Flashy lungs and sarcoidosis: not always a sign of disease activity.

This is the case of a 68-year-old man with known cardiac sarcoidosis undergoing treatment with methotrexate who presented with new onset of dyspnea and lipothymia. FDG-PET/CT revealed pathological uptake within lung parenchyma which resolved following discontinuation of methotrexate, compatible with methotrexate-induced pneumonitis. This is the first case of methotrexate-induced pneumonitis documented by FDG-PET/CT.

177Lu-PSMA-617 in Metastatic Castration-Resistant Prostate Cancer: A Review of the Evidence and Implications for Canadian Clinical Practice.

Prostate-specific membrane antigen (PSMA) is highly expressed in prostate cancer and a therapeutic target. Lutetium-177 (177Lu)-PSMA-617 is the first radioligand therapy to be approved in Canada for use in patients with metastatic castration-resistant prostate cancer (mCRPC). As this treatment represents a new therapeutic class, guidance regarding how to integrate it into clinical practice is needed. This article aims to review the evidence from prospective phase 2 and 3 clinical trials and meta-analyses of observational studies on the use of 177Lu-PSMA-617 in prostate cancer and discuss how Canadian clinicians might best apply these data in practice. The selection of appropriate patients, the practicalities of treatment administration, including necessary facilities for treatment procedures, the assessment of treatment response, and the management of adverse events are considered. Survival benefits were observed in clinical trials of 177Lu-PSMA-617 in patients with progressive, PSMA-positive mCRPC who were pretreated with androgen receptor pathway inhibitors and taxanes, as well as in taxane-naïve patients. However, the results of ongoing trials are awaited to clarify questions regarding the optimal sequencing of 177Lu-PSMA-617 with other therapies, as well as the implications of predictive biomarkers, personalized dosimetry, and combinations with other therapies.

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convolutional neural networks (CNNs) hold promise in accurately identifying tumor locations and boundaries in PET scans. However, a major hurdle is the extensive amount of supervised and annotated data necessary for training. To overcome this limitation, this study explores semi-supervised approaches utilizing unlabeled data, specifically focusing on PET images of diffuse large B-cell lymphoma (DLBCL) and primary mediastinal large B-cell lymphoma (PMBCL) obtained from two centers. We considered 2-[18F]FDG PET images of 292 patients PMBCL (n = 104) and DLBCL (n = 188) (n = 232 for training and validation, and n = 60 for external testing). We harnessed classical wisdom embedded in traditional segmentation methods, such as the fuzzy clustering loss function (FCM), to tailor the training strategy for a 3D U-Net model, incorporating both supervised and unsupervised learning approaches. Various supervision levels were explored, including fully supervised methods with labeled FCM and unified focal/Dice loss, unsupervised methods with robust FCM (RFCM) and Mumford-Shah (MS) loss, and semi-supervised methods combining FCM with supervised Dice loss (MS + Dice) or labeled FCM (RFCM + FCM). The unified loss function yielded higher Dice scores (0.73 ± 0.11; 95% CI 0.67-0.8) than Dice loss (p value < 0.01). Among the semi-supervised approaches, RFCM + αFCM (α = 0.3) showed the best performance, with Dice score of 0.68 ± 0.10 (95% CI 0.45-0.77), outperforming MS + αDice for any supervision level (any α) (p < 0.01). Another semi-supervised approach with MS + αDice (α = 0.2) achieved Dice score of 0.59 ± 0.09 (95% CI 0.44-0.76) surpassing other supervision levels (p < 0.01). Given the time-consuming nature of manual delineations and the inconsistencies they may introduce, semi-supervised approaches hold promise for automating medical imaging segmentation workflows.

Clinical impact of unsuccessful subcutaneous administration of octreotide LAR instead of intramuscular administration in patients with metastatic gastroenteropancreatic neuroendocrine tumors.

Octreotide LAR is a long-acting somatostatin analogue (SSA) used in the management of metastatic gastroenteropancreatic neuroendocrine tumors (GEP NETs). It requires intramuscular (IM) injection. Missed IM injections cause subcutaneous nodules (SCNs) on radiologic images. We reviewed the rates of SCNs in a real-world cohort of GEP NETs receiving octreotide LAR and explored treatment outcomes. Patients commencing octreotide LAR between August 5, 2010 and March 8, 2018 at a single cancer center in Canada were identified from pharmacy records. Patients were included if they had a computed tomography (CT) scan performed at the time of progression and a preceding CT with pelvis included to enable assessment for the presence of nodules. Fisher's exact test was used to examine predictors of SCNs, and Kaplan-Meier curves summarized differences in progression free (PFS) and overall survival (OS) that were compared with log-rank tests. Of 243 patients receiving octreotide LAR, 45 had all required CT images available for central review. SCNs were found in 20/45 (44%) of patients on the last scan showing stable disease before progression and were numerically but not statistically more likely in females (OR: 2.36, 95% CI: 0.66-8.29, p = .23). There was an increased risk of SCNs in patients with a skin-to-muscle distance >38 mm (the length of an octreotide LAR needle) on CT (OR: 5.09, 95% CI: 1.39-16.6, p = .018) and a trend toward increased risk in obese patients (OR: 5.71, 95% CI: 1.26-23.4, p = .061). PFS (HR: 1.01, 95% CI: 0.56-1.78, p = .98) and OS (HR: 0.86, 95% CI: 0.41-1.8, p = .70) was similar between those with/without SCNs. In conclusion, almost half of patients receiving octreotide LAR had SCNs; however, missed administration of SSA did not appear to result in worse survival in this small study. Factors such as sex, younger age skin-to-muscle distance, and obesity may affect SCN development and should be considered when choosing an SSA.

Predicting maximum temperatures over India 10-days ahead using machine learning models.

In the months of March-June, India experiences high daytime temperatures (Tmax), which sometimes lead to heatwave-like conditions over India. In this study, 10 different machine learning models are evaluated for their ability to predict the daily Tmax anomalies 10 days ahead in the months of March-June. Several model experiments were carried out to identify an optimal model to predict daily Tmax anomalies over India. The results indicate that the AdaBoost regressor with Multi-layer Perceptron as the base estimator is an optimal model to predict the Tmax anomalies over India in the months of March-June. The optimal model predictions are benchmarked against 10-day persistence predictions and the predictions from the Climate Forecast System (CFS) reforecast. The results indicate that the machine learning model skill is higher than persistence and comparable to CFS reforecast 10-day predictions in April and May. In March and June, the machine learning models have low skill scores and perform no better than persistence. These results indicate that the machine learning models are promising tools to predict the surface air maximum temperature anomalies over India in April and May and can complement predictions from more sophisticated numerical models.

Optimizing stress-only myocardial perfusion imaging: a clinical prediction model to improve patient selection.

BACKGROUND: Stress-only single photon emission computed tomography myocardial perfusion imaging (MPI) offers numerous advantages in terms of improved workflow, cost and radiation reduction but is currently not widely utilized due to challenges in selecting appropriate patients for this technique. METHODS: Data from 5959 individuals were used to derive (N = 4018) and validate (N = 1941) a binomial logistic regression model to predict normal stress MPI studies (stress total perfusion deficit  < 4%, ejection fraction ≥ 50%). Model performance was analyzed using receiver operator characteristic curves. A simplified point-scoring system was developed and its impact on imaging workflow was assessed. RESULTS: Significant predictors of abnormal vs. normal stress MPI included male sex, age > 65 years, cardiomyopathy, congestive heart failure, myocardial infarction, angina, and pharmacological stress. The final model and simplified scoring system were associated with areas under the curve of 0.81 (95% CI 0.79-0.83) and 0.80 (95% CI 0.79-0.82) in the validation group, respectively. Use of the scoring system was estimated to result in a decrease of 56.5% in the number of non-contributory imaging studies acquired with minimal patient rescheduling. CONCLUSION: A prediction tool derived from simple clinical information can identify candidates for stress-only MPI studies with a beneficial impact on departmental workflow.

FDG-PET/CT and rest myocardial perfusion imaging to predict high-degree atrioventricular block recovery in cardiac sarcoidosis.

BACKGROUNDS: High-degree atrioventricular block (AVB) recovery in CS has been shown to be highly variable despite immunosuppressive treatment, with no reliable tool available to predict odds of reversibility. This study sought to evaluate the potential of combined fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and resting myocardial perfusion imaging (rMPI) to predict reversibility of newly diagnosed high-grade AVB in cardiac sarcoidosis (CS). METHODS: We performed a single-center, retrospective analysis of patients with CS presenting with high-grade AVB who underwent combined FDG-PET/CT and rMPI. The 2016 JCS and the 2014 HRS diagnostic criteria were used for the diagnosis of CS. Patients with a history of coronary artery disease or prior immunosuppressive treatment were excluded. Patients were divided into AVB recovery and non-recovery subgroups. CS disease staging was based on FDG-PET and rMPI findings: (Stage 0) normal FDG-PET and rMPI (Stage 1) positive FDG-PET and normal rMPI (Stage 2) positive FDG-PET with perfusion deficits on rMPI (Stage 3) normal FDG-PET with perfusion deficits on rMPI. RESULTS: Twenty-seven patients, including 13 demonstrating AVB recovery, were identified. Eleven out of fourteen (78.6%) patients presenting with stage 1 CS demonstrated AVB recovery. Stage 1 CS was significantly more present in the recovery group compared to the non-recovery group (84.6% vs 21.4%, P = .002). Eleven presented with stage 2 CS, with only 2 (18.2%) recovering AV nodal conduction. Stage 2 CS presented more frequently in the non-recovery group (64.3% vs 15.4%, P = .020). CONCLUSIONS: Combined FDG-PET and rMPI employed to stage CS disease presenting with high-degree AVB appears to have good performance for predicting likelihood of recovery.

Improving Detection of CAD and Prognosis with PET/CT Quantitative Absolute Myocardial Blood Flow Measurements.

PURPOSE OF REVIEW: The purpose of this review is to provide an overview of the role of PET MPI in the detection of CAD, focussing on the added value of MBF for diagnosis and prognostication. RECENT FINDINGS: Positron emission tomography (PET) myocardial perfusion imaging (MPI) is increasingly used for the risk stratification of patients with suspected or established coronary artery disease (CAD). PET MPI provides accurate and reproducible non-invasive quantification of myocardial blood flow (MBF) at rest and during hyperemia, providing incremental information over conventional myocardial perfusion alone. Inclusion of MBF in PET MPI interpretation improves both its sensitivity and specificity. Moreover, quantitative MBF measurements have repeatedly been shown to offer incremental and independent prognostic information over conventional clinical markers in a broad range of conditions, including in CAD. Quantitative MBF measurement is now an established and powerful tool enabling accurate risk stratification and guiding patients' management. The role of PET MPI and flow quantification in cardiac allograft vasculopathy (CAV), which represents a particular form of CAD, will also be reviewed.

Atypical Muscular Sarcoidosis Involvement Revealed by 18 F-FDG PET/CT.

We present the case of a 65-year-old woman with known pulmonary and muscular sarcoidosis who presented with dyspnea. FDG-PET/CT revealed unsuspected active myositis of multiple muscle groups, including the neck, and was useful in monitoring treatment response.

Development of scalable lymphatic system in the 4D XCAT phantom: Application to quantitative evaluation of lymphoma PET segmentations.

BACKGROUND: Digital anthropomorphic phantoms, such as the 4D extended cardiac-torso (XCAT) phantom, are actively used to develop, optimize, and evaluate a variety of imaging applications, allowing for realistic patient modeling and knowledge of ground truth. The XCAT phantom defines the activity and attenuation for a simulated patient, which includes a complete set of organs, muscle, bone, and soft tissue, while also accounting for cardiac and respiratory motion. However, the XCAT phantom does not currently include the lymphatic system, critical for evaluating medical imaging tasks such as sentinel node detection, node density measurement, and radiation dosimetry. PURPOSE: In this study, we aimed to develop a scalable lymphatic system in the XCAT phantom, to facilitate improved research of the lymphatic system in medical imaging. Using this scalable lymphatic system, we modeled the lymph node conglomerate pathology that is characteristically observed in primary mediastinal B-cell lymphoma (PMBCL). As an extended application, we evaluated positron emission tomography (PET) image quantification of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of these simulated lymphomas, though the phantoms may be applied to other imaging modalities and study design paradigms (e.g., image quality, detection). METHODS: A template model for the lymphatic system was developed based on anatomical data from the Visible Human Project of the National Library of Medicine. The segmented nodes and vessels were fit with non-uniform rational basis spline surfaces, and multichannel large deformation diffeomorphic metric mapping was used to propagate the template to different XCAT anatomies. To model conglomerates observed in PMBCL, lymph nodes were enlarged, converged within the mediastinum, and tracer concentration was increased. We used the phantoms as inputs to a PET simulation tool, which generated images using ordered subsets expectation maximization reconstruction with 2-8 mm Gaussian filters. Fixed thresholding (FT) and gradient segmentation were used to determine MTV and TLG. Percent bias (%Bias) and coefficient of variation (COV) were computed as measures of accuracy and precision, respectively, for each MTV and TLG measurement. RESULTS: Using the methodology described above, we introduced a scalable lymphatic system in the XCAT phantom, which allows for the radioactivity and attenuation ground truth to be generated in 116 ± 2.5 s using a 2.3 GHz processor. Within the Rhinoceros interface, lymph node anatomy and function were modified to create a cohort of 10 phantoms with lymph node conglomerates. Using the lymphoma phantoms to evaluate PET quantification of MTV, mean %Bias values were -9.3%, -41.3%, and 20.9%, while COV values were 4.08%, 7.6%, and 3.4% using 25% FT, 40% FT, and gradient segmentations, respectively. Comparatively for TLG, mean %Bias values were -27.4%, -45.8%, and -16.0%, while COV values were 1.9%, 5.7%, and 1.4%, for the 25% FT, 40% FT, and gradient segmentations, respectively. CONCLUSIONS: In this work, we upgraded the XCAT phantom to include a lymphatic system, comprised of a network of 276 scalable lymph nodes and corresponding vessels. As an application, we created a cohort of phantoms with lymph node conglomerates to evaluate lymphoma quantification in PET imaging, which highlights an important application of this work.

Predicting malaria outbreaks from sea surface temperature variability up to 9 months ahead in Limpopo, South Africa, using machine learning.

Malaria is the cause of nearly half a million deaths worldwide each year, posing a great socioeconomic burden. Despite recent progress in understanding the influence of climate on malaria infection rates, climatic sources of predictability remain poorly understood and underexploited. Local weather variability alone provides predictive power at short lead times of 1-2 months, too short to adequately plan intervention measures. Here, we show that tropical climatic variability and associated sea surface temperature over the Pacific and Indian Oceans are valuable for predicting malaria in Limpopo, South Africa, up to three seasons ahead. Climatic precursors of malaria outbreaks are first identified via lag-regression analysis of climate data obtained from reanalysis and observational datasets with respect to the monthly malaria case count data provided from 1998-2020 by the Malaria Institute in Tzaneen, South Africa. Out of 11 sea surface temperature sectors analyzed, two regions, the Indian Ocean and western Pacific Ocean regions, emerge as the most robust precursors. The predictive value of these precursors is demonstrated by training a suite of machine-learning classification models to predict whether malaria case counts are above or below the median historical levels and assessing their skills in providing early warning predictions of malaria incidence with lead times ranging from 1 month to a year. Through the development of this prediction system, we find that past information about SST over the western Pacific Ocean offers impressive prediction skills (~80% accuracy) for up to three seasons (9 months) ahead. SST variability over the tropical Indian Ocean is also found to provide good skills up to two seasons (6 months) ahead. This outcome represents an extension of the effective prediction lead time by about one to two seasons compared to previous prediction systems that were more computationally costly compared to the machine learning techniques used in the current study. It also demonstrates the value of climatic information and the prediction framework developed herein for the early planning of interventions against malaria outbreaks.

[18F]FDG-PET CT for the evaluation of native valve endocarditis.

BACKGROUND: We examined the use of [18F]FDG-PET/CT for the diagnosis of native valve endocarditis (NVE). METHODS: PET/CT images in patients with suspected NVE were retrospectively reviewed independently by two experienced physicians blinded to all clinical information. The gold standard consisted of surgical findings, when available, or the modified Duke criteria. RESULTS: Fifty four subjects were included, 31 (57%) with a diagnosis of NVE. [18F]FDG-PET/CT correctly identified 21/31 (67.7%) subjects, yielding a sensitivity and specificity of 68% (95% CI 49-83%) and 100% (95% CI 85-100%), respectively. The sensitivity and specificity of the modified Duke criteria were 48% and 74%, respectively. Positive and negative predictive values of PET were 100% (95% CI 84-100%) and 70% (95% CI 51-84%), respectively. Modifying the Duke criteria to include [18F]FDG-PET positivity as a major criterion increased sensitivity to 77% without affecting specificity and led to the correct reclassification of 8/18 (44.4%) subjects from Possible IE to Definite IE. CONCLUSION: The addition of a positive [18F]FDG-PET/CT as a major criterion in the modified Duke Criteria improved performance of the criteria for the diagnosis of NVE, particularly in those subjects with Possible IE.

Comparison of 18F-sodium fluoride positron emission tomography imaging and 99mTc-pyrophosphate in cardiac amyloidosis.

BACKGROUND: Pyrophosphate (PYP) scintigraphy provides high diagnostic accuracy for the detection of transthyretin (ATTR) cardiac amyloidosis (CA). There has recently been emerging interest in using 18F-sodium fluoride (NaF) for this application, yet its sensitivity has never been directly compared to that of PYP, the current molecular gold standard METHODS: Twelve subjects with ATTR-CA and 5 controls referred for PYP-SPECT were prospectively enrolled. 18F-NaF PET/CT scans were performed at 1 and 3 hours. Qualitative and quantitative analyses of the images were performed, and the sensitivity of 18F-NaF PET/CT and PYP-SPECT were compared RESULTS: Visual interpretation of NaF PET/CT yielded a sensitivity of 0.25 (95% CI 0.089 to 0.53) for the detection of ATTR-CA, which is significantly inferior to that of PYP-SPECT/CT (100%, P = .016). Visual interpretation at 3 hours yielded a similar sensitivity of 0.30 (95% CI 0.11 to 0.60, P = 1.00). There were no false-positive NaF PET studies. Mean target-to-background ratio (TBRmean) at 1h did not differ significantly (P = .21) in ATTR-CA subjects (0.83 ± 0.15) compared to controls (0.72 ± 0.15). Receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.69 ± 0.16 (95% CI 0.37 to 1.00, P = .23). CONCLUSION: With qualitative and quantitative analyses, sensitivity of NaF PET/CT is significantly inferior to that of PYP-SPECT for the diagnosis of ATTR-CA.

Incremental Value of FDG-PET in the Evaluation of Cardiac Masses.

PURPOSE OF REVIEW: This study aims to review the various roles and evidence underlying the use of fluorodeoxyglucose (FDG) PET/CT and PET/MR for the assessment of cardiac masses. RECENT FINDINGS: The role of FDG-PET for the evaluation of cardiac masses continues to evolve. Studies have shown that FDG-PET is particularly well-suited for differentiating malignant from benign cardiac lesions based on their metabolic activity. Furthermore, FDG-PET is uniquely positioned to investigate patients with cardiac mass as most malignant cardiac lesions are metastasis. Finally, FDG-PET enables staging of patients with primary malignant cardiac tumor, identification of potential biopsy site, and planning of radiotherapy. FDG-PET is a complementary tool for the evaluation of patients with cardiac mass and can help differentiate benign from malignant lesions, as well as provide whole-body staging.

Assessing cardiovascular infection and inflammation with FDG-PET.

FDG-PET has been shown to be a useful imaging modality for the assessment of cardiovascular infection and inflammatory pathologies. However, interpretation of these studies can be challenging in light of the variability of physiological myocardial uptake and, occasionally, interpreter's lack of familiarity with the typical findings present in cardiac pathologies. In this article, we review established and emerging applications for cardiovascular infection and inflammation imaging with FDG-PET and present typical examples of representative pathologies.

FDG PET Findings Post-COVID Vaccinations: Signs of the Times?

ABSTRACT: Vaccinations can cause hypermetabolic axillary lymphadenopathy on FDG PET. We present the case of a 71-year-old man who underwent FDG PET/CT for melanoma staging 6 days following a COVID (coronavirus disease) vaccination. Imaging showed a prominent intramuscular mass at the vaccination site, in addition to extensive axillary lymphadenopathy. The mass was compatible with a hematoma at the vaccination site, and the lymphadenopathy was most likely reactive. This case demonstrates unconventional findings in response to a routine vaccination event-findings that, in light of current world events, are likely to be routinely encountered on PET imaging and that should be recognized reactive rather malignant.

Metastatic Adamantinoma of the Femur on FDG PET/CT: Atypical Presentation of a Rare Disease.

ABSTRACT: Adamantinomas are rare malignant primary bone tumors, which typically arise in young patients, are generally low-grade tumors, and classically arise from the anterior tibial diaphysis. We present the case of a 70-year-old woman who underwent repeat imaging with FDG PET for a pathologically proven case of femoral adamantinoma who experienced a relatively rapid development of metastatic disease with an atypical distribution of lesions.

Bone Mineral Densitometry Reporting: Pearls and Pitfalls.

Dual-energy X-ray absorptiometry (DXA) is the method of choice for assessing bone mineral density (BMD). Unfortunately, the performance and interpretation of DXA can be challenging and errors are common. In fact, it has been reported that up to 90% of BMD reports contain at least 1 error. Errors can be the result of technique or interpretative in nature or both and can result in inappropriate diagnosis and management. In this article, we review the various types of pitfalls frequently encountered by physicians interpreting DXA studies. Being aware of these pitfalls will help readers recognize and avoid them when encountered in clinical practice.

Examining the sensitivity of 18F-NaF PET for the imaging of cardiac amyloidosis.

BACKGROUND: Conventional nuclear imaging with bone-seeking radiopharmaceuticals has been shown to be a sensitive test for the detection of transthyretin cardiac amyloidosis (ATTR); however, to date, few data exist on the utility of 18F-sodium fluoride (NaF) positron emission tomography (PET) in subjects with cardiac amyloidosis (CA). METHODS: Myocardial perfusion imaging and cardiac 18F-NaF PET/CT of 7 subjects with ATTR, four with light-chain CA (AL), and four controls were retrospectively reviewed. Qualitative interpretation and quantitative analyses with average left ventricular standardized uptake values (SUVmean) and target-to-background ratios (TBRmean) were performed. RESULTS: Average TBRmean was significantly increased in subjects with ATTR (0.98 ± 0.09) compared to AL (0.85 ± 0.08, P = .026) and CTL (0.82 ± 0.07, P = .020), while SUVmean was not (P = .14). Receiver-operator characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.91, with a sensitivity/specificity of 75%/100% for TBRmean using a cutoff value of 0.89 for the diagnosis of ATTR. Qualitative interpretation resulted in a sensitivity/specificity of 57%/100% for ATTR. CONCLUSIONS: While 18F-NaF PET/CT demonstrates good diagnostic accuracy for ATTR, particularly when using quantitative analysis, the low TBRmean values observed in ATTR indicate poor myocardial signal. 18F-NaF PET/CT is not yet ready for clinical use in CA until further comparison studies are performed with 99mTc-DPD/PYP.

Sinus Tarsi Syndrome on Bone Scintigraphy With SPECT/CT: Spectrum of Findings.

ABSTRACT: Sinus tarsi syndrome is a common cause of hindfoot pain in adults; however, diagnosis on planar bone scintigraphy can be challenging. We present 3 cases of sinus tarsi syndrome, review the spectrum of imaging findings associated with sinus tarsi syndrome, and show the key role that SPECT/CT can play in its diagnosis.