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Background To evaluate quantitative myocardial perfusion SPECT/CT datasets for routine clinical reporting and the assessment of myocardial tracer uptake in patients with severe TVCAD. Methods MPS scans were reconstructed as quantitative SPECT datasets using CTs from internal (SPECT/CT, Q_INT) and external (PET/CT, Q_EXT) sources for attenuation correction. TPD was calculated and compared to the TPD from non-quantitative SPECT datasets of the same patients. SUVmax, SUVpeak, and SUVmean were compared between Q_INT and Q_EXT SPECT datasets. Global SUVmax and SUVpeak were compared between patients with and without TVCAD. Results Quantitative reconstruction was feasible. TPD showed an excellent correlation between quantitative and non-quantitative SPECT datasets. SUVmax, SUVpeak, and SUVmean showed an excellent correlation between Q_INT and Q_EXT SPECT datasets, though mean SUVmean differed significantly between the two groups. Global SUVmax and SUVpeak were significantly reduced in patients with TVCAD. Conclusions Absolute quantification of myocardial tracer uptake is feasible. The method seems to be robust and principally suitable for routine clinical reporting. Quantitative SPECT might become a valuable tool for the assessment of severe coronary artery disease in a setting of balanced ischemia, where potentially life-threatening conditions might otherwise go undetected.

Background Integrin alpha-V-beta-3 (αvβ3) pathway is involved in intraplaque angiogenesis and inflammation and represents a promising target for molecular imaging in cardiovascular diseases such as atherosclerosis. The aim of this study was to assess the clinical correlates of arterial wall accumulation of 68Ga-NODAGA-RGD, a specific αvβ3 integrin ligand for PET. Materials and methods The data of 44 patients who underwent 68Ga-NODAGA-RGD PET/CT scans were retrospectively analyzed. Tracer accumulation in the vessel wall of major arteries was analyzed semi-quantitatively by blood-pool-corrected target-to-background ratios. Tracer uptake was compared with clinically documented atherosclerotic cardiovascular disease, cardiovascular risk factors and calcified plaque burden. Data were compared using the Mann–Whitney U test, Pearson correlation and Spearman correlation. Results 68Ga-NODAGA-RGD arterial uptake was significantly higher in patients with previous clinically documented atherosclerotic cardiovascular disease (mean TBR 2.44 [2.03–2.55] vs. 1.81 [1.56–1.96], p = 0.001) and showed a significant correlation with prior cardiovascular or cerebrovascular event (r = 0.33, p = 0.027), BMI (ρ = 0.38, p = 0.01), plaque burden (ρ = 0.31, p = 0.04) and hypercholesterolemia (r = 0.31, p = 0.04). Conclusions 68Ga-NODAGA-RGD holds promise as a non-invasive marker of disease activity in atherosclerosis, providing information about intraplaque angiogenesis.

Purpose The application of automated image analyses could improve and facilitate standardization and consistency of quantification in [18F]DCFPyL (PSMA) PET/CT scans. In the current study, we analytically validated aPROMISE, a software as a medical device that segments organs in low-dose CT images with deep learning, and subsequently detects and quantifies potential pathological lesions in PSMA PET/CT. Methods To evaluate the deep learning algorithm, the automated segmentations of the low-dose CT component of PSMA PET/CT scans from 20 patients were compared to manual segmentations. Dice scores were used to quantify the similarities between the automated and manual segmentations. Next, the automated quantification of tracer uptake in the reference organs and detection and pre-segmentation of potential lesions were evaluated in 339 patients with prostate cancer, who were all enrolled in the phase II/III OSPREY study. Three nuclear medicine physicians performed the retrospective independent reads of OSPREY images with aPROMISE. Quantitative consistency was assessed by the pairwise Pearson correlations and standard deviation between the readers and aPROMISE. The sensitivity of detection and pre-segmentation of potential lesions was evaluated by determining the percent of manually selected abnormal lesions that were automatically detected by aPROMISE. Results The Dice scores for bone segmentations ranged from 0.88 to 0.95. The Dice scores of the PSMA PET/CT reference organs, thoracic aorta and liver, were 0.89 and 0.97, respectively. Dice scores of other visceral organs, including prostate, were observed to be above 0.79. The Pearson correlation for blood pool reference was higher between any manual reader and aPROMISE, than between any pair of manual readers. The standard deviations of reference organ uptake across all patients as determined by aPROMISE (SD = 0.21 blood pool and SD = 1.16 liver) were lower compared to those of the manual readers. Finally, the sensitivity of aPROMISE detection and pre-segmentation was 91.5% for regional lymph nodes, 90.6% for all lymph nodes, and 86.7% for bone in metastatic patients. Conclusion In this analytical study, we demonstrated the segmentation accuracy of the deep learning algorithm, the consistency in quantitative assessment across multiple readers, and the high sensitivity in detecting potential lesions. The study provides a foundational framework for clinical evaluation of aPROMISE in standardized reporting of PSMA PET/CT.

In this study, we used machine learning to develop a new method derived from a ligand-independent amyloid (Aβ) positron emission tomography (PET) classifier to harmonise different Aβ ligands. We obtained 107 paired 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) PET images at the Samsung Medical Centre. To apply the method to FMM ligand, we transferred the previously developed FBB PET classifier to test similar features from the FMM PET images for application to FMM, which in turn developed a ligand-independent Aβ PET classifier. We explored the concordance rates of our classifier in detecting cortical and striatal Aβ positivity. We investigated the correlation of machine learning-based cortical tracer uptake (ML-CTU) values quantified by the classifier between FBB and FMM. This classifier achieved high classification accuracy (area under the curve = 0.958) even with different Aβ PET ligands. In addition, the concordance rate of FBB and FMM using the classifier (87.5%) was good to excellent, which seemed to be higher than that in visual assessment (82.7%) and lower than that in standardised uptake value ratio cut-off categorisation (93.3%). FBB and FMM ML-CTU values were highly correlated with each other (R = 0.903). Our findings suggested that our novel classifier may harmonise FBB and FMM ligands in the clinical setting which in turn facilitate the biomarker-guided diagnosis and trials of anti-Aβ treatment in the research field.

A 42-year-old female underwent a myocardial perfusion scan (MPS) for the evaluation of coronary artery disease. Raw and cine loop images hinted at abnormal tracer accumulation in the chest. Review of short-axis slices and low-dose computed tomography images taken for attenuation correction and their subsequent fusion confirmed the presence of focal tracer uptake localized to nodular breast masses. This case demonstrates that despite MPS not being optimized to detect breast pathologies, careful inspection of unprocessed images and the application of available software for fusion can help detect concurrent pathology.

Stable isotope tracer experiments provide a powerful tool for understanding plant root distributions, resource uptake, niche partitioning and water cycling. Plant water is typically collected from pre-transpiring tissues to avoid the effects of evaporative isotope enrichment at the leaf surface, but extracting water from these plant samples is difficult and expensive. The purpose of this study was to test a simple transpiration bagging approach for measuring hydrologic tracer uptake. Sampling was performed as part of a depth-specific tracer experiment in which 2H2O was injected to target depths (5, 15, 30, 60, or 150 cm) in different replicated plots. One day following injections, leaves from three species were sealed in bags for 16 h and transpired water was collected. Water from pre-transpiring stem tissue was then collected in a separate set of samples and extracted using cryogenic distillation. Deuterium concentrations from the two techniques were correlated (R2 = 0.84) and both approaches produced similar descriptions of vertical root distributions for three dominant plant species. 18O concentrations from the two techniques were not correlated. Bagging transpired water produced similar estimates of 2H tracer uptake as the standard sampling technique. Bagging requires no destructive sampling, specialized laboratory equipment, training or consumables and is expected to halve sampling costs. While effective in this tracer experiment, bagging may be not be effective in natural abundance experiments, or tracer experiments with very small plants or small transpiration rates (i.e., early-season or arid sites).

A 43-year-old man diagnosed with fibrous dysplasia with McCune-Albright syndrome was subjected to 18F-fluoride bone scan and 68Ga-PSMA-HBED-CC PET/CT as per the institution protocol. 18F-bone scan revealed extensive involvement of axial and appendicular skeleton confirming polyostotic fibrous dysplasia. 68Ga-PSMA PET/CT showed increased tracer uptake in corresponding lesions of fibrous dysplasia. PSMA uptake in fibrous dysplasia lesions has been rarely described with literature evidence being limited to anecdotal case reports. Nevertheless, due to increasing use of PSMA PET/CT, one should be aware of this false-positive finding to avoid misinterpretation of the scans.

18F-2-fluoro-2-deoxy-D-glucose ([18F]-FDG) positron emission tomography (PET) CT has proven useful in the evaluation of high-grade glioma and is also useful as a predictor of the degree of malignancy in newly diagnosed brain tumors. It is commonly accepted that high-grade gliomas are characterized by increased FDG uptake, whereas the low-grade glioma demonstrates reduced or absent FDG uptake. [18F]-FDOPA is an amino acid PET tracer which is a marker of the proliferative activity of brain tumors and demonstrates positive uptake in all grades of brain tumors; however, the degree of tracer uptake is significantly higher in high-grade tumors as compared to low-grade tumors. Here, we discuss a case where both FDG and DOPA PET/CT scans raised suspicion of low-grade glioma; however, the final histopathology report confirmed WHO grade IV Glioblastoma.

Fibroblast activation protein inhibitor (FAPI) PET/CT is a new tool in the diagnostic workup of cancer. With a growing volume of applications, pitfalls and common findings need to be considered for (68)Ga-FAPI PET/CT image interpretation. The aim of this study was to summarize common findings and report pitfalls in (68)Ga-FAPI PET/CT. Methods: Ninety-one patients underwent whole-body PET/CT with either FAPI-04 (n = 25) or FAPI-46 (n = 66). Findings were rated in a consensus session of 2 experienced readers. Pitfalls and common findings were defined as focal or localized uptake above the background level and categorized as unspecific or nonmalignant and grouped into degenerative, muscular, scarring/wound-healing, uterine, mammary gland, and head-and-neck findings. The frequency of findings was reported on a per-patient and per-group basis, and SUV(max), SUV(mean), and SUV(peak) were measured. Results: Non–tumor-specific uptake was found in 81.3% of patients. The most frequent finding was uptake in degenerative lesions (51.6%), with a mean SUV(max) of 7.7 ± 2.9, and head-and-neck findings (45.1%). Except for the salivary glands, the uptake values did not differ between 10 and 60 min after injection in most findings. Uterine uptake was found in most women (66.7%), with a mean SUV(max) of 12.2 ± 7.3, and uptake correlated negatively with age (SUV(max), r = −0.6, P < 0.01; SUV(peak), r = −0.57, P < 0.01; SUV(mean), r = −0.58, P < 0.01). Conclusion: Pitfalls include non–tumor-specific (68)Ga-FAPI uptake in degenerative lesions, muscle, the head and neck, scarring, the mammary glands, or the uterus. Here, we summarize the findings to help readers avoid common mistakes at centers introducing (68)Ga-FAPI PET/CT.

We report a patient with breast cancer (BC) diagnosed in 2009 with metachronous lymph node, liver, and bone metastases. In 2017, colorectal cancer with peritoneal metastases was additionally diagnosed and treated with 8 cycles of capecitabine due to its antitumor activity against both malignancies. At progression of both diseases, FAPI PET/CT demonstrated positive tumor targeting in BC-related metastases and colorectal cancer-related metastases. The patient received an experimental therapy with 90Y-FAPI46. Although there was similar tracer uptake in the PET/CT, the radioligand therapy resulted in mixed response with disappearance of peritoneal metastases but minor efficacy treating the BC-related metastases.

Diffuse peritoneal and omental infiltration of prostate cancer detected by 18F-PSMA-1007 PET/CT was rarely reported. We report a case of an 80-year-old man who was suspected of prostate carcinoma metastasis and underwent 18F-PSMA-1007 PET/CT for restaging the disease. PET/CT imaging presented intense tracer uptake in the prostate gland, multiple lymph nodes, and bones. Interestingly, we found extremely increased radioactive uptake of diffuse peritoneum and omentum on 18F-PSMA-1007 PET/CT images, which are very rare metastatic sites for prostate cancer.