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The integration of automated whole-body tumor segmentation using 18F-FDG PET/CT images represents a pivotal shift in oncologic diagnostics, enhancing the precision and efficiency of tumor burden assessment. This editorial examines the transition toward automation, propelled by advancements in artificial intelligence, notably through deep learning techniques. We highlight the current availability of commercial tools and the academic efforts that have set the stage for these developments. Further, we comment on the challenges of data diversity, validation needs, and regulatory barriers. The role of metabolic tumor volume and total lesion glycolysis as vital metrics in cancer management underscores the significance of this evaluation. Despite promising progress, we call for increased collaboration across academia, clinical users, and industry to better realize the clinical benefits of automated segmentation, thus helping to streamline workflows and improve patient outcomes in oncology.

OBJECTIVE: Whole-body silicon photomultiplier positron emission tomography (WB SiPM PET) could be used to diagnose breast cancer spread before lumpectomy. We aimed to investigate the method of measuring the tumor size by WB SiPM PET as a basis for diagnosing breast cancer spread in the breast.
METHODS: We retrospectively reviewed 35 breast cancer lesions in 32 patients who underwent WB SiPM PET/CT in the prone position as preoperative breast cancer examinations from September 2020 to March 2022. In all cases, a 20-mm spherical VOI was placed in the normal mammary gland to measure the mean standardised uptake value (SUVmean) and the standard deviation (SD) of 18F-fluorodeoxyglucose (FDG) uptake. We prepared four types of candidates (SUVmean + 2 SD, SUVmean + 3 SD, 1.5 SUVmean + 2 SD, 1.5 SUVmean + 3 SD) for thresholds for delineating tumor contours on PET images. On the semiautomatic viewer soft, the maximum tumor sizes were measured at each of the four thresholds and compared with the pathological tumor sizes, including the extensive intraductal component (EIC).
RESULTS: The lesion detection sensitivity was 97% for WB SiPM PET. PET detected 34 lesions, excluding 4-mm ductal carcinomas in situ (DCIS). PET measurements at the \'1.5 SUVmean + 2 SD\' threshold demonstrated values closest to the pathological tumor sizes, including EIC. Moreover, \'1.5 SUVmean + 2 SD\' had the highest concordance (63%).
CONCLUSIONS: The study demonstrated that among various PET thresholds, the \'1.5 SUVmean + 2 SD\' threshold exhibited the best performance. However, even with this threshold, the concordance rate was limited to only 63%.

We performed a systematic evaluation of the diagnostic performance of LAFOV PET/CT with increasing acquisition time. The first 100 oncologic adult patients referred for 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose PET/CT on the Siemens Biograph Vision Quadra were included. A standard imaging protocol of 10 min was used and scans were reconstructed at 30 s, 60 s, 90 s, 180 s, 300 s, and 600 s. Paired comparisons of quantitative image noise, qualitative image quality, lesion detection, and lesion classification were performed. Image noise (n = 50, 34 women) was acceptable according to the current standard of care (coefficient-of-varianceref < 0.15) after 90 s and improved significantly with increasing acquisition time (PB < 0.001). The same was seen in observer rankings (PB < 0.001). Lesion detection (n = 100, 74 women) improved significantly from 30 s to 90 s (PB < 0.001), 90 s to 180 s (PB = 0.001), and 90 s to 300 s (PB = 0.002), while lesion classification improved from 90 s to 180 s (PB < 0.001), 180 s to 300 s (PB = 0.021), and 90 s to 300 s (PB < 0.001). We observed improved image quality, lesion detection, and lesion classification with increasing acquisition time while maintaining a total scan time of less than 5 min, which demonstrates a potential clinical benefit. Based on these results we recommend a standard imaging acquisition protocol for LAFOV PET/CT of minimum 180 s to maximum 300 s after injection of 3 MBq/kg 2-[18F]fluoro-2-deoxy-D-glucose.

We introduce the Fast Algorithm for Motion Correction (FALCON) software, which allows correction of both rigid and nonlinear motion artifacts in dynamic whole-body (WB) images, irrespective of the PET/CT system or the tracer. Methods: Motion was corrected using affine alignment followed by a diffeomorphic approach to account for nonrigid deformations. In both steps, images were registered using multiscale image alignment. Moreover, the frames suited to successful motion correction were automatically estimated by calculating the initial normalized cross-correlation metric between the reference frame and the other moving frames. To evaluate motion correction performance, WB dynamic image sequences from 3 different PET/CT systems (Biograph mCT, Biograph Vision 600, and uEXPLORER) using 6 different tracers (18F-FDG, 18F-fluciclovine, 68Ga-PSMA, 68Ga-DOTATATE, 11C-Pittsburgh compound B, and 82Rb) were considered. Motion correction accuracy was assessed using 4 different measures: change in volume mismatch between individual WB image volumes to assess gross body motion, change in displacement of a large organ (liver dome) within the torso due to respiration, change in intensity in small tumor nodules due to motion blur, and constancy of activity concentration levels. Results: Motion correction decreased gross body motion artifacts and reduced volume mismatch across dynamic frames by about 50%. Moreover, large-organ motion correction was assessed on the basis of correction of liver dome motion, which was removed entirely in about 70% of all cases. Motion correction also improved tumor intensity, resulting in an average increase in tumor SUVs by 15%. Large deformations seen in gated cardiac 82Rb images were managed without leading to anomalous distortions or substantial intensity changes in the resulting images. Finally, the constancy of activity concentration levels was reasonably preserved (<2% change) in large organs before and after motion correction. Conclusion: FALCON allows fast and accurate correction of rigid and nonrigid WB motion artifacts while being insensitive to scanner hardware or tracer distribution, making it applicable to a wide range of PET imaging scenarios.

BACKGROUND: In patients with increasing PSA and suspicion for prostate cancer, but previous negative biopsies, PET/MRI is used to test for tumours and target potential following biopsy. We aimed to determine different PSMA PET timing effects on signal kinetics and test its correlation with the patients\' PSA and Gleason scores (GS).
METHODS: A total of 100 patients were examined for 900 s using PET/MRI approximately 1-2 h p.i. depending on the tracer used (68Ga-PSMA-11, 18F-PSMA-1007 or 18F-rhPSMA7). The scans were reconstructed in static and dynamic mode (6 equal frames capturing \"late\" PSMA dynamics). TACs were computed for detected lesions as well as linear regression plots against time for static (SUV) and dynamic (SUV, SUL, and percent injected dose per gram) parameters. All computed trends were tested for correlation with PSA and GS.
RESULTS: Static and dynamic scans allowed unchanged lesion detection despite the difference in statistics. For all tracers, the lesions in the pelvic lymph nodes and bones had a mostly negative activity concentration trend (78% and 68%, resp.), while a mostly positive, stronger trend was found for the lesions in the prostate and prostatic fossa following RPE (84% and 83%, resp.). In case of 68Ga-PSMA-11, a strong negative (Rmin = - 0.62, Rmax = - 0.73) correlation was found between the dynamic parameters and the PSA. 18F-PSMA-1007 dynamic data showed no correlation with PSA, while for 18F-rhPSMA7 dynamic data, it was consistently low positive (Rmin = 0.29, Rmax = 0.33). All tracers showed only moderate correlation against GS (Rmin = 0.41, Rmax = 0.48). The static parameters showed weak correlation with PSA (Rmin = 0.24, Rmax = 0.36) and no correlation with GS.
CONCLUSIONS: \"Late\" dynamic PSMA data provided additional insight into the PSMA kinetics. While a stable moderate correlation was found between the PSMA kinetics in pelvic lesions and GS, a significantly variable correlation with the PSA values was shown depending on the radiotracer used, the highest being consistently for 68Ga-PSMA-11. We reason that with such late dynamics, the PSMA kinetics are relatively stable and imaging could even take place at earlier time points as is now in the clinical routine.

The nervous and circulatory system interconnects the various organs of the human body, building hierarchically organized subsystems, enabling fine-tuned, metabolically expensive brain-body and inter-organ crosstalk to appropriately adapt to internal and external demands. A deviation or failure in the function of a single organ or subsystem could trigger unforeseen biases or dysfunctions of the entire network, leading to maladaptive physiological or psychological responses. Therefore, quantifying these networks in healthy individuals and patients may help further our understanding of complex disorders involving body-brain crosstalk. Here we present a generalized framework to automatically estimate metabolic inter-organ connectivity utilizing whole-body functional positron emission tomography (fPET). The developed framework was applied to 16 healthy subjects (mean age ± SD, 25 ± 6 years; 13 female) that underwent one dynamic 18F-FDG PET/CT scan. Multiple procedures of organ segmentation (manual, automatic, circular volumes) and connectivity estimation (polynomial fitting, spatiotemporal filtering, covariance matrices) were compared to provide an optimized thorough overview of the workflow. The proposed approach was able to estimate the metabolic connectivity patterns within brain regions and organs as well as their interactions. Automated organ delineation, but not simplified circular volumes, showed high agreement with manual delineation. Polynomial fitting yielded similar connectivity as spatiotemporal filtering at the individual subject level. Furthermore, connectivity measures and group-level covariance matrices did not match. The strongest brain-body connectivity was observed for the liver and kidneys. The proposed framework offers novel opportunities towards analyzing metabolic function from a systemic, hierarchical perspective in a multitude of physiological pathological states.

Performing 2-[18F]FDG PET/CT in addition to a PSMA-ligand PET/CT can assist in the detection of lesions with low PSMA expression and may help in prognostication and identification of patients who likely benefit from PSMA-radioligand therapy (PSMA-RLT). However, the cost and time needed for a separate PET/CT examination might hinder its routine implementation. In this communication, we present our initial experiences with additional low-dose 2-[18F]FDG PET/CT as part of a dual-tracer and same-day imaging protocol which exploits the higher sensitivity exhibited by long-axial field-of-view (LAFOV) and total-body PET/CT systems and demonstrates its feasibility.
Fourteen patients referred for evaluation for PSMA-RLT received [68 Ga]Ga-PSMA-11 PET/CT at 1 h p.i. with a standard activity of 150 MBq and an additional low-dose 2-[18F]FDG PET/CT with 40 MBq 1 h thereafter using a long-axial field-of-view PET/CT system in a single sitting and as per institutional protocol. Scans were scrutinized by two experienced nuclear medicine physicians for mismatch findings.
The combined protocol identified additional lesions with low or absent PSMA-expression but high FDG-avidity in 1/14 (7%) patients. The protocol was easily implemented and well tolerated by all patients.
Additional low-dose 2-[18F]FDG-PET/CT is feasible as part of a same-day imaging protocol and can help reveal lesions of low PSMA avidity as part of therapy assessment for [177Lu]-PSMA radioligand therapy and demonstrates higher sensitivity compared to [68 Ga]Ga-PSMA-11 PET/CT alone in some patients.

Distinct physiological states arise from complex interactions among the various organs present in the human body. PET is a non-invasive modality with numerous successful applications in oncology, neurology, and cardiology. However, while PET imaging has been applied extensively in detecting focal lesions or diseases, its potential in detecting systemic abnormalities is seldom explored, mostly because total-body imaging was not possible until recently.
In this context, the present study proposes a framework capable of constructing an individual metabolic abnormality network using a subject\'s whole-body 18F-FDG SUV image and a normal control database. The developed framework was evaluated in the patients with lung cancer, the one discharged after suffering from Covid-19 disease, and the one that had gastrointestinal bleeding with the underlying cause unknown.
The framework could successfully capture the deviation of these patients from healthy subjects at the level of both system and organ. The strength of the altered network edges revealed the abnormal metabolic connection between organs. The overall deviation of the network nodes was observed to be highly correlated to the organ SUV measures. Therefore, the molecular connectivity of glucose metabolism was characterized at a single subject level.
The proposed framework represents a significant step toward the use of PET imaging for identifying metabolic dysfunction from a systemic perspective. A better understanding of the underlying biological mechanisms and the physiological interpretation of the interregional connections identified in the present study warrant further research.

In the past years, the gamma-ray detector designs based on the monolithic crystals have demonstrated to be excellent candidates for the design of high-performance PET systems. The monolithic crystals allow to achieve the intrinsic detector resolutions well below state-of-the-art; to increase packing fraction thus, increasing the system sensitivity; and to improve lesion detectability at the edges of the scanner field of view (FOV) because of their intrinsic depth of interaction (DOI) capabilities. The bottleneck to translate to the clinical PET systems based on a large number of monolithic detectors is eventually the requirement of mechanically complex and time-consuming calibration processes. To mitigate this drawback, several methods have been already proposed, such as using non-physically collimated radioactive sources or implementing the neuronal networks (NN) algorithms trained with simulated data. In this work, we aimed to simplify and fasten a calibration process of the monolithic based systems. The Normal procedure consists of individually acquiring a 11 × 11 22Na source array for all the detectors composing the PET system and obtaining the calibration map for each module using a method based on the Voronoi diagrams. Two reducing time methodologies are presented: (i) TEST1, where the calibration map of one detector is estimated and shared among all others, and (ii) TEST2, where the calibration map is slightly modified for each module as a function of their detector uniformity map. The experimental data from a dedicated prostate PET system was used to compare the standard calibration procedure with both the proposed methods. A greater similarity was exhibited between the TEST2 methodology and the Normal procedure; obtaining spatial resolution variances within 0.1 mm error bars and count rate deviations as small as 0.2%. Moreover, the negligible reconstructed image differences (13% deviation at most in the contrast-to-noise ratio) and almost identical contrast values were reported. Therefore, this proposed method allows us to calibrate the PET systems based on the monolithic crystals reducing the calibration time by approximately 80% compared with the Normal procedure.