Search

Cystic fibrosis (CF) is a genetic disorder characterized by recurrent airway infections, inflammation, impaired mucociliary clearance, and progressive decline in lung function. The disease may start in the small airways; however, this is difficult to prove due to the limited accessibility of the small airways with the current single-photon mucociliary clearance assay. Here, we developed a dynamic positron emission tomography assay with high spatial and temporal resolution. We tested that mucociliary clearance is abnormal in the small airways of newborn cystic fibrosis pigs. Clearance of [ 68 Ga]-tagged macroaggregated albumin from small airways started immediately after delivery and continued for the duration of the study. Initial clearance was fast but slowed down a few minutes after delivery. Cystic fibrosis pigs' small airways cleared significantly less than non-CF pigs' small airways (non-CF 25.1 ± 3.1% vs. CF 14.6 ± 0.1%). Stimulation of the cystic fibrosis airways with the purinergic secretagogue uridine-5'-triphosphate (UTP) further impaired clearance (non-CF with UTP 20.9 ± 0.3% vs. CF with UTP 13.0 ± 1.8%). None of the cystic fibrosis pigs treated with UTP ( n = 6) cleared more than 20% of the delivered dose. These data indicate that mucociliary clearance in the small airways is fast and can easily be missed if the assay is not sensitive enough. The data also indicate that mucociliary clearance is impaired in the small airways of cystic fibrosis pigs. This defect is exacerbated by stimulation of mucus secretions with purinergic agonists. NEW & NOTEWORTHY We developed a novel positron emission tomography scan assay with unprecedented temporal and spatial resolution to measure mucociliary clearance in the small airways. We proved a long-standing but unproven assertion that mucociliary clearance is inherently abnormal in the small airways of newborn cystic fibrosis piglets that are otherwise free of infection or inflammation. This technique can be easily extended to other airway diseases such as asthma, idiopathic pulmonary fibrosis, or chronic obstructive pulmonary disease.

The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical use. Drawing on the traditional principles of medical and research ethics, and highlighting the need to ensure health justice, the AI task force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks: privacy of data subjects, data quality and model efficacy, fairness toward marginalized populations, and transparency of clinical performance. We provide preliminary recommendations to developers of AI-driven medical devices for mitigating the impact of these risks on patients and populations., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

The deployment of artificial intelligence (AI) has the potential to make nuclear medicine and medical imaging faster, cheaper, and both more effective and more accessible. This is possible, however, only if clinicians and patients feel that these AI medical devices (AIMDs) are trustworthy. Highlighting the need to ensure health justice by fairly distributing benefits and burdens while respecting individual patients' rights, the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks that arise during the deployment of AIMD: autonomy of patients and clinicians, transparency of clinical performance and limitations, fairness toward marginalized populations, and accountability of physicians and developers. We provide preliminary recommendations for governing these ethical risks to realize the promise of AIMD for patients and populations., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

There has been significant recent interest in understanding both the frequency of nuclear medicine injection infiltration and the potential for negative impact, including skin injury. However, no large-scale study has yet correlated visualized injection site activity with actual activity measurement of an infiltrate. Additionally, current skin dosimetry approaches lack sufficient detail to account for critical factors that impact the dose to the radiosensitive epidermis. Methods: From 10 imaging sites, 1,000 PET/CT patient studies were retrospectively collected. At each site, consecutive patients with the injection site in the field of view were used. The radiopharmaceutical, injected activity, time of injection and imaging, injection site, and injection method were recorded. Net injection site activity was calculated from volumes of interest. Monte Carlo image-based absorbed dose calculations were performed using the actual geometry from a patient with a minor infiltration. The simulation model used an activity distribution in the skin microanatomy based on known properties of subcutaneous fat, dermis, and epidermis. Simulations using several subcutaneous fat-to-dermis concentration ratios were performed. Absorbed dose to the epidermis, dermis, and fat were calculated along with relative γ- and β-contributions, and these findings were extrapolated to a hypothetical worst-case (470 MBq) full-injection infiltration. Results: Only 6 of 1,000 patients had activity at the injection site in excess of 370 kBq (10 μCi), with no activities greater than 1.7 MBq (45 μCi). In 460 of 1,000 patients, activity at the injection site was clearly visualized. However, quantitative assessment of activities averaged only 34 kBq (0.9 μCi), representing 0.008% of the injected activity. Calculations for the extrapolated 470-MBq infiltration resulted in a hypothetical absorbed dose to the epidermis of below 1 Gy, a factor of 2 lower than what is required for deterministic skin reactions. Analysis of the dose distribution demonstrates that the dermis acts as a β-shield for the radiation-sensitive epidermis. Dermal shielding is highly effective for low-energy 18 F positrons but less so with the higher-energy positrons of 68 Ga. Conclusion: When quantitative activity measurement criteria are used rather than visual, the frequency of PET infiltration appears substantially below frequencies previously published. Shallow doses to the epidermis from infiltration events are also likely substantially lower than previously reported because of absorption of β-particles in the dermis., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Historically, patient datasets have been used to develop and validate various reconstruction algorithms for PET/MRI and PET/CT. To enable such algorithm development, without the need for acquiring hundreds of patient exams, in this article we demonstrate a deep learning technique to generate synthetic but realistic whole-body PET sinograms from abundantly available whole-body MRI. Specifically, we use a dataset of 56 18 F-FDG-PET/MRI exams to train a 3-D residual UNet to predict physiologic PET uptake from whole-body T1-weighted MRI. In training, we implemented a balanced loss function to generate realistic uptake across a large dynamic range and computed losses along tomographic lines of response to mimic the PET acquisition. The predicted PET images are forward projected to produce synthetic PET (sPET) time-of-flight (ToF) sinograms that can be used with vendor-provided PET reconstruction algorithms, including using CT-based attenuation correction (CTAC) and MR-based attenuation correction (MRAC). The resulting synthetic data recapitulates physiologic 18 F-FDG uptake, e.g., high uptake localized to the brain and bladder, as well as uptake in liver, kidneys, heart, and muscle. To simulate abnormalities with high uptake, we also insert synthetic lesions. We demonstrate that this sPET data can be used interchangeably with real PET data for the PET quantification task of comparing CTAC and MRAC methods, achieving ≤ 7.6% error in mean-SUV compared to using real data. These results together show that the proposed sPET data pipeline can be reasonably used for development, evaluation, and validation of PET/MRI reconstruction methods.

Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of health care. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We envision a road map for the establishment of trustworthy AI ecosystems in nuclear medicine. In this report, AI is contextualized in the history of technologic revolutions. Opportunities for AI applications in nuclear medicine related to diagnosis, therapy, and workflow efficiency, as well as emerging challenges and critical responsibilities, are discussed. Establishing and maintaining leadership in AI require a concerted effort to promote the rational and safe deployment of this innovative technology by engaging patients, nuclear medicine physicians, scientists, technologists, and referring providers, among other stakeholders, while protecting our patients and society. This strategic plan was prepared by the AI task force of the Society of Nuclear Medicine and Molecular Imaging., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18 F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

An important need exists for strategies to perform rigorous objective clinical-task-based evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we propose a 4-class framework to evaluate AI algorithms for promise, technical task-specific efficacy, clinical decision making, and postdeployment efficacy. We provide best practices to evaluate AI algorithms for each of these classes. Each class of evaluation yields a claim that provides a descriptive performance of the AI algorithm. Key best practices are tabulated as the RELAINCE (Recommendations for EvaLuation of AI for NuClear medicinE) guidelines. The report was prepared by the Society of Nuclear Medicine and Molecular Imaging AI Task Force Evaluation team, which consisted of nuclear-medicine physicians, physicists, computational imaging scientists, and representatives from industry and regulatory agencies., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

Molecular tumor volume (MTV) is a parameter of interest in prostate cancer for assessing total disease burden on prostate-specific membrane antigen (PSMA) PET. Although software segmentation tools can delineate whole-body MTV, a necessary step toward meaningful monitoring of total tumor burden and treatment response through PET is establishing the repeatability of these metrics. The present study assessed the repeatability of total MTV and related metrics for 68 Ga-PSMA-HBED-CC in prostate cancer. Methods: Eighteen patients from a prior repeatability study who underwent 2 test-retest PSMA PET/CT scans within a mean interval of 5 d were reanalyzed. Within-subject coefficient of variation and repeatability coefficients (RCs) were analyzed on a per-lesion and per-patient basis. For the per-lesion analysis, individual lesions were segmented for analysis by a single reader. For the per-patient analysis, subgroups of up to 10 lesions (single reader) and the total tumor volume per patient were segmented (independently by 2 readers). Image parameters were MTV, SUV max , SUV peak , SUV mean , total lesion PSMA, and the related metric PSMA quotient (which integrates lesion volume and PSMA avidity). Results: In total, 192 segmentations were analyzed for the per-lesion analysis and 1,662 segmentations for the per-patient analysis (combining the 2 readers and 2 scans). The RC of the MTV of single lesions was 77% (95% CI, 63%-96%). The RC improved to 33% after aggregation of up to 10 manually selected lesions into subgroups assessed per patient (95% CI, 25%-46%). The RC of the semiautomatic MTV total (the sum of all voxels in the whole-body total tumor segmentation per patient) was 35% (95% CI, 25%-50%), the Bland-Altman bias was -6.70 (95% CI, -14.32-0.93). Alternating readers between scans led to a comparable RC of 37% (95% CI, 28%-49%) for MTV total , meaning that the metric is robust between scanning sessions and between readers. Conclusion: 68 Ga-PSMA-HBED-CC PET-derived semiautomatic MTV total is repeatable and reader-independent, with a change of ±35% representing a true change in tumor volume. Volumetry of single manually selected lesions has considerably lower repeatability, and volumetry based on subgroups of these lesions, although showing acceptable repeatability, is less systematic. The semiautomatic analysis of MTV total used in this study offers an efficient and robust means of assessing response to therapy., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

For multicenter clinical studies, characterizing the robustness of image-derived radiomics features is essential. Features calculated on PET images have been shown to be very sensitive to image noise. The purpose of this work was to investigate the efficacy of a relatively simple harmonization strategy on feature robustness and agreement. A purpose-built texture pattern phantom was scanned on 10 different PET scanners in 7 institutions with various different image acquisition and reconstruction protocols. An image harmonization technique based on equalizing a contrast-to-noise ratio was employed to generate a "harmonized" alongside a "standard" dataset for a reproducibility study. In addition, a repeatability study was performed with images from a single PET scanner of variable image noise, varying the binning time of the reconstruction. Feature agreement was measured using the intraclass correlation coefficient (ICC). In the repeatability study, 81/93 features had a lower ICC on the images with the highest image noise as compared to the images with the lowest image noise. Using the harmonized dataset significantly improved the feature agreement for five of the six investigated feature classes over the standard dataset. For three feature classes, high feature agreement corresponded with higher sensitivity to the different patterns, suggesting a way to select suitable features for predictive models.

The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations on technical best practices for developing AI algorithms in nuclear medicine are provided, beginning with general recommendations and then continuing with descriptions of how one might practice these principles for specific topics within nuclear medicine. This report was produced by the AI Task Force of the Society of Nuclear Medicine and Molecular Imaging., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: The purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation in computed tomography (CT) scans to enable the quantification of active pelvic bone marrow by means of Fluorothymidine F-18 (FLT) tracer uptake measurement in positron emission tomography (PET) scans. This quantification is a critical step in calculating bone marrow dose for radiopharmaceutical therapy clinical applications as well as external beam radiation doses., Methods: An approach for the combined localization and segmentation of the pelvis in CT volumes of varying sizes, ranging from full-body to pelvis CT scans, was developed that utilizes a novel CNN architecture in combination with a random sampling strategy. The method was validated on 34 planning CT scans and 106 full-body FLT PET-CT scans using a cross-validation strategy. Specifically, two different training and CNN application options were studied, quantitatively assessed, and statistically compared., Results: The proposed method was able to successfully locate and segment the pelvis in all test cases. On all data sets, an average Dice coefficient of 0.9396 ± $\pm$ 0.0182 or better was achieved. The relative tracer uptake measurement error ranged between 0.065% and 0.204%. The proposed approach is time-efficient and shows a reduction in runtime of up to 95% compared to a standard U-Net-based approach without a localization component., Conclusions: The proposed method enables the efficient calculation of FLT uptake in the pelvis. Thus, it represents a valuable tool to facilitate bone marrow preserving adaptive radiation therapy and radiopharmaceutical dose calculation. Furthermore, the method can be adapted to process other bone structures as well as organs., (© 2022 American Association of Physicists in Medicine.)

Objective: Simultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems., Method: The NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3-7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUV mean , SUV max and SUV peak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction., Results: The range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRC mean , 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRC max , 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRC peak , 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively., Conclusions: For two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters., (© 2021. The Author(s).)

Rational: To validate a population-based input function (PBIF) model that alleviates the need for scanning since injection time in dynamic whole-body (WBdyn) PET. Methods: Thirty-seven patients with suspected/known well-differentiated neuroendocrine tumors were included (GAPETNET trial NTC03576040). All WBdyn 68Ga-DOTATOC-PET/CT acquisitions were performed on a digital PET system (one heart-centered 6 min-step followed by nine WB-passes). The PBIF model was built from 20 image-derived input functions (IDIFs) obtained from a respective number of patients' WBdyn exams using an automated left-ventricle segmentation tool. All IDIF peaks were aligned to the median time-to-peak, normalized to patient weight and administrated activity, and then fitted to an exponential model function. PBIF was then applied to 17 independent patient studies by scaling it to match the respective IDIF section at 20-55 min post-injection time windows corresponding to WB-passes 3-7. The ratio of area under the curves (AUCs) of IDIFs and PBIF3-7 were compared using a Bland--Altman analysis (mean bias ± SD). The Patlakestimated mean Ki for physiological uptake (Ki-liver and Ki-spleen) and tumor lesions (Ki-tumor) using either IDIF or PBIF were also compared. Results: The mean AUC ratio (PBIF/IDIF) was 0.98 ± 0.06. The mean Ki bias between PBIF3-7 and IDIF was -2.6 ± 6.2% (confidence interval, CI: -5.8; 0.6). For Ki-spleen and Ki-tumor, low relative bias with low SD were found [4.65 ± 7.59% (CI: 0.26; 9.03) and 3.70 ± 8.29% (CI: -1.09; 8.49) respectively]. For Ki-liver analysis, relative bias and SD were slightly higher [7.43 ± 13.13% (CI: -0.15; 15.01)]. Conclusion: Our study showed that the PBIF approach allows for reduction in WBdyn DOTATOC-PET/CT acquisition times with a minimum gain of 20 min. [ABSTRACT FROM AUTHOR]

Interest and research into radiopharmaceutical extravasation concepts has risen with the increase in use of radiopharmaceutical therapies, growing access to novel molecular imaging agents, and recent regulatory controversies. This minireview will examine the literature of the last twenty years to summarize the history of radiopharmaceutical extravasations, determine key trends in imaging and therapies, and highlight critical gaps in research that currently exist. The intent of this work is to provide a summary of this complex topic that helps build awareness and promotes new innovations in this interesting aspect of theranostic radiopharmaceuticals. [ABSTRACT FROM AUTHOR]

Introduction: Pediatric patients have an increased risk of radiation-induced malignancies due to their ongoing development and long remaining life span. Thus, optimization of PET protocols is an important task in pediatric nuclear medicine. Long axial field-of-view (LAFOV) PET/CT has shown a significant increase in sensitivity, which provides an ideal opportunity for reduction of injected tracer activity in the pediatric population. In this study we aim to evaluate the clinical performance of a 2-[18F]FDG-tracer reduction from 3 MBq/kg to 1.5 MBq/kg on the Biograph Vision Quadra LAFOV PET/CT. Materials and methods: The first 50 pediatric patients referred for clinical whole-body PET/CT with 1.5 MBq/kg 2-[18F]FDG, were included. A standard pediatric protocol was applied. Five reconstructions were created with various time, filter and iteration settings. Image noise was computed as coefficient-of-variance (COV = SD/mean standardized-uptake-value) calculated from a spherical 20-50 mm (diameter) liver volume-of-interest. Sets of reconstructions were reviewed by one nuclear medicine physicians, who reported image lesions on a pre-defined list of sites. Paired comparison analysis was performed with significance at PB< 0.05 (Bonferroni corrected). Results: All reconstructions, except one, achieved a COVmean (0.08-0.15) equal to or lower than current clinical acceptable values (COVref ≤ 0.15). Image noise significantly improved with increasing acquisition time, lowering iterations (i) from 6i to 4i (both with five subsets) and when applying a 2 mm Gauss filter (PB< 0.001). Significant difference in lesion detection was seen from 150s to 300s and from 150s to 600s (PB = 0.006-0.007). 99% of all lesions rated as malignant could be found on the 150s reconstruction, while 100% was found on the 300s, when compared to the 600s reconstruction. Conclusion: Injected activity and scan time can be reduced to 1.5 MBq/kg 2-[18F] FDG with 5 min acquisition time on LAFOV PET/CT, while maintaining clinical performance in the pediatric population. These results can help limit radiation exposure to patients and personnel as well as shorten total scan time, which can help increase patient comfort, lessen the need for sedation and provide individually tailored scans. [ABSTRACT FROM AUTHOR]

Introduction: Pediatric patients have an increased risk of radiation-induced malignancies due to their ongoing development and long remaining life span. Thus, optimization of PET protocols is an important task in pediatric nuclear medicine. Long axial field-of-view (LAFOV) PET/CT has shown a significant increase in sensitivity, which provides an ideal opportunity for reduction of injected tracer activity in the pediatric population. In this study we aim to evaluate the clinical performance of a 2-[18F]FDG-tracer reduction from 3 MBq/kg to 1.5 MBq/kg on the Biograph Vision Quadra LAFOV PET/CT. Materials and methods: The first 50 pediatric patients referred for clinical whole-body PET/CT with 1.5 MBq/kg 2-[18F]FDG, were included. A standard pediatric protocol was applied. Five reconstructions were created with various time, filter and iteration settings. Image noise was computed as coefficient-ofvariance (COV = SD/mean standardized-uptake-value) calculated from a spherical 20-50 mm (diameter) liver volume-of-interest. Sets of reconstructions were reviewed by one nuclear medicine physicians, who reported image lesions on a pre-defined list of sites. Paired comparison analysis was performed with significance at PB < 0.05 (Bonferroni corrected). Results: All reconstructions, except one, achieved a COVmean (0.08-0.15) equal to or lower than current clinical acceptable values (COVref = 0.15). Image noise significantly improved with increasing acquisition time, lowering iterations (i) from 6i to 4i (both with five subsets) and when applying a 2 mm Gauss filter (PB < 0.001). Significant difference in lesion detection was seen from 150s to 300s and from 150s to 600s (PB = 0.006-0.007). 99% of all lesions rated as malignant could be found on the 150s reconstruction, while 100% was found on the 300s, when compared to the 600s reconstruction. Conclusion: Injected activity and scan time can be reduced to 1.5 MBq/kg 2-[18F] FDG with 5 min acquisition time on LAFOV PET/CT, while maintaining clinical performance in the pediatric population. These results can help limit radiation exposure to patients and personnel as well as shorten total scan time, which can help increase patient comfort, lessen the need for sedation and provide individually tailored scans. [ABSTRACT FROM AUTHOR]

Copper (Cu) is used as a cofactor in all organisms, and yet it can be toxic at high intracellular concentrations, causing cell death. Diethyldithiocarbamate (DDC) is a Cu ionophore that can transport Cu effectively into the cell. Copper-diethyldithiocarbamate (Cu-DDC) can treat prostate cancer (PCa) and may correlate with the cell death process. However, the specific Cu-DDC-related cell death genes in PCa are still unknown. Information about the Cu-DDC-related cell death genes was obtained from a previous study. Concurrently, the RNA expression profiles and clinical data were downloaded from public databases such as GEO, TCGA, and CPGEA. Using data from TCGA database, the logistic and lasso regression models were generated using R software. The influence of these genes in affecting PCa progression and prognosis was analyzed. Finally, the expression of these genes was verified in clinical samples. We found five Cu-DDC-related cell death genes associated with the occurrence of PCa from GSE35988, a gene dataset, namely, CDKN2A, PRC1, CDK1, SOX2, and ZNF365. CDKN2A, PRC1, and CDK1 are known to influence PCa patients' disease-free survival (DFS) status and were overexpressed, whereas SOX2 and ZNF365 were under-expressed in PCa in the different databases. Some of these genes can affect PCa progression. Consistent with the database results, the mRNA and protein expression of CDKN2A, PRC1, and CDK1 was also higher in clinical samples. In conclusion, we identified five hub genes which are important for Cu-DDC-related cell death process that can predict the development of PCa. [ABSTRACT FROM AUTHOR]

Chronic pain is highly prevalent and burdensome, affecting millions of people worldwide. Although it emerges at any point in life, it often manifests in adolescence. Given that adolescence is a unique developmental period, additional strains associated with persistent and often idiopathic pain lead to significant long-term consequences. While there is no singular cause for the chronification of pain, epigenetic modifications that lead to neural reorganization may underpin central sensitization and subsequent manifestation of pain hypersensitivity. Epigenetic processes are particularly active during the prenatal and early postnatal years. We demonstrate how exposure to various traumas, such as intimate partner violence while in utero or adverse childhood experiences, can significantly influence epigenetic regulation within the brain and in turn modify pain-related processes. We provide compelling evidence that the burden of chronic pain is likely initiated early in life, often being transmitted from mother to offspring. We also highlight two promising prophylactic strategies, oxytocin administration and probiotic use, that have the potential to attenuate the epigenetic consequences of early adversity. Overall, we advance understanding of the causal relationship between trauma and adolescent chronic pain by highlighting epigenetic mechanisms that underlie this transmission of risk, ultimately informing how to prevent this rising epidemic. [ABSTRACT FROM AUTHOR]

Background: [18F]FDG PET denoising by SubtlePET™ using deep learning artificial intelligence (AI) was previously found to induce slight modifications in lesion and reference organs' quantification and in lesion detection. As a next step, we aimed to evaluate its clinical impact on [18F]FDG PET solid tumour treatment response assessments, while comparing "standard PET" to "AI denoised half-duration PET" ("AI PET") during follow-up. Results: 110 patients referred for baseline and follow-up standard digital [18F]FDG PET/CT were prospectively included. "Standard" EORTC and, if applicable, PERCIST response classifications by 2 readers between baseline standard PET1 and follow-up standard PET2 as a "gold standard" were compared to "mixed" classifications between standard PET1 and AI PET2 (group 1; n = 64), or between AI PET1 and standard PET2 (group 2; n = 46). Separate classifications were established using either standardized uptake values from ultra-high definition PET with or without AI denoising (simplified to "UHD") or EANM research limited v2 (EARL2)-compliant values (by Gaussian filtering in standard PET and using the same filter in AI PET). Overall, pooling both study groups, in 11/110 (10%) patients at least one EORTCUHD or EARL2 or PERCISTUHD or EARL2 mixed vs. standard classification was discordant, with 369/397 (93%) concordant classifications, unweighted Cohen's kappa = 0.86 (95% CI: 0.78–0.94). These modified mixed vs. standard classifications could have impacted management in 2% of patients. Conclusions: Although comparing similar PET images is preferable for therapy response assessment, the comparison between a standard [18F]FDG PET and an AI denoised half-duration PET is feasible and seems clinically satisfactory. [ABSTRACT FROM AUTHOR]

Introduction: Data acquisition and image reconstruction protocols affect image quality and quantification accuracy in PET imaging. We aimed to standardize and optimize image acquisition, and reconstruction parameter sets using a simultaneous quantitative and qualitative assessment framework for a lutetium oxyorthosilicate (LSO)-based PET/CT scanner. Methods: The NEMA IEC Body Phantom acquisition was performed in list mode for 10 minutes with four spheres to background ratios (SBRs). Raw PET data were reconstructed using 60 different protocols. Image quality was evaluated for standardization using contrast, CNR, and noise. Recovery coefficient (RC) measurements were performed for different common VOI definitions. Results: No significant differences were observed between RCs for various acquisition durations. The contrast to noise ratio (CNR) increased at all SBRs by expanding the acquisition duration from 60 to 600 seconds. PET scan time was reduced to 90 seconds per bed position while preserving image quality. Up to 50% improvement in CNR for the highest sub-iteration with a high level of smoothing was observed. PSF-based reconstruction produced a positive bias of RCmax in high SBRs (8 and 10) using higher sub-iterations (30 to 60) with Gaussian filters less than 6 mm FWHM. Moreover, a Sub-iteration of more than 32 with a 4-6 mm FWHM Gaussian filter provides optimized reconstruction sets. Conclusion: Our study demonstrates it would be feasible for PET image acquisition and reconstruction settings to simultaneously allow optimal lesion detection with high image quality while providing accurate quantification. [ABSTRACT FROM AUTHOR]

Background: Practice effects on cognitive testing in mild cognitive impairment (MCI) and Alzheimer's disease (AD) remain understudied, especially with how they compare to biomarkers of AD. Objective: The current study sought to add to this growing literature. Methods: Cognitively intact older adults (n = 68), those with amnestic MCI (n = 52), and those with mild AD (n = 45) completed a brief battery of cognitive tests at baseline and again after one week, and they also completed a baseline amyloid PET scan, a baseline MRI, and a baseline blood draw to obtain APOE ɛ4 status. Results: The intact participants showed significantly larger baseline cognitive scores and practice effects than the other two groups on overall composite measures. Those with MCI showed significantly larger baseline scores and practice effects than AD participants on the composite. For amyloid deposition, the intact participants had significantly less tracer uptake, whereas MCI and AD participants were comparable. For total hippocampal volumes, all three groups were significantly different in the expected direction (intact > MCI > AD). For APOE ɛ4, the intact had significantly fewer copies of ɛ4 than MCI and AD. The effect sizes of the baseline cognitive scores and practice effects were comparable, and they were significantly larger than effect sizes of biomarkers in 7 of the 9 comparisons. Conclusion: Baseline cognition and short-term practice effects appear to be sensitive markers in late life cognitive disorders, as they separated groups better than commonly-used biomarkers in AD. Further development of baseline cognition and short-term practice effects as tools for clinical diagnosis, prognostic indication, and enrichment of clinical trials seems warranted. [ABSTRACT FROM AUTHOR]

Background: Pancreatic neuroendocrine tumors (P-NETs) constitute a subset of pancreatic mass lesions characterized by diverse clinical presentations. Despite their inherent malignant potential, the timely identification and treatment of these tumors are critical for achieving favorable clinical outcomes. This study aims to shed light on the heterogeneous tumor biology of P-NETs and the management strategies employed at a tertiary care center in Pakistan. Method: A retrospective study encompassing all patients with a biopsy-confirmed diagnosis of P-NETs at Shifa International Hospital between January 1st, 2016, and June 30th, 2021, was conducted. Meticulous data extraction from pathology records and thorough searches of medical records were performed to gather relevant demographic and clinical information. Results: A total of 24 patients were retrieved from our database, with 13 (54%) female patients. The mean age was 49.5 ± 16.3 years. Eight out of the 24 patients presented with abdominal pain. Most patients (14 out of 24) had lesions in the pancreatic head region. In three cases, lesions exhibited multicentricity. The mean lesion size measured 4.4 ± 2.3 cm. Three of the 24 patients displayed distant liver metastasis at the presentation time. 19 out of the 24 patients underwent surgical resections, while endoscopic ultrasound (EUS)-guided biopsy was performed in 4 out of 24 cases. EUS-guided tissue biopsy yielded accurate diagnoses in all four cases. Conclusion: Most P-NETs are non-functional, and there is an almost equal distribution between male and female patients. Solitary lesions predominate, and metastasis is uncommon at initial presentation. EUS-guided fine needle biopsy stands out as a dependable diagnostic modality for P-NETs. [ABSTRACT FROM AUTHOR]

Background: Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases. Methods: For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment. Results: The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and − 16.3% for SUVmax, and 21.2% and − 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak. Conclusion: In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response. [ABSTRACT FROM AUTHOR]

Objective approaches to treatment. [ABSTRACT FROM AUTHOR]

Background: Studying biomarkers in children with temporomandibular disorders (TMD) such as epinephrine, norepinephrine, and dopamine may reveal factors like screen time or sleep loss that affect these biomarkers and predict TMD-related pain, offering new research opportunities., Aim: To determine the association between stress and catecholamines with myofascial pain and headache related to TMD in children., Design: Sixty-six 9- to 11-year-old children assisting at the clinics of Pediatric Dentistry of Universidad CES participated in the study. Myofascial pain and headache attributed to TMD were determined according to the Diagnostic Criteria for TMD (DC/TMD) Axis I. Stress was evaluated with the Perceived Stress Scale-Children (PSS-C), and a 24-h urine sample was analyzed using liquid chromatography to assay catecholamines. Single and multiple regression analyses were performed., Results: Children with a mean age of 10.3 years participated in the study. The mean score of stress was 29 ± 4. Perceived stress, dopamine, epinephrine, and norepinephrine were statistically significant predictors of myofascial pain and headache attributed to TMD in the single- and multiple variable logistic regression analyses., Conclusion: Stressful states and its biological biomarkers increase the probability of developing myofascial pain and headache attributed to TMD in children., (© 2024 BSPD, IAPD and John Wiley & Sons Ltd.)

Background: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation. Methods: PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789). Results: In 20,887 screened references, 79 articles (82.5% in 2017–2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5–52,000, median 21) and large-span sample size (range 80–3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively. Conclusion: AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field. [ABSTRACT FROM AUTHOR]

Circulating tumor DNA (ctDNA), which circulates in the blood after being shed from cancer cells in the body, has recently gained attention as an excellent tumor marker. The purpose of this study was to evaluate whether ct human papillomavirus (HPV) 16 DNA (ctHPV16DNA) levels were associated with quantitative PET parameters in patients with HPV-positive head and neck (HN) squamous cell carcinoma (SCC). Fifty patients with oropharyngeal SCC (OPSCC) and 5 with SCC of unknown primary (SCCUP) before treatment were included. They all underwent blood sampling to test ctHPV16DNA levels and FDG PET-CT examinations. Quantitative PET parameters included SUVmax, metabolic tumor volume (MTV), MTV of whole-body lesions (wbMTV), and 56 texture features. ctHPV16DNA levels were compared to texture features of primary tumors in OPSCC patients (Group A) or the largest primary or metastatic lymph node lesions in OPSCC and SCCUP patients (Group B) and to other PET parameters. Spearman rank correlation test and multiple regression analysis were used to confirm the associations between ctHPV16DNA levels and PET parameters. ctHPV16DNA levels moderately correlated with wbMTV, but not with SUVmax or MTV in Groups A and B. ctHPV16DNA levels exhibited a weak negative correlation with low gray-level zone emphasis in Groups A and B. Multiple regression analysis revealed that wbMTV and high gray-level zone emphasis were the significant factors for ctHPV16DNA levels in Group B. These results were not observed in Group A. This study demonstrated that ctHPV16DNA levels correlated with the whole-body tumor burden and tumor heterogeneity visualized on FDG PET-CT in patients with HPV-positive HNSCC. [ABSTRACT FROM AUTHOR]

Introduction: Functional informaton is introduced as the mechanism to adapt cancer therapies uniquely to individual patients based on changes defined by qualified tumor biomarkers. Methods: To demonstrate the methodology, a tumor volume biomarker model, characterized by a tumor volume reduction rate coefficient, is used to adapt a tumor cell survival bioresponse radiotherapy model in terms of therapeutic radiation dose. Tumor volume, acquired from imaging data, serves as a surrogate measurement for tumor cell death, but the biomarker model derived from this data cannot be used to calculate the radiation dose absorbed by the target tumor. However, functional information does provide a mathematical connection between the tumor volume biomarker model and the tumor cell survival bioresponse model by quantifying both data sets in the units of information, thus creating an analytic conduit from bioresponse to biomarker. Results: The information guided process for individualized dose adaptations using information values acquired from the tumor cell survival bioresponse model and the tumor volume biomarker model are presented in detailed form by flowchart and tabular data. Clinical data are used to generate a presentation that assists investigator application of the information guided methodology to adaptive cancer therapy research. Conclusions: Information guided adaptation of bioresponse using surrogate data is extensible across multiple research fields because functional information mathematically connects disparate bioresponse and biomarker data sets. Thus, functional information offers adaptive cancer therapy by mathematically connecting immunotherapy, chemotherapy, and radiotherapy cancer treatment processes to implement individualized treatment plans. [ABSTRACT FROM AUTHOR]

Background: Chronic postsurgical pain (CPP) markedly impairs patients' quality of life. Research has shown that chronic stress may extend incisional nociception in male mice. Dopaminergic (DAergic) neurons in the ventral tegmental area (VTA) are integral to stress-related mental disorders (including major depressive disorder, anxiety disorders, and PTSD) and pain. However, the impact of chronic social defeat stress (CSDS) on mesolimbic dopamine (DA) transmission in the development of CPP is yet to be established. It remains uncertain whether the dopamine signals in the rostral anterior cingulate cortex (rACC), which regulate pain, derive from the VTA. This study aims to explore the role of VTA-rACC dopaminergic circuits in a mouse model of CPP induced by CSDS. Methods: We conducted CSDS on C57BL/6 J wild-type male mice (n = 12–16 mice/group) and DAT-cre male mice (n = 10–12 mice/group). After 10 days of CSDS, a left posterior plantar incision was made to establish a mouse model of CPP. Paw withdrawal thresholds (PWTs) were evaluated using Von-Frey fibre stimulation. The open field test (OFT) and elevated plus maze test (EPM) were used to assess pain-related negative emotions. We used immunofluorescence staining and Western Blot to analyse D1, D2, c-Fos, and TH expression. DAergic fibre projections in the VTA-rACC neural pathway were traced using retrograde tracing and immunofluorescence staining. Optogenetics and Chemogenetics were employed to manipulate DAergic neurons in the VTA and their axons in the rACC. Results: The ipsilateral PWTs in male C57BL/6 J mice significantly decreased after surgery, returning to baseline after seven days. Conversely, in CSDS mice, ipsilateral PWTs remained reduced for at least 30 days post-incision. A significant reduction in TH-positive neurons expressing c-Fos in the VTA of CPP mice was observed 15 days post-incision. Activating DAergic neurons significantly improved ipsilateral PWTs and locomotor performance in the OFT and EPM in CPP mice post-incision. Additionally, D1 expression in the rACC was found to decrease in CPP mice, and this reduction counteracted the increase in PWTs caused by activating DAergic neuron axon terminals in the rACC. Conclusion: CSDS results in chronicity of postsurgical nociception and anxiety-like negative emotions, with alterations in DA transmission playing a role in CPP. Specific activation of DAergic neurons mitigates nociceptive responses and anxiety-like bahaviors, possibly mediated by D1 receptors in the rACC. [ABSTRACT FROM AUTHOR]

PET/CT and radioisotope therapy are diagnostic and therapeutic arms of Nuclear Medicine, respectively. With the emergence of better technology, PET/CT has become an accessible modality. Diagnostic tracers exploring diseasespecific targets has led the clinicians to look beyond FDG PET. Moreover, with the emergence of theranostic pairs of radiopharmaceuticals, radioisotope therapy is gradually making it's way into treatment algorithm of common cancers in India. We therefore would like to discuss in detail the updates in PET/CT imaging and radionuclide therapy and generate a consensus-driven evidence based document which would guide the practitioners of Oncology. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The standardized uptake value ratio (SUVR) is used to measure amyloid beta–positron emission tomography (Aβ‐PET) uptake in the brainDifferences in PET scanner technologies and image reconstruction techniques can lead to variability in PET images across scanners. This poses a challenge for Aβ‐PET studies conducted in multiple centers. The aim of harmonization is to achieve consistent Aβ‐PET measurements across different scanners. In this study, we propose an Aβ‐PET harmonization method of matching spatial resolution, as measured via a barrel phantom, across PET scanners. Our approach was validated using paired subject data, for which patients were imaged on multiple scanners. METHODS: In this study, three different PET scanners were evaluated: the Siemens Biograph Vision 600, Siemens Biograph molecular computed tomography (mCT), and Philips Gemini TF64. A total of five, eight, and five subjects were each scanned twice with [18F]‐NAV4694 across Vision‐mCT, mCT‐Philips, and Vision‐Philips scanner pairs. The Vision and mCT scans were reconstructed using various iterations, subsets, and post‐reconstruction Gaussian smoothing, whereas only one reconstruction configuration was used for the Philips scans. The full‐width at half‐maximum (FWHM) of each reconstruction configuration was calculated using [18F]‐filled barrel phantom scans with the Society of Nuclear Medicine and Molecular Imaging (SNMMI) phantom analysis toolkit. Regional SUVRs were calculated from 72 brain regions using the automated anatomical labelling atlas 3 (AAL3) atlas for each subject and reconstruction configuration. Statistical similarity between SUVRs was assessed using paired (within subject) t‐tests for each pair of reconstructions across scanners; the higher the p‐value, the greater the similarity between the SUVRs. RESULTS: Vision‐mCT harmonization: Vision reconstruction with FWHM = 4.10 mm and mCT reconstruction with FWHM = 4.30 mm gave the maximal statistical similarity (maximum p‐value) between regional SUVRs. Philips‐mCT harmonization: The FWHM of the Philips reconstruction was 8.2 mm and the mCT reconstruction with the FWHM of 9.35 mm, which gave the maximal statistical similarity between regional SUVRs. Philips–Vision harmonization: The Vision reconstruction with an FWHM of 9.1 mm gave the maximal statistical similarity between regional SUVRs when compared with the Philips reconstruction of 8.2 mm and were selected as the harmonized for each scanner pair. CONCLUSION: Based on data obtained from three sets of participants, each scanned on a pair of PET scanners, it has been verified that using reconstruction configurations that produce matched‐barrel, phantom spatial resolutions results in maximally harmonized Aβ‐PET quantitation between scanner pairs. This finding is encouraging for the use of PET scanners in multi‐center trials or updates during longitudinal studies. Highlights: Question: Does the process of matching the barrel phantom‐derived spatial resolution between scanners harmonize amyloid beta–standardized uptake value ratio (Aβ‐SUVR) quantitation?Pertinent findings: It has been validated that reconstruction pairs with matched barrel phantom‐derived spatial resolution maximize the similarity between subjects paired Aβ‐PET (positron emission tomography) SUVR values recorded on two scanners.Implications for patient care: Harmonization between scanners in multi‐center trials and PET camera updates in longitudinal studies can be achieved using a simple and efficient phantom measurement procedure, beneficial for the validity of Aβ‐PET quantitation measurements. [ABSTRACT FROM AUTHOR]

Background: Modern PET reconstruction algorithms incorporate point-spread-function (PSF) correction to mitigate partial volume effect. However, PSF correction can introduce edge artifacts that lead to quantification errors. Consequently, current international guidelines advise against using PSF correction in brain PET reconstruction., Purpose: We aimed to investigate PSF-induced quantification errors in recent digital PET systems and identify conditions that mitigate them. This study utilized brain PET imaging with alginate-based realistic phantoms, simulating lesion-to-background activity ratios of 10:1 and 2:1, with eleven reconstruction parameter sets., Methods: Phantoms were prepared using a commercial anthropomorphic head phantom and two homemade inserts. Each insert contained a homogeneous 18 F-FDG alginate background with hot spheres of varying diameter (3, 4, 6, 8, 10, 12, and 15 mm). PET imaging was conducted on a digital PET-CT system Biograph Vision 600 (Siemens), with a 10 min scan duration. Imaging was performed with and without PSF correction, with 2, 4, 6, 12, 18, or 24 iterations in reconstruction, and with or without additional Gaussian postfiltering. We assessed the recovery coefficient (RC), contrast recovery coefficient (CRC), variability, and CRC-to-variability ratios for each sphere size and reconstruction parameter set., Results: PSF-corrected images of the 10:1 spheres exhibited a nonmonotonic CRC-to-sphere diameter relationship due to edge artifacts overshoot in the 10 mm-diameter sphere. In contrast, PSF images of the 2:1 spheres showed a monotonically increasing relationship. Non-PSF images of both phantoms showed an expected monotonically increasing CRC-to-sphere diameter relationship but with lower CRC values compared to PSF images. The nonmonotonic relationship observed with 10:1 spheres was mitigated by applying a 3-mm FWHM Gaussian postfiltering. For both phantoms, reconstructions with 6 iterations, PSF correction, and additional 3-mm FWHM Gaussian postfiltering demonstrated the highest CRC-to-variability ratios., Conclusions: Our findings indicate that Gaussian postfiltering suppresses PSF artifacts. This parameter set corrected the nonmonotonic CRC-to-sphere diameter relationship and improved the CRC-to-variability ratio compared to non-PSF reconstructions. Therefore, to enhance lesion detectability without compromising quantification accuracy, PSF correction coupled with Gaussian postfiltering should be used in brain PET., (© 2024 American Association of Physicists in Medicine.)

Although peptide radionuclide therapy (PRRT) using a somatostatin analog (SSA) radiolabeled with a beta- emitter: [ 177 Lu]Lu-DOTATATE has shown a good clinical efficacy in neuroendocrine tumors (NETs), most of the patients only achieved tumoral stabilization and rare but severe long-term hematological toxicities have been reported. One of the promising options to improve PRRT is targeted alpha therapy. It is therefore essential to propose animal models that can mimic systemic spread disease, especially microscopic disease such as early stage of NET liver metastases to explore targeted alpha therapy. Herein, we report the evaluation of efficacy and toxicity of [ 225 Ac]Ac-DOTATOC in an original preclinical murine model simulating the development of well-characterized liver metastases of pancreatic NETs with SSTR overexpression., Methods: A mouse model of liver metastases of pancreatic NETs was developed by intraportal injection of AR42J cells and explored using [ 68  Ga]Ga-DOTATOC and [ 18 F]F-FDG PET/MRI. Biodistribution study and radiation dosimetry of [ 225 Ac]Ac-DOTATOC were determined in subcutaneous tumor-bearing NMRI-nude mice. Efficacy and toxicity were determined by intravenous injection of increasing activities of [ 225 Ac]Ac-DOTATOC 10 days after intraportal graft., Results: Liver tumors showed a high uptake of [ 68  Ga]Ga-DOTATOC and no uptake of [ 18 F]F-FDG confirming the well-differentiated phenotype. All groups treated with [ 225 Ac]Ac-DOTATOC showed a significant increase in overall survival compared with DOTATOC-treated mice, especially those treated with the highest activities: 53 days with 240 kBq (p = 0.0001), and 58 days with 2 × 120 kBq (p < 0.0001) vs 28 days with non-radiolabeled DOTATOC. On blood tests, a transient and moderate decreased in white blood cells count after treatment and no severe hepatic or renal toxicity were observed after treatment which was consistent with pathological and radiation dosimetry findings., Conclusion: [ 225 Ac]Ac-DOTATOC exhibit a favorable efficacy and toxicity profile in a mouse model of liver micrometastatic pancreatic NET., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Attenuation correction (AC) is essential for quantitative positron emission tomography (PET) images. Attenuation coefficient maps (μ-maps) are usually generated from computed tomography (CT) images when PET-CT combined systems are used. If CT has been performed prior to PET imaging, pre-acquired CT can be used for brain PET AC, because the human head is almost rigid. This pre-acquired CT-based AC approach is suitable for stand-alone brain-dedicated PET, such as VRAIN (ATOX Co. Ltd., Tokyo, Japan). However, the headrest of PET is different from the headrest in pre-acquired CT images, which may degrade the PET image quality. In this study, we prepared three different types of μ-maps: (1) based on the pre-acquired CT, where namely the headrest is different from the PET system (μ-map-diffHr); (2) manually removing the headrest from the pre-acquired CT (μ-map-noHr); and (3) artificially replacing the headrest region with the headrest of the PET system (μ-map-sameHr). Phantom images by VRAIN using each μ-map were investigated for uniformity, noise, and quantitative accuracy. Consequently, only the uniformity of the images using μ-map-diffHr was out of the acceptance criteria. We then proposed an automated method for removing the headrest from pre-acquired CT images. In comparisons of standardized uptake values in nine major brain regions from the 18F-fluoro-2-deoxy-D-glucose-PET of 10 healthy volunteers, no significant differences were found between the μ-map-noHr and the μ-map-sameHr. In conclusion, pre-acquired CT-based AC with automated headrest removal is useful for brain-dedicated PET such as VRAIN. [ABSTRACT FROM AUTHOR]

Not only visual interpretation for lesion detection, staging, and characterization, but also quantitative treatment response assessment are key roles for 18 F-FDG PET in oncology. In multicenter oncology PET studies, image quality standardization and SUV harmonization are essential to obtain reliable study outcomes. Standards for image quality and SUV harmonization range should be regularly updated according to progress in scanner performance. Accordingly, the first aim of this study was to propose new image quality reference levels to ensure small lesion detectability. The second aim was to propose a new SUV harmonization range and an image noise criterion to minimize the inter-scanner and intra-scanner SUV variabilities. We collected a total of 37 patterns of images from 23 recent PET/CT scanner models using the NEMA NU2 image quality phantom. PET images with various acquisition durations of 30-300 s and 1800 s were analyzed visually and quantitatively to derive visual detectability scores of the 10-mm-diameter hot sphere, noise-equivalent count (NEC phantom ), 10-mm sphere contrast (Q H,10 mm ), background variability (N 10 mm ), contrast-to-noise ratio (Q H,10 mm /N 10 mm ), image noise level (CV BG ), and SUVmax and SUVpeak for hot spheres (10-37 mm diameters). We calculated a reference level for each image quality metric, so that the 10-mm sphere can be visually detected. The SUV harmonization range and the image noise criterion were proposed with consideration of overshoot due to point-spread function (PSF) reconstruction. We proposed image quality reference levels as follows: Q H,10 mm /N 10 mm  ≥ 2.5 and CV BG  ≤ 14.1%. The 10th-90th percentiles in the SUV distributions were defined as the new SUV harmonization range. CV BG  ≤ 10% was proposed as the image noise criterion, because the intra-scanner SUV variability significantly depended on CV BG . We proposed new image quality reference levels to ensure small lesion detectability. A new SUV harmonization range (in which PSF reconstruction is applicable) and the image noise criterion were also proposed for minimizing the SUV variabilities. Our proposed new standards will facilitate image quality standardization and SUV harmonization of multicenter oncology PET studies. The reliability of multicenter oncology PET studies will be improved by satisfying the new standards., (© 2021. The Author(s) under exclusive licence to The Japanese Society of Nuclear Medicine.)

Background: The calculation of the net administered activity (Aadmin) in patients undergoing 90Y‐radioembolization is essential for dosimetry and radiation safety, yet current methods for measuring residual 90Y activity are often associated with high uncertainty. Therefore, an accurate, robust, and clinically viable method for the determination of Aadmin across approved 90Y microsphere devices is desirable. Purpose: We report on a novel method to determine Aadmin by leveraging the quantitative capabilities of SPECT/CT to measure 90Y‐emission in vivo from patients following 90Y‐radioembolization with glass or resin microspheres. Methods: 90Y‐SPECT/CT attenuation‐corrected count data from 147 sequential 90Y‐radioembolization patients was used for this analysis. Aadmin was calculated as part of routine clinical practice via the exposure rate differences between the initial 90Y‐vial and the 90Y‐residual jar. This served as our gold standard measure of Aadmin. Patient data for each microsphere device were separated into training and testing cohorts to first develop regression models and then to independently assess model performance. The training cohorts were divided into four groups: first, based on the microsphere device (glass or resin), and second, based on the SPECT volume used to calculate counts (the full SPECT field of view (FOV) or liver only (VOIliver)). Univariate linear regression models were generated for each group to predict Aadmin based on 90Y‐SPECT data from the training cohorts. Leave‐one‐out cross validation was implemented to estimate variability in model parameters. To assess performance, linear models derived from the training cohort were applied to 90Y‐SPECT data from the testing cohort. A comparison of the models between microspheres devices was also performed. Results: Linear models derived from the glass and resin training cohorts demonstrated a strong, positive correlation between 90Y‐SPECT image counts and Aadmin for VOIliver and FOV with R2 > 0.98 in all cases. In the glass training cohort, model accuracy (100%—absolute mean prediction error) and precision (95% prediction intervals of mean prediction error) were 99.0% and 15.4% for the VOIliver and 99.7% and 17.5% for the FOV models, respectively. In the resin training cohort, the corresponding values were 98.6% and 16.7% for VOIliver and > 99.9% and 11.4% for the FOV models, respectively. The application of these linear models to 90Y‐SPECT data from the testing cohort showed Aadmin prediction errors to have high accuracy and precision for both microsphere devices. For the glass testing cohort, accuracy (precision) was 96.9% (19.6%) and 98.8% (21.1%) for the VOIliver and FOV models, respectively. The corresponding values for the resin training cohort were 97.3% (26.2%) and 98.5% (25.7%) for the VOIliver and FOV models, respectively. The slope of the linear models between the two microsphere devices was observed to be significantly different with resin microspheres generating 48%–49% more SPECT counts for equivalent 90Y activity based on each device manufacturer's activity calibration process. Conclusion: 90Y‐SPECT image counts can reliably predict (accuracy > 95% and precision < 18%) Aadmin after 90Y‐radioembolization, with performance characteristics essentially equivalent for both glass and resin microspheres. There is a clear indication that activity calibrations are fundamentally different between the two microsphere devices. [ABSTRACT FROM AUTHOR]

Objective: Non-blinded image deblurring with deep learning was performed on blurred numerical brain images without point spread function (PSF) reconstruction to obtain edge artifacts (EA)-free images. This study uses numerical simulation to investigate the mechanism of EA in PSF reconstruction based on the spatial frequency characteristics of EA-free images. Methods: In 256 × 256 matrix brain images, the signal values of gray matter (GM), white matter, and cerebrospinal fluid were set to 1, 0.25, and 0.05, respectively. We assumed ideal projection data of a two-dimensional (2D) parallel beam with no degradation factors other than detector response blur to precisely grasp EA using the PSF reconstruction algorithm from blurred projection data. The detector response was assumed to be a shift-invariant and one-dimensional (1D) Gaussian function with 2–5 mm full width at half maximum (FWHM). Images without PSF reconstruction (non-PSF), PSF reconstruction without regularization (PSF) and with regularization of relative difference function (PSF-RD) were generated by ordered subset expectation maximization (OSEM). For non-PSF, the image deblurring with a deep image prior (DIP) was applied using a 2D Gaussian function with 2–5 mm FWHM. The 1D object-specific modulation transfer function (1D-OMTF), which is the ratio of 1D amplitude spectrum of the original and reconstructed images, was used as the index of spatial frequency characteristics. Results: When the detector response was greater than 3 mm FWHM, EA in PSF was observed in GM borders and narrow GM. No remarkable EA was observed in the DIP, and the FWHM estimated from the recovery coefficient for the deblurred image of non-PSF at 5 mm FWHM was reduced to 3 mm or less. PSF of 5 mm FWHM showed higher spatial frequency characteristics than that of DIP up to around 2.2 cycles/cm but was lower than the latter after 3 cycles/cm. PSF-RD showed almost the same spatial frequency characteristics as that of DIP above 3 cycles/cm but was inferior below 3 cycles/cm. PSF-RD has a lower spatial resolution than DIP. Conclusions: Unlike DIP, PSF lacks high-frequency components around the Nyquist frequency, generating EA. PSF-RD mitigates EA while simultaneously suppressing the signal, diminishing spatial resolution. [ABSTRACT FROM AUTHOR]

Objective: To investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spread ≤ 5 mm). Methods: This retrospective study enrolled 303 patients with low T-staging rectal cancer (training cohort, n = 213, testing cohort n = 90). A total of 960 radiomics features were extracted from T2WI. Minimum redundancy and maximum relevance (mRMR) and support vector machine were performed to select the best performed radiomics features for predicting LN metastasis. Multivariate logistic regression analysis was then used to construct the clinical and clinical-radiomics combined models. The model performance for predicting LN metastasis was assessed by receiver operator characteristic curve (ROC) and clinical utility implementing a nomogram and decision curve analysis (DCA). The predictive performance for LN metastasis was also compared between the combined model and human readers (2 seniors). Results: Fourteen radiomics features and 2 clinical characteristics were selected for predicting LN metastasis. In the testing cohort, a higher positive predictive value of 75.9% for the combined model was achieved than those of the clinical model (44.8%) and two readers (reader 1: 54.9%, reader 2: 56.3%) in identifying LN metastasis. The interobserver agreement between 2 readers was moderate with a kappa value of 0.416. A clinical-radiomics nomogram and decision curve analysis demonstrated that the combined model was clinically useful. Conclusion: T2WI-based radiomics combined with clinical data could improve the efficacy in noninvasively evaluating LN metastasis for the low T-staging rectal cancer and aid in tailoring treatment strategies. [ABSTRACT FROM AUTHOR]