Increased Metabolic Activity on 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography in Human Immunodeficiency Virus-Associated Immune Reconstitution Inflammatory Syndrome.

Background: Immune reconstitution inflammatory syndrome (IRIS) represents an unexpected inflammatory response shortly after initiation of antiretroviral therapy (ART) in some human immunodeficiency virus (HIV)-infected patients with underlying neoplasia or opportunistic infections, including tuberculosis. We hypothesized that IRIS is associated with increased glycolysis and that 18F-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) could help identify high-risk subjects. Methods: In this prospective cohort study, 30 HIV-infected patients (CD4+ count <100 cells/µL) underwent FDG-PET/CT scans at baseline and 4-8 weeks after ART initiation. Ten patients developed IRIS (6 mycobacterial). Results: At baseline, total glycolytic activity, total lesion volume, and maximum standardized uptake values (SUVs) of pathologic FDG uptake (reflective of opportunistic disease burden) were significantly higher in IRIS vs non-IRIS (P = .010, .017, and .029, respectively) and significantly correlated with soluble inflammatory biomarkers (interferon-γ, myeloperoxidase, tumor necrosis factor, interleukin 6, soluble CD14). Baseline bone marrow (BM) and spleen FDG uptake was higher in mycobacterial IRIS specifically. After ART initiation, BM and spleen mean SUV decreased in non-IRIS (P = .004, .013) but not IRIS subjects. Our results were supported by significantly higher glucose transporter 1 (Glut-1) expression of CD4+ cells and monocytes after ART initiation in IRIS/mycobacterial IRIS compared with non-IRIS patients. Conclusions: We conclude that increased pathologic metabolic activity on FDG-PET/CT prior to ART initiation is associated with IRIS development and correlates with inflammatory biomarkers. Abnormally elevated BM and spleen metabolism is associated with mycobacterial IRIS, HIV viremia, and Glut-1 expression on CD4+ cells and monocytes. Clinical Trials Registration: NCT02147405.

Prognostic Utility of Total 68Ga-DOTATATE-Avid Tumor Volume in Patients With Neuroendocrine Tumors.

BACKGROUND & AIMS: Survival times vary among patients with neuroendocrine tumors (NETs) - even among those with the same site, stage, and grade of primary tumor. This makes it difficult to select treatment for patients with unresectable NETs because some patients can survive decades without treatment. 68Gallium-DOTATATE positron emission tomography with computed tomography (68Ga-DOTATATE PET/CT) is a sensitive imaging technique for detection of NETs. We investigated the prognostic accuracy of 68Ga-DOTATATE PET/CT-based analysis of tumor volume in patients with NETs. METHODS: We performed a prospective study of 184 patients with NETs (128 [69.6%] with metastases and 11 patients [6.0%] with locally advanced disease) at the National Institutes of Health Clinical Center (Bethesda, MD) from 2013 through 2017. All patients underwent 68Ga-DOTATATE PET/CT image analysis and total 68Ga-DOTATATE-Avid tumor volume (68Ga-DOTATATE TV) was determined. We also measured fasting serum chromogranin A, neuron-specific enolase, gastrin, glucagon, vasoactive intestinal peptide, pancreatic polypeptide, and 24-hour urinary 5-hydroxyindoleacetic acid levels in all patients. Disease progression was defined as a new lesion or a growth of a known lesion during the interval between baseline 68Ga-DOTATATE PET/CT scan and follow-up imaging (14.0 ± 6.1 months; range, 1-35 months). The primary outcomes were progression-free survival (PFS) and disease-specific mortality during a median follow-up time of 18 months (range, 4-35 months). RESULTS: We found an inverse correlation between quartiles of 68Ga-DOTATATE TV and PFS (P = .001) and disease-specific survival (P = .002). A 68Ga-DOTATATE TV of 7.0 mL or more was associated with higher odds of disease progression (hazard ratio, 3.0; P = .04). A 68Ga-DOTATATE TV of 35.8 mL or more was associated with increased risk of disease-specific death (hazard ratio, 10.6) in multivariable analysis (P = .01), as well as in subgroup analysis of patients with pancreatic NETs. CONCLUSIONS: In a prospective study, we demonstrated the prognostic utility of 68Ga-DOTATATE TV in a large cohort of patients with NETs, in terms of PFS and disease-specific mortality.

In vivo imaging of sterile microglial activation in rat brain after disrupting the blood-brain barrier with pulsed focused ultrasound: [18F]DPA-714 PET study.

BACKGROUND: Magnetic resonance imaging (MRI)-guided pulsed focused ultrasound combined with the infusion of microbubbles (pFUS+MB) induces transient blood-brain barrier opening (BBBO) in targeted regions. pFUS+MB, through the facilitation of neurotherapeutics' delivery, has been advocated as an adjuvant treatment for neurodegenerative diseases and malignancies. Sterile neuroinflammation has been recently described following pFUS+MB BBBO. In this study, we used PET imaging with [18F]-DPA714, a biomarker of translocator protein (TSPO), to assess for neuroinflammatory changes following single and multiple pFUS+MB sessions. METHODS: Three groups of Sprague-Dawley female rats received MRI-guided pFUS+MB (Optison™; 5-8 × 107 MB/rat) treatments to the left frontal cortex and right hippocampus. Group A rats were sonicated once. Group B rats were sonicated twice and group C rats were sonicated six times on weekly basis. Passive cavitation detection feedback (PCD) controlled the peak negative pressure during sonication. We performed T1-weighted scans immediately after sonication to assess efficiency of BBBO and T2*-weighted scans to evaluate for hypointense voxels. [18F]DPA-714 PET/CT scans were acquired after the BBB had closed, 24 h after sonication in group A and within an average of 10 days from the last sonication in groups B and C. Ratios of T1 enhancement, T2* values, and [18F]DPA-714 percent injected dose/cc (%ID/cc) values in the targeted areas to the contralateral brain were calculated. Histological assessment for microglial activation/astrocytosis was performed. RESULTS: In all groups, [18F]DPA-714 binding was increased at the sonicated compared to non-sonicated brain (%ID/cc ratios > 1). Immunohistopathology showed increased staining for microglial and astrocytic markers in the sonicated frontal cortex compared to contralateral brain and to a lesser extent in the sonicated hippocampus. Using MRI, we documented BBB disruption immediately after sonication with resolution of BBBO 24 h later. We found more T2* hypointense voxels with increasing number of sonications. In a longitudinal group of animals imaged after two and after six sonications, there was no cumulative increase of neuroinflammation on PET. CONCLUSION: Using [18F]DPA-714 PET, we documented in vivo neuroinflammatory changes in association with pFUS+MB. Our protocol (utilizing PCD feedback to minimize damage) resulted in neuroinflammation visualized 24 h post one sonication. Our findings were supported by immunohistochemistry showing microglial activation and astrocytosis. Experimental sonication parameters intended for BBB disruption should be evaluated for neuroinflammatory sequelae prior to implementation in clinical trials.

3D Volumetric Measurements of GH Secreting Adenomas Correlate with Baseline Pituitary Function, Initial Surgery Success Rate, and Disease Control.

There is scarce data on the clinical utility of volume measurement for growth hormone (GH)-secreting pituitary adenomas. The current study objective was to assess the association between pituitary adenoma volumes and baseline endocrine evaluation, initial surgical success rate, and disease control among patients with acromegaly. A retrospective cohort study was conducted at a clinical research center including patients with acromegaly due to GH-secreting pituitary adenomas. Baseline hormonal evaluation and adenoma characteristics according to MRI were collected. Volumetric measurements of pituitary adenomas were performed using a semi-automated lesion segmentation and tumor-volume assessment tools. Rates of post-operative medical treatment, radiation therapy, and re-operation were gathered from the patients' medical records. Twenty seven patients (11 females) were included, median age 21.0 years (interquartile range 29 years, range 3-61 years). Patients harboring adenomas with a volume <2 000 mm3 had higher chance to achieve disease remission [94.1% (n=16) vs. 50.0% (n=4), p<0.05]. Adenoma volumes positively correlated with baseline plasma GH levels before and after oral glucose administration, and with plasma IGF-I and PRL levels. Adenoma volume had negative correlation with morning plasma cortisol levels. Finally, patients harboring larger adenomas required 2nd surgery and/or medical treatment more often compared with subjects with smaller adenomas. Accurate 3D volume measurement of GH-secreting pituitary adenomas may be used for the prediction of initial surgery success and for disease control rates among patients with a GH-secreting pituitary adenomas and performs better than standard size assessments.

Kidney Stones as an Underrecognized Clinical Sign in Pediatric Cushing Disease.

OBJECTIVE: To investigate the prevalence of kidney stones in a population of children with Cushing disease (CD) and to compare it with the prevalence of kidney stones in healthy children. STUDY DESIGN: Clinical and biochemical data from 139 pediatric patients with CD (68 females, 71 males) were analyzed retrospectively. Computed tomography scans were reviewed for kidney stones. RESULTS: Among 139 patients, 27 with CD (19.4%) had either radiographic evidence and/or a history of kidney stones. Those with kidney stones had higher urine free cortisol (P = .008) and transsphenoidal surgery at an older age (P = .007). The average urinary calcium/creatinine ratio was elevated in patients with CD (0.22 ± 0.11). The prevalence of kidney stones was higher in children with CD than in normal children (19.42% vs 1.0%; P < .001). CONCLUSION: Our results illustrate that kidney stones are an underestimated complication of pediatric CD, especially when compared with the prevalence of nephrolithiasis in the general pediatric population. Long-term consequences for kidney function are not known and need to be studied.

Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends.

The computer-based process of identifying the boundaries of lung from surrounding thoracic tissue on computed tomographic (CT) images, which is called segmentation, is a vital first step in radiologic pulmonary image analysis. Many algorithms and software platforms provide image segmentation routines for quantification of lung abnormalities; however, nearly all of the current image segmentation approaches apply well only if the lungs exhibit minimal or no pathologic conditions. When moderate to high amounts of disease or abnormalities with a challenging shape or appearance exist in the lungs, computer-aided detection systems may be highly likely to fail to depict those abnormal regions because of inaccurate segmentation methods. In particular, abnormalities such as pleural effusions, consolidations, and masses often cause inaccurate lung segmentation, which greatly limits the use of image processing methods in clinical and research contexts. In this review, a critical summary of the current methods for lung segmentation on CT images is provided, with special emphasis on the accuracy and performance of the methods in cases with abnormalities and cases with exemplary pathologic findings. The currently available segmentation methods can be divided into five major classes: (a) thresholding-based, (b) region-based, (c) shape-based, (d) neighboring anatomy-guided, and (e) machine learning-based methods. The feasibility of each class and its shortcomings are explained and illustrated with the most common lung abnormalities observed on CT images. In an overview, practical applications and evolving technologies combining the presented approaches for the practicing radiologist are detailed.

Erratum: [Corrigendum] CD271+ stem cell treatment of patients with chronic stroke: A retrospective case series report.

[This corrects the article DOI: 10.3892/etm.2020.8948.].

Leveraging artificial intelligence to advance the understanding of chemical neurotoxicity.

Neurotoxicology is a specialty that aims to understand and explain the impact of chemicals, xenobiotics and physical conditions on nervous system function throughout the life span. Herein, we point to the need for integration of novel translational bioinformatics and chemo-informatics approaches, such as machine learning (ML) and artificial intelligence (AI) to the discipline. Specifically, we advance the notion that AI and ML will be helpful in identifying neurotoxic signatures, provide reliable data in predicting neurotoxicity in the context of genetic variability, and improve the understanding of neurotoxic outcomes associated with exposures to mixtures, to name a few.

Current status and future prospects of PET-imaging applications in patients with gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs).

Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) represent a heterogeneous group of rare neoplasms with increasing incidence over the last decades. Localization of GEP-NETs and their metastases is a vital component for the implementation of accurate and patient-tailored treatment strategies. Addressing this challenge requires the employment of multidisciplinary imaging approaches, with hybrid positron emission tomography/computed tomography (PET/CT) imaging techniques standing at the forefront of this effort. GEP-NETs exhibit several pathophysiologic characteristics, which can serve as highly specific molecular targets that can be effectively visualized and quantified by means of PET-radiopharmaceuticals, facilitating diagnosis, accurate staging and efficient monitoring of treatment response. Furthermore, the capability for whole-body, in-vivo, non-invasive characterization of the molecular heterogeneity of the disease, provides strong prognostic information, while enabling the selection of patients suitable for precision-based theranostic approaches. The dual tracer (18F-FDG & 68Ga-DOTA-peptides) PET/CT imaging approach is the current optimal diagnostic imaging strategy, since it enables tumor localization, accurate staging, non-invasive whole-body total tumor burden characterization of disease heterogeneity, while providing strong prognostic information and guidance towards treatment strategy. Moreover, 64Cu-DOTATATE has been recently approved by FDA for SSTRs positive NETs, promising substantial diagnostic and logistical benefits. Furthermore, 18F-DOPA offers diagnostic capabilities for serotonin-secreting GEP-NETs which are not characterized by cell-surface over-expression of somatostatin receptors (SSTRs) and cannot be seen on morphological imaging. In addition, PET/CT with agents targeting the expression of glucagon-like peptide-1 receptor (GLP-R1) should be considered in cases of clinical suspicion for insulinomas that cannot be detected by morphological imaging or STTRs PET/CT imaging.

Advanced clinical imaging for the evaluation of stem cell based therapies.

Introduction: As stem cell treatments reach closer to the clinic, the need for appropriate noninvasive imaging for accurate disease diagnosis, treatment planning, follow-up, and early detection of complications, is constantly rising. Clinical radiology affords an extensive arsenal of advanced imaging techniques, to provide anatomical and functional information on the whole spectrum of stem cell treatments from diagnosis to follow-up.Areas covered: This manuscript aims at providing a critical review of major published studies on the utilization of advanced imaging for stem cell treatments. Uses of magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and positron emission tomography (PET) are reviewed and interrogated for their applicability to stem cell imaging.Expert opinion: A wide spectrum of imaging methods have been utilized for the evaluation of stem cell therapies. The majority of published techniques are not clinically applicable, using methods exclusively applicable to animals or technology irrelevant to current clinical practice. Harmonization of preclinical methods with clinical reality is necessary for the timely translation of stem cell therapies to the clinic. Methods such as diffusion weighted MRI, hybrid imaging, and contrast-enhanced ultrasound hold great promise and should be routinely incorporated in the evaluation of patients receiving stem cell treatments.

Cross-Sectional Imaging Useful in Melorheostosis.

Melorheostosis is a rare disease of bone overgrowth that is primarily diagnosed based on imaging studies. Recently, the association of different radiological patterns of the disease with distinct genetic cause was reported. Several case reports have described the radiological findings in patients with melorheostosis. However, the added value of cross-sectional imaging with CT and MRI beyond X-rays has not been investigated. The aim of the current study was to investigate this existing gap in knowledge. Forty patients with melorheostosis seen at the National Institute of Health Clinical Center were included in the study, and all their imaging studies were analyzed. The sequence of interpretation was X-ray followed by CT and then MRI. CT images were extracted from whole-body 18F-sodium fluoride positron emission tomography/CT studies. The information from CT reclassified the initial X-rays based radiological pattern in 13 patients. Additionally, CT comprehensively identified joint involvement and disease extent. In 76% of patients (n = 29) who underwent MRI, additional findings were noted, ranging from soft tissue edema to identification of soft tissue masses and incidental findings. MRI did not provide additional information on skeletal lesions beyond CT scans. However, it revealed the extension of soft tissue ossification into ischiofemoral space in four patients who complained of deep gluteal pain consistent with ischiofemoral impingement syndrome. In addition, MRI revealed soft tissue edema in 20 patients, 9 of whom had bone marrow edema and periosteal edema in the tibias consistent with shin splints. These findings suggest that select patients with melorheostosis should be evaluated with both CT and MRI, particularly patients in whom the distribution of pain does not correlate with the anatomic location of the disease in plain radiographs. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.

Emerging deep learning techniques using magnetic resonance imaging data applied in multiple sclerosis and clinical isolated syndrome patients (Review).

Computer-aided diagnosis systems aim to assist clinicians in the early identification of abnormal signs in order to optimize the interpretation of medical images and increase diagnostic precision. Multiple sclerosis (MS) and clinically isolated syndrome (CIS) are chronic inflammatory, demyelinating diseases affecting the central nervous system. Recent advances in deep learning (DL) techniques have led to novel computational paradigms in MS and CIS imaging designed for automatic segmentation and detection of areas of interest and automatic classification of anatomic structures, as well as optimization of neuroimaging protocols. To this end, there are several publications presenting artificial intelligence-based predictive models aiming to increase diagnostic accuracy and to facilitate optimal clinical management in patients diagnosed with MS and/or CIS. The current study presents a thorough review covering DL techniques that have been applied in MS and CIS during recent years, shedding light on their current advances and limitations.

Pituitary Imaging Abnormalities and Related Endocrine Disorders in Erdheim-Chester Disease.

PURPOSE: We examined abnormal pituitary imaging (API) and associated endocrine dysfunction in subjects with ECD. METHODS: A cross-sectional descriptive examination of a natural history cohort study diagnosed with ECD was conducted at a clinical research center. Subjects underwent baseline endocrine tests of anterior and posterior pituitary function and dedicated pituitary gland MRI scans. We determined the frequency of various pituitary imaging abnormalities in ECD and assessed its relationships with age, sex, body mass index (BMI), BRAF V600E status, high sensitivity C-reactive protein (hsCRP), erythrocyte sedimentation rate (ESR), pituitary hormone deficits and number, diabetes insipidus (DI), and panhypopituitarism. RESULTS: Our cohort included 61 subjects with ECD [age (SD): 54.3 (10.9) y, 46 males/15 females]. API was present in 47.5% (29/61) of ECD subjects. Loss of the posterior pituitary bright spot (36.1%) followed by thickened pituitary stalk (24.6%), abnormal enhancement (18.0%), and pituitary atrophy (14.8%) were the most common abnormalities. DI and panhypopituitarism were more frequent in subjects with API without differences in age, sex distribution, hsCRP, ESR, and BRAF V600E status compared to normal pituitary imaging. CONCLUSIONS: We noted a high burden of API and endocrinopathies in ECD. API was highly associated with the presence of panhypopituitarism and DI. Therefore, a thorough assessment of hypothalamic-pituitary integrity should be considered in subjects with ECD.

Volumetric Modeling of Adrenal Gland Size in Primary Bilateral Macronodular Adrenocortical Hyperplasia.

CONTEXT: Radiological characterization of adrenal size in primary bilateral macronodular adrenocortical hyperplasia (PBMAH) has not been previously investigated. OBJECTIVE: We hypothesized that volumetric modeling of adrenal gland size may correlate with biochemical disease severity in patients with PBMAH. Secondary analysis of patients with concurrent primary aldosteronism (PA) was performed. DESIGN: A retrospective cross-sectional analysis of 44 patients with PBMAH was conducted from 2000 to 2019. SETTING: Tertiary care clinical research center. PATIENTS: Patients were diagnosed with PBMAH based upon clinical, genetic, radiographic and biochemical characteristics. INTERVENTION: Clinical, biochemical, and genetic data were obtained. Computed tomography scans were used to create volumetric models by manually contouring both adrenal glands in each slice using Vitrea Core Fx v6.3 software (Vital Images, Minnetonka, Minnesota). MAIN OUTCOME AND MEASURES: 17-hydroxycorticosteroids (17-OHS), ARMC5 genetics, and aldosterone-to-renin ratio (ARR) were retrospectively obtained. Pearson test was used for correlation analysis of biochemical data with adrenal volume. RESULTS: A cohort of 44 patients with PBMAH was evaluated, with a mean age (±SD) of 53 ±â€…11.53. Eight patients met the diagnostic criteria for PA, of whom 6 (75%) were Black. In the Black cohort, total adrenal volumes positively correlated with midnight cortisol (R = 0.76, P = 0.028), urinary free cortisol (R = 0.70, P = 0.035), and 17-OHS (R = 0.87, P = 0.0045), with a more pronounced correlation with left adrenal volume alone. 17-OHS concentration positively correlated with total, left, and right adrenal volume in patients harboring pathogenic variants in ARMC5 (R = 0.72, P = 0.018; R = 0.65, P = 0.042; and R = 0.73, P = 0.016, respectively). CONCLUSIONS: Volumetric modeling of adrenal gland size may associate with biochemical severity in patients with PBMAH, with particular utility in Black patients.

Musculoskeletal trauma imaging in the era of novel molecular methods and artificial intelligence.

Over the past decade rapid advancements in molecular imaging (MI) and artificial intelligence (AI) have revolutionized traditional musculoskeletal radiology. Molecular imaging refers to the ability of various methods to in vivo characterize and quantify biological processes, at a molecular level. The extracted information provides the tools to understand the pathophysiology of diseases and thus to early detect, to accurately evaluate the extend and to apply and evaluate targeted treatments. At present, molecular imaging mainly involves CT, MRI, radionuclide, US, and optical imaging and has been reported in many clinical and preclinical studies. Although originally MI techniques targeted at central nervous system disorders, later on their value on musculoskeletal disorders was also studied in depth. Meaningful exploitation of the large volume of imaging data generated by molecular and conventional imaging techniques, requires state-of-the-art computational methods that enable rapid handling of large volumes of information. AI allows end-to-end training of computer algorithms to perform tasks encountered in everyday clinical practice including diagnosis, disease severity classification and image optimization. Notably, the development of deep learning algorithms has offered novel methods that enable intelligent processing of large imaging datasets in an attempt to automate decision-making in a wide variety of settings related to musculoskeletal trauma. Current applications of AI include the diagnosis of bone and soft tissue injuries, monitoring of the healing process and prediction of injuries in the professional sports setting. This review presents the current applications of novel MI techniques and methods and the emerging role of AI regarding the diagnosis and evaluation of musculoskeletal trauma.

CD271+ stem cell treatment of patients with chronic stroke: : A retrospective case series report.

Patients with chronic stroke have currently little hope for motor improvement towards regaining independent activities of daily living; stem cell treatments offer a new treatment option and needs to be developed. Patients with chronic stroke (more than 3 months prior to stem cell treatment, mean 21.2 months post-stroke) were treated with CD271+ stem cells, 7 patients received autologous and 1 allogeneic cells from first degree relative; administration was intravenous in 1 and intrathecal in 7 patients. Each patient received a single treatment consisting of 2-5x106 cells/kg and they were followed up for up to 12 months. There were significant improvements in expressive aphasia (2/3 patients) spasticity (5/5, of which 2 were transient), and small improvements in motor function (2/8 patients). Although motor improvements were minor in our chronic stroke patients, improvements in aphasia and spasticity were significant and in the context of good safety we are advocating further administration and clinical studies of CD271+ stem cells not only in chronic stroke patients, but also for spastic paresis/plegia; a different, yet unexplored application is pulmonary emphysema.

Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care (Review).

The new era of artificial intelligence (AI) has introduced revolutionary data­driven analysis paradigms that have led to significant advancements in information processing techniques in the context of clinical decision­support systems. These advances have created unprecedented momentum in computational medical imaging applications and have given rise to new precision medicine research areas. Radiogenomics is a novel research field focusing on establishing associations between radiological features and genomic or molecular expression in order to shed light on the underlying disease mechanisms and enhance diagnostic procedures towards personalized medicine. The aim of the current review was to elucidate recent advances in radiogenomics research, focusing on deep learning with emphasis on radiology and oncology applications. The main deep learning radiogenomics architectures, together with the clinical questions addressed, and the achieved genetic or molecular correlations are presented, while a performance comparison of the proposed methodologies is conducted. Finally, current limitations, potentially understudied topics and future research directions are discussed.