Establishing the psychological impact of congenital upper limb differences on parents and families.

The aim of this prospective study was to report the psychological experiences of parents caring for children with a congenital upper limb difference and to compare these to population norms. Contributing factors were explored, including access to support and coping strategies. Finally, parents with a congenital upper limb difference themselves were compared to those without. Data recorded included demographics, a validated wellbeing and family impact measure, a unique measure of emotions experienced and exploratory questions. Wellbeing and family impact scores were significantly lower than populations norms. Mothers experienced significantly more negative emotions than fathers. There was no significant different between parents with and without a congenital upper limb difference. Of the parents, 68% felt there should be improved access to psychological support. This demonstrates that parents of children with congenital upper limb differences have unique psychological experiences and needs. They may benefit from specialist psychological support and further research is needed.Level of evidence: III.

Radiotherapy for aseptic granulomatous dermatitis: A case report.

Granulomatous dermatitis is a common tissue reaction pattern seen in the skin or systematically in various presentations. Granulomatous dermatitis can be subclassified into infectious and non-infectious categories. This article focuses on a patient with non-infectious granulomatous dermatitis followed for many years. Past medical history included bilateral total shoulder arthroplasty complicated by prosthetic joint infections. In its early stages, the axillary rash was painful and had many fluid-filled blisters. Ultimately, the histology of the rash deemed the lesion non-infectious and mostly due to an inflammatory process. Specifically, ionizing radiation was used for this patient. The category of granulomatous processes is broad and there are many subtypes. Other treatment options for non-infectious granulomatous processes may include corticosteroids, phototherapy, and interferon-gamma injections. The differential for granulomatous processes is extensive and treatment should be decided on a case-by-case basis.

Non-Fungible Tokens for Organoids: Decentralized Biobanking to Empower Patients in Biospecimen Research.

Introduction: Scientists use donated biospecimens to create organoids, which are miniature copies of patient tumors that are revolutionizing precision medicine and drug discovery. However, biobanking platforms remove donor identifiers to protect privacy, precluding patients from benefiting from their contributions or sharing information that may be relevant to research outcomes. Decentralized biobanking (de-bi) leverages blockchain technology to empower patient engagement in biospecimen research. We describe the creation of the first de-bi prototype for an organoid biobanking use case. Methods: We designed and developed a proof-of-concept non-fungible tokens (NFTs) framework for an organoid research network of patients, physicians, and scientists within a synthetic dataset modeled on a real-world breast cancer organoid ecosystem. Our implementation deployed multiple smart contracts on Ethereum test networks, minting NFTs representing each stakeholder, biospecimen, and organoid. The system architecture was designed to be composable with established biobanking programs. Results: Our de-bi prototype demonstrated how NFTs representing patients, physicians, scientists, and organoids may be united in a privacy-preserving platform that builds upon relationships and transactions of existing biobank research networks. The mobile application simulated key features, enabling patients to track their biospecimens, view organoid images and research updates from scientists, and allow physicians to participate in peer-to-peer communications with basic scientists and patients alike, all while ensuring compliance with de-identification requirements. Discussion: We demonstrate proof-of-concept for a web3 platform engaging patients, physicians, and scientists in a dynamic research community, unlocking value for a model organoid ecosystem. This initial prototype is a critical first step for advancing paradigm-shifting de-bi technology that provides unprecedented transparency and suggests new standards for equity and inclusion in biobanking. Further research must address feasibility and acceptability considering the ethical, legal, economic, and technical complexities of organoid research and clinical translation.

Extracellular vesicles produced by HIV-1 Nef-expressing cells induce myelin impairment and oligodendrocyte damage in the mouse central nervous system.

HIV-associated neurocognitive disorders (HAND) are a spectrum of cognitive impairments that continue to affect approximately half of all HIV-positive individuals despite effective viral suppression through antiretroviral therapy (ART). White matter pathologies have persisted in the ART era, and the degree of white matter damage correlates with the degree of neurocognitive impairment in patients with HAND. The HIV protein Nef has been implicated in HAND pathogenesis, but its effect on white matter damage has not been well characterized. Here, utilizing in vivo, ex vivo, and in vitro methods, we demonstrate that Nef-containing extracellular vesicles (Nef EVs) disrupt myelin sheaths and inflict damage upon oligodendrocytes within the murine central nervous system. Intracranial injection of Nef EVs leads to reduced myelin basic protein (MBP) staining and a decreased number of CC1 + oligodendrocytes in the corpus callosum. Moreover, cerebellar slice cultures treated with Nef EVs exhibit diminished MBP expression and increased presence of unmyelinated axons. Primary mixed brain cultures and enriched oligodendrocyte precursor cell cultures exposed to Nef EVs display a decreased number of O4 + cells, indicative of oligodendrocyte impairment. These findings underscore the potential contribution of Nef EV-mediated damage to oligodendrocytes and myelin maintenance in the pathogenesis of HAND.

Deep Learning-Enabled Quantification of 99mTc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis.

Transthyretin cardiac amyloidosis (ATTR CA) is increasingly recognized as a cause of heart failure in older patients, with 99mTc-pyrophosphate imaging frequently used to establish the diagnosis. Visual interpretation of SPECT images is the gold standard for interpretation but is inherently subjective. Manual quantitation of SPECT myocardial 99mTc-pyrophosphate activity is time-consuming and not performed clinically. We evaluated a deep learning approach for fully automated volumetric quantitation of 99mTc-pyrophosphate using segmentation of coregistered anatomic structures from CT attenuation maps. Methods: Patients who underwent SPECT/CT 99mTc-pyrophosphate imaging for suspected ATTR CA were included. Diagnosis of ATTR CA was determined using standard criteria. Cardiac chambers and myocardium were segmented from CT attenuation maps using a foundational deep learning model and then applied to attenuation-corrected SPECT images to quantify radiotracer activity. We evaluated the diagnostic accuracy of target-to-background ratio (TBR), cardiac pyrophosphate activity (CPA), and volume of involvement (VOI) using the area under the receiver operating characteristic curve (AUC). We then evaluated associations with the composite outcome of cardiovascular death or heart failure hospitalization. Results: In total, 299 patients were included (median age, 76 y), with ATTR CA diagnosed in 83 (27.8%) patients. CPA (AUC, 0.989; 95% CI, 0.974-1.00) and VOI (AUC, 0.988; 95% CI, 0.973-1.00) had the highest prediction performance for ATTR CA. The next highest AUC was for TBR (AUC, 0.979; 95% CI, 0.964-0.995). The AUC for CPA was significantly higher than that for heart-to-contralateral ratio (AUC, 0.975; 95% CI, 0.952-0.998; P = 0.046). Twenty-three patients with ATTR CA experienced cardiovascular death or heart failure hospitalization. All methods for establishing TBR, CPA, and VOI were associated with an increased risk of events after adjustment for age, with hazard ratios ranging from 1.41 to 1.84 per SD increase. Conclusion: Deep learning segmentation of coregistered CT attenuation maps is not affected by the pattern of radiotracer uptake and allows for fully automatic quantification of hot-spot SPECT imaging such as 99mTc-pyrophosphate. This approach can be used to accurately identify patients with ATTR CA and may play a role in risk prediction.

Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction.

Background: While low-dose computed tomography scans are traditionally used for attenuation correction in hybrid myocardial perfusion imaging (MPI), they also contain additional anatomic and pathologic information not utilized in clinical assessment. We seek to uncover the full potential of these scans utilizing a holistic artificial intelligence (AI)-driven image framework for image assessment. Methods: Patients with SPECT/CT MPI from 4 REFINE SPECT registry sites were studied. A multi-structure model segmented 33 structures and quantified 15 radiomics features for each on CT attenuation correction (CTAC) scans. Coronary artery calcium and epicardial adipose tissue scores were obtained from separate deep-learning models. Normal standard quantitative MPI features were derived by clinical software. Extreme Gradient Boosting derived all-cause mortality risk scores from SPECT, CT, stress test, and clinical features utilizing a 10-fold cross-validation regimen to separate training from testing data. The performance of the models for the prediction of all-cause mortality was evaluated using area under the receiver-operating characteristic curves (AUCs). Results: Of 10,480 patients, 5,745 (54.8%) were male, and median age was 65 (interquartile range [IQR] 57-73) years. During the median follow-up of 2.9 years (1.6-4.0), 651 (6.2%) patients died. The AUC for mortality prediction of the model (combining CTAC, MPI, and clinical data) was 0.80 (95% confidence interval [0.74-0.87]), which was higher than that of an AI CTAC model (0.78 [0.71-0.85]), and AI hybrid model (0.79 [0.72-0.86]) incorporating CTAC and MPI data (p<0.001 for all). Conclusion: In patients with normal perfusion, the comprehensive model (0.76 [0.65-0.86]) had significantly better performance than the AI CTAC (0.72 [0.61-0.83]) and AI hybrid (0.73 [0.62-0.84]) models (p<0.001, for all).CTAC significantly enhances AI risk stratification with MPI SPECT/CT beyond its primary role - attenuation correction. A comprehensive multimodality approach can significantly improve mortality prediction compared to MPI information alone in patients undergoing cardiac SPECT/CT.

An Enzymatic and Proteomic Analysis of Panus lecomtei during Biodegradation of Gossypol in Cottonseed.

Cotton is an important plant-based protein. Cottonseed cake, a byproduct of the biodiesel industry, offers potential in animal supplementation, although the presence of the antinutritional sesquiterpenoid gossypol limits utilization. The macrofungus Panus lecomtei offers potential in detoxification of antinutritional factors. Through an enzymatic and proteomic analysis of P. lecomtei strain BRM044603, grown on crushed whole cottonseed contrasting in the presence of free gossypol (FG), this study investigated FG biodegradation over a 15-day cultivation period. Fungal growth reduced FG to levels at 100 µg/g, with a complex adaptive response observed, involving primary metabolism and activation of oxidative enzymes for metabolism of xenobiotics. Increasing activity of secreted laccases correlated with a reduction in FG, with enzyme fractions degrading synthetic gossypol to trace levels. A total of 143 and 49 differentially abundant proteins were observed across the two contrasting growth conditions after 6 and 12 days of cultivation, respectively, revealing a dynamic protein profile during FG degradation, initially related to constitutive metabolism, then later associated with responses to oxidative stress. The findings advance our understanding of the mechanisms involved in gossypol degradation and highlight the potential of P. lecomtei BRM044603 in cotton waste biotreatment, relevant for animal supplementation, sustainable resource utilization, and bioremediation.

Sex Differences in Muscle Morphology between Male and Female Sprinters.

There is a marked difference between males and females in sprint running performance, yet a comprehensive investigation of sex differences in the muscle morphology of sprinters remains to completed. This study compared muscle volumes of 23 individual leg muscles/compartments and five functional muscle groups, assessed with 3T magnetic resonance imaging, between male (n=31) and female (n=22) sprinters, and sub-groups of elite males (EM, n=5), elite females (EF, n=5), and performance matched (to elite females) males (PMMEF, n=6). Differences in muscle volume distribution between EM, EF and unathletic male controls (UM) were also assessed. For the full sprint cohorts, males were more muscular than females, but the differences were non-uniform and anatomically variable, with the largest differences in the hip extensors and flexors. However, amongst elite sprinters the sex differences in the volume of the functional muscle groups were almost uniform (absolute volume +47-53%), and the muscle volume distribution of EM was more similar to EF than UM (P<0.039). For PMMEF relative hip extensor volume, but not stature or percent body fat, differentiated for performance (PMMEF and EF < EM) rather than sex. In conclusion, whilst the full cohorts of sprinters showed a marked sex difference in the amount and distribution of muscle mass, elite sprinters appeared to be selected for a common muscle distribution phenotype that for these elite sub-groups was a stronger effect than that of sex. Relative hip extensor muscle volume appeared to be the primary determinant of the sex difference in performance.

Pulmonary vascular disease in Veterans with post-deployment respiratory syndrome.

Exertional dyspnea has been documented in US military personnel after deployment to Iraq and Afghanistan. We studied whether continued exertional dyspnea in this patient population is associated with pulmonary vascular disease (PVD). We performed detailed histomorphometry of pulmonary vasculature in 52 Veterans with biopsy-proven post-deployment respiratory syndrome (PDRS) and then recruited five of these same Veterans with continued exertional dyspnea to undergo a follow-up clinical evaluation, including symptom questionnaire, pulmonary function testing, surface echocardiography, and right heart catheterization (RHC). Morphometric evaluation of pulmonary arteries showed significantly increased intima and media thicknesses, along with collagen deposition (fibrosis), in Veterans with PDRS compared to non-diseased (ND) controls. In addition, pulmonary veins in PDRS showed increased intima and adventitia thicknesses with prominent collagen deposition compared to controls. Of the five Veterans involved in our clinical follow-up study, three had borderline or overt right ventricle (RV) enlargement by echocardiography and evidence of pulmonary hypertension (PH) on RHC. Together, our studies suggest that PVD with predominant venular fibrosis is common in PDRS and development of PH may explain exertional dyspnea and exercise limitation in some Veterans with PDRS.

Debamestrocel multimodal effects on biomarker pathways in amyotrophic lateral sclerosis are linked to clinical outcomes.

INTRODUCTION/AIMS: Biomarkers have shown promise in amyotrophic lateral sclerosis (ALS) research, but the quest for reliable biomarkers remains active. This study evaluates the effect of debamestrocel on cerebrospinal fluid (CSF) biomarkers, an exploratory endpoint. METHODS: A total of 196 participants randomly received debamestrocel or placebo. Seven CSF samples were to be collected from all participants. Forty-five biomarkers were analyzed in the overall study and by two subgroups characterized by the ALS Functional Rating Scale-Revised (ALSFRS-R). A prespecified model was employed to predict clinical outcomes leveraging biomarkers and disease characteristics. Causal inference was used to analyze relationships between neurofilament light chain (NfL) and ALSFRS-R. RESULTS: We observed significant changes with debamestrocel in 64% of the biomarkers studied, spanning pathways implicated in ALS pathology (63% neuroinflammation, 50% neurodegeneration, and 89% neuroprotection). Biomarker changes with debamestrocel show biological activity in trial participants, including those with advanced ALS. CSF biomarkers were predictive of clinical outcomes in debamestrocel-treated participants (baseline NfL, baseline latency-associated peptide/transforming growth factor beta1 [LAP/TGFß1], change galectin-1, all p < .01), with baseline NfL and LAP/TGFß1 remaining (p < .05) when disease characteristics (p < .005) were incorporated. Change from baseline to the last measurement showed debamestrocel-driven reductions in NfL were associated with less decline in ALSFRS-R. Debamestrocel significantly reduced NfL from baseline compared with placebo (11% vs. 1.6%, p = .037). DISCUSSION: Following debamestrocel treatment, many biomarkers showed increases (anti-inflammatory/neuroprotective) or decreases (inflammatory/neurodegenerative) suggesting a possible treatment effect. Neuroinflammatory and neuroprotective biomarkers were predictive of clinical response, suggesting a potential multimodal mechanism of action. These results offer preliminary insights that need to be confirmed.

Self-reported exercise activity influences the relationship between coronary computed tomography angiographic finding and mortality.

AIM: Recent studies suggest that the application of exercise activity questionnaires, including the use of a single-item exercise question, can be additive to the prognostic efficacy of imaging findings. This study aims to evaluate the prognostic efficacy of exercise activity in patients undergoing coronary computed tomography angiography (CCTA). METHODS AND RESULTS: We assessed 9772 patients who underwent CCTA at a single center between 2007 and 2020. Patients were divided into 4 groups of physical activity as no exercise (n â€‹= â€‹1643, 17%), mild exercise (n â€‹= â€‹3156, 32%), moderate exercise (n â€‹= â€‹3542, 36%), and high exercise (n â€‹= â€‹1431,15%), based on a single-item self-reported questionnaire. Coronary stenosis was categorized as no (0%), non-obstructive (1-49%), borderline (50-69%), and obstructive (≥70%). During a median follow-up of 4.64 (IQR 1.53-7.89) years, 490 (7.6%) died. There was a stepwise inverse relationship between exercise activity and mortality (p â€‹< â€‹0.001). Compared with the high activity group, the no activity group had a 3-fold higher mortality risk (HR: 3.3, 95%CI (1.94-5.63), p â€‹< â€‹0.001) after adjustment for age, clinical risk factors, symptoms, and statin use. For any level of CCTA stenosis, mortality rates were inversely associated with the degree of patients' exercise activity. The risk of all-cause mortality was similar among the patients with obstructive stenosis with high exercise versus those with no coronary stenosis but no exercise activity (p â€‹= â€‹0.912). CONCLUSION: Physical activity as assessed by a single-item self-reported questionnaire is a strong stepwise inverse predictor of mortality risk among patients undergoing CCTA.

Enhancing In Vivo Electroporation Efficiency through Hyaluronidase: Insights into Plasmid Distribution and Optimization Strategies.

Electroporation (EP) stands out as a promising non-viral plasmid delivery strategy, although achieving optimal transfection efficiency in vivo remains a challenge. A noteworthy advancement in the field of in vivo EP is the application of hyaluronidase, an enzyme with the capacity to degrade hyaluronic acid in the extracellular matrix, which thereby enhances DNA transfer efficiency by 2- to 3-fold. This paper focuses on elucidating the mechanism of hyaluronidase's impact on transfection efficiency. We demonstrate that hyaluronidase promotes a more uniform distribution of plasmid DNA (pDNA) within skeletal muscle. Additionally, our study investigates the effect of the timing of hyaluronidase pretreatment on EP efficiency by including time intervals of 0, 5, and 30 min between hyaluronidase treatment and the application of pulses. Serum levels of the pDNA-encoded transgene reveal a minimal influence of the hyaluronidase pretreatment time on the final serum protein levels following delivery in both mice and rabbit models. Leveraging bioimpedance measurements, we capture morphological changes in muscle induced by hyaluronidase treatment, which result in a varied pDNA distribution. Subsequently, these findings are employed to optimize EP electrical parameters following hyaluronidase treatment in animal models. This paper offers novel insights into the potential of hyaluronidase in enhancing the effectiveness of in vivo EP, as well as guides optimized electroporation strategies following hyaluronidase use.

Improving 1-Year Mortality Following Intensive Care Unit Admission in Adults with HIV: A 20-Year Observational Study.

BACKGROUND: Despite widespread use of combination antiretroviral therapy, people with HIV (PWH) continue to have an increased risk of admission to and mortality in the intensive care unit (ICU). Mortality risk after hospital discharge is not well described. Using retrospective data on adult PWH (≥18 years) admitted to ICU from 2000-2019 in an HIV-referral centre, we describe trends in 1-year mortality after ICU admission. METHODS: One-year mortality was calculated from index ICU admission to date of death; with follow-up right-censored at day 365 for people remaining alive at 1 year, or day 7 after ICU discharge if lost-to-follow-up after hospital discharge. Cox regression was used to describe the association with calendar year before and after adjustment for patient characteristics (age, sex, Acute Physiology and Chronic Health Evaluation II [APACHE II] score, CD4+ T-cell count, and recent HIV diagnosis) at ICU admission. Analyses were additionally restricted to those discharged alive from ICU using a left-truncated design, with further adjustment for respiratory failure at ICU admission in these analyses. RESULTS: Two hundred and twenty-one PWH were admitted to ICU (72% male, median [interquartile range] age 45 [38-53] years) of whom 108 died within 1-year (cumulative 1-year survival: 50%). Overall, the hazard of 1-year mortality was decreased by 10% per year (crude hazard ratio (HR): 0.90 (95% confidence interval: 0.87-0.93)); the association was reduced to 7% per year (adjusted HR: 0.93 (0.89-0.98)) after adjustment. Conclusions were similar among the subset of 136 patients discharged alive (unadjusted: 0.91 (0.84-0.98); adjusted 0.92 (0.84, 1.02)). CONCLUSIONS: Between 2000 and 2019, 1-year mortality after ICU admission declined at this ICU. Our findings highlight the need for multi-centre studies and the importance of continued engagement in care after hospital discharge among PWH.

Nebulised pentamidine prophylaxis of pneumocystis pneumonia in adults accessing HIV services at royal free hospital, London.

Receipt of nebulised pentamidine in people with HIV was audited to identify if individuals were appropriately receiving nebulised pentamidine, and whether national guidelines were being followed when prophylaxis was commenced and discontinued. Of 76 people with who received nebulised pentamidine, the main indication for starting nebulised pentamidine was a co-trimoxazole adverse drug reaction. Co-trimoxazole desensitization was not attempted before starting nebulised pentamidine. The main indication for stopping nebulised pentamidine prophylaxis was when immune reconstitution occurred. This single centre audit revealed that national guidelines were being followed in most cases. The lack of information regarding the reason for starting or stopping nebulised pentamidine prophylaxis, or detail of the clinician's concerns about potential poor adherence with oral regimens of prophylaxis as a reason for choosing nebulised pentamidine prophylaxis, identifies a need for improved documentation of clinicians' decision-making. Introduction of pharmacist-led interventions/alerts using patients' electronic records, similar to those used in primary care, would enable the specialist pharmacy team to identify when and if co-trimoxazole desensitization has been offered and discussed/declined before a clinician prescribes nebulised pentamidine as well as enabling identification of those in who pentamidine prophylaxis has been continued, despite "immune reconstitution".

Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography.

Chest computed tomography is one of the most common diagnostic tests, with 15 million scans performed annually in the United States. Coronary calcium can be visualized on these scans, but other measures of cardiac risk such as atrial and ventricular volumes have classically required administration of contrast. Here we show that a fully automated pipeline, incorporating two artificial intelligence models, automatically quantifies coronary calcium, left atrial volume, left ventricular mass, and other cardiac chamber volumes in 29,687 patients from three cohorts. The model processes chamber volumes and coronary artery calcium with an end-to-end time of ~18 s, while failing to segment only 0.1% of cases. Coronary calcium, left atrial volume, and left ventricular mass index are independently associated with all-cause and cardiovascular mortality and significantly improve risk classification compared to identification of abnormalities by a radiologist. This automated approach can be integrated into clinical workflows to improve identification of abnormalities and risk stratification, allowing physicians to improve clinical decision-making.

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and imaging parameters could predict hospitalization for acute HF exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging. Methods: The HF risk prediction model was developed using data from 4,766 patients who underwent SPECT/CT at a single center (internal cohort). The algorithm used clinical risk factors, stress variables, SPECT imaging parameters, and fully automated deep learning-generated calcium scores from attenuation CT scans. The model was trained and validated using repeated hold-out (10-fold cross-validation). External validation was conducted on a separate cohort of 2,912 patients. During a median follow-up of 1.9 y, 297 patients (6%) in the internal cohort were admitted for HF exacerbation. Results: The final model demonstrated a higher area under the receiver-operating-characteristic curve (0.87 ± 0.03) for predicting HF admissions than did stress left ventricular ejection fraction (0.73 ± 0.05, P < 0.0001) or a model developed using only clinical parameters (0.81 ± 0.04, P < 0.0001). These findings were confirmed in the external validation cohort (area under the receiver-operating-characteristic curve: 0.80 ± 0.04 for final model, 0.70 ± 0.06 for stress left ventricular ejection fraction, 0.72 ± 0.05 for clinical model; P < 0.001 for all). Conclusion: Integrating SPECT myocardial perfusion imaging into an artificial intelligence-based risk assessment algorithm improves the prediction of HF hospitalization. The proposed method could enable early interventions to prevent HF hospitalizations, leading to improved patient care and better outcomes.

Artificial Intelligence in Nuclear Cardiology: An Update and Future Trends.

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) or positron emission tomography (PET), is one of the most commonly ordered cardiac imaging tests, with prominent clinical roles for disease diagnosis and risk prediction. Artificial intelligence (AI) could potentially play a role in many steps along the typical MPI workflow, from image acquisition through to clinical reporting and risk estimation. AI can be utilized to improve image quality, reducing radiation exposure and image acquisition times. Once images are acquired, AI can help optimize motion correction and image registration during image reconstruction or provide direct image attenuation correction. Utilizing these image sets, AI can segment a number of anatomic features from associated computed tomographic imaging or even generate synthetic attenuation imaging. Lastly, AI may play an important role in disease diagnosis or risk prediction by combining the large number of potentially important clinical, stress, and imaging-related variables. This review will focus on the most recent developments in the field, providing clinicians and researchers with a timely update on the field. Additionally, it will discuss future trends including applications of AI during multiple points of the typical MPI workflow to maximize clinical utility and methods to maximize the information that can be obtained from hybrid imaging.