeted tracers and investigated if the tracers derived from the Lys-urea-Aad pharmacophore could have minimized uptake in off-target organs/tissues. In vitro competition binding assays showed that compared with HYNIC-iPSMA, the three novel ligands had slightly weaker PSMA binding affinity (average Ki = 3.11 vs. 8.96-11.6 nM). Imaging and ex vivo biodistribution studies in LNCaP tumor-bearing mice showed that [99mTc]Tc-EDDA/HYNIC-iPSMA and the three novel tracers successfully visualized LNCaP tumor xenografts in SPECT images and were excreted mainly via the renal pathway. The average tumor uptake at 1 h post-injection varied from 5.40 to 18.8%ID/g, and the tracers derived from the Lys-urea-Aad pharmacophore had much lower uptake in the spleen and salivary glands. Compared with the clinical tracer [99mTc]Tc-EDDA/HYNIC-iPSMA, the Lys-urea-Aad-derived [99mTc]Tc-EDDA-KL01127 had lower background uptake and superior tumor-to-background contrast ratios and is therefore promising for clinical translation to detect prostate cancer lesions with SPECT.

Automated Retinal Layer Segmentation Using Spectral Domain Optical Coherence Tomography: Evaluation of Inter-Session Repeatability and Agreement between Devices.

Retinal and intra-retinal layer thicknesses are routinely generated from optical coherence tomography (OCT) images, but on-board software capabilities and image scaling assumptions are not consistent across devices. This study evaluates the device-independent Iowa Reference Algorithms (Iowa Institute for Biomedical Imaging) for automated intra-retinal layer segmentation and image scaling for three OCT systems. Healthy participants (n = 25) underwent macular volume scans using a Cirrus HD-OCT (Zeiss), 3D-OCT 1000 (Topcon), and a non-commercial long-wavelength (1040nm) OCT on two occasions. Mean thickness of 10 intra-retinal layers was measured in three ETDRS subfields (fovea, inner ring and outer ring) using the Iowa Reference Algorithms. Where available, total retinal thicknesses were measured using on-board software. Measured axial eye length (AEL)-dependent scaling was used throughout, with a comparison made to the system-specific fixed-AEL scaling. Inter-session repeatability and agreement between OCT systems and segmentation methods was assessed. Inter-session coefficient of repeatability (CoR) for the foveal subfield total retinal thickness was 3.43µm, 4.76µm, and 5.98µm for the Zeiss, Topcon, and long-wavelength images respectively. For the commercial software, CoR was 4.63µm (Zeiss) and 7.63µm (Topcon). The Iowa Reference Algorithms demonstrated higher repeatability than the on-board software and, in addition, reliably segmented all 10 intra-retinal layers. With fixed-AEL scaling, the algorithm produced significantly different thickness values for the three OCT devices (P<0.05), with these discrepancies generally characterized by an overall offset (bias) and correlations with axial eye length for the foveal subfield and outer ring (P<0.05). This correlation was reduced to an insignificant level in all cases when AEL-dependent scaling was used. Overall, the Iowa Reference Algorithms are viable for clinical and research use in healthy eyes imaged with these devices, however ocular biometry is required for accurate quantification of OCT images.