Search

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., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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 ( 18 F-FDG & 68 Ga-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, 64 Cu-DOTATATE has been recently approved by FDA for SSTRs positive NETs, promising substantial diagnostic and logistical benefits. Furthermore, 18 F-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., (Copyright © 2021. Published by Elsevier B.V.)

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., Competing Interests: DAS is the Editor-in-Chief of the journal, but had no personal involvement in the reviewing process, or any influence in terms of adjudicating on the final decision for this article. All the authors declare that they have no competing interests., (Copyright: © Kontopodis et al.)

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.

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.

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., Competing Interests: The authors declare that there is no conflict of interests that could be perceived as prejudicing the impartiality of the research reported., (© 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.)

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., Competing Interests: Declaration of Competing Interest No conflict of interest to disclose for all authors, (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The coronavirus pandemic and its unprecedented consequences globally has spurred the interest of the artificial intelligence research community. A plethora of published studies have investigated the role of imaging such as chest X-rays and computer tomography in coronavirus disease 2019 (COVID-19) automated diagnosis. Οpen repositories of medical imaging data can play a significant role by promoting cooperation among institutes in a world-wide scale. However, they may induce limitations related to variable data quality and intrinsic differences due to the wide variety of scanner vendors and imaging parameters. In this study, a state-of-the-art custom U-Net model is presented with a dice similarity coefficient performance of 99.6% along with a transfer learning VGG-19 based model for COVID-19 versus pneumonia differentiation exhibiting an area under curve of 96.1%. The above was significantly improved over the baseline model trained with no segmentation in selected tomographic slices of the same dataset. The presented study highlights the importance of a robust preprocessing protocol for image analysis within a heterogeneous imaging dataset and assesses the potential diagnostic value of the presented COVID-19 model by comparing its performance to the state of the art., (Copyright: © Trivizakis et al.)

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 ± 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., (Published by Oxford University Press on behalf of the Endocrine Society 2020.)

Importance: Erdheim-Chester disease (ECD) is a rare non-Langerhans cell histiocytosis affecting multiple organs and commonly caused by somatic pathogenic variants in BRAF V600E and mitogen-activated protein kinase genes. Clinical features of ECD result from histiocytic involvement of various tissues; while endocrine involvement in ECD occurs frequently, the prevalence of central or primary hypothyroidism has not been thoroughly investigated., Objective: To assess hypothalamus-pituitary-thyroid (HPT) dysfunction in patients with ECD., Design, Setting, and Participants: This cross-sectional study included 61 patients with ECD who were enrolled in a natural history study at a tertiary care center between January 2011 and December 2018. ECD was diagnosed on the basis of clinical, genetic, and histopathological features. Data were analyzed in March 2020., Exposure: Diagnosis of ECD., Main Outcomes and Measures: Main outcome was the prevalence of thyroid dysfunction in adults with ECD compared with community estimates. Patients underwent baseline evaluation with a thyroid function test, including thyrotropin, free thyroxine (fT4), and total thyroxine (T4), and sellar imaging with magnetic resonance imaging or computed tomography scan. The association of HPT dysfunction was assessed for differences in age, sex, body mass index, BRAF V600E status, high sensitivity C-reactive protein level, sellar imaging, and pituitary hormonal dysfunction., Results: A total of 61 patients with ECD (46 [75%] men; mean [SD] age, 54.3 [10.9] years) were evaluated. Seventeen patients (28%) had hypothyroidism requiring levothyroxine therapy. The prevalence of both central and primary hypothyroidism were higher than community estimates (central hypothyroidism: 9.8% vs 0.1%; odds ratio, 109.0; 95% CI, 37.4-260.6; P < .001; primary hypothyroidism: 18.0% vs 4.7%; OR, 4.4; 95% CI, 2.1-8.7; P < .001). Patients with hypothyroidism (both primary and central), compared with patients with euthyroidism, had higher body mass index (median [interquartile range] 31.4 [28.3-38.3] vs 26.7 [24.4-31.9]; P = .004) and a higher prevalence of panhypopituitarism (7 [47%] vs 3 [7%]; P < .001). Among patients with hypothyroidism, those with central hypothyroidism, compared with patients with primary hypothyroidism, had a lower mean (SD) body mass index (28.3 [2.6] vs 36.3 [5.9]; P = .007) and higher frequencies of abnormal sellar imaging (5 [83%] vs 3 [27%]; P = .050) and panhypopituitarism (5 [83%] vs 3 [27%]; P = .050)., Conclusions and Relevance: In this cohort study, a higher prevalence of central and primary hypothyroidism was identified in patients with ECD compared with the community. There should be a low threshold for testing for hypothyroidism in patients with ECD, and treatment should follow standard guidelines.

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 2-5x10 6 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., Competing Interests: DAS is the Editor-in-Chief for the journal, but had no personal involvement in the reviewing process, or any influence in terms of adjudicating on the final decision, for this article. The other authors declare that they have no competing interests., (Copyright: © Stancioiu et al.)

Blood-brain barrier opening (BBBO) with pulsed Focused Ultrasound (pFUS) and microbubbles (MB) has received increasing interest as a method for neurotherapeutics of the central nervous system. In general, conventional MRI [i.e., T2w, T2 ∗ w, gadolinium (Gd) enhanced T1w] is used to monitor the effects of pFUS+MB on BBBO and/or assess whether sonication results in parenchymal damage. This study employed multimodal MRI techniques and 18 F-Fludeoxyglucose (FDG) PET to evaluate the effects of single and multiple weekly pFUS+MB sessions on morphology and glucose utilization levels in the rat cortex and hippocampus. pFUS was performed with 0.548 MHz transducer with a slow infusion over 1 min of Optison TM (5-8 × 10 7 MB) in nine focal points in cortex and four in hippocampus. During pFUS+MB treatment, Gd-T1w was performed at 3 T to confirm BBBO, along with subsequent T2w, T2 ∗ w, DTI and glucose CEST (glucoCEST)-weighted imaging by high field 9.4 T and compared with FDG-PET and immunohistochemistry. Animals receiving a single pFUS+MB exhibited minimal hypointense voxels on T2 ∗ w. Brains receiving multiple pFUS+MB treatments demonstrated persistent T2w and T2 ∗ abnormalities associated with changes in DTI and glucoCEST when compared to contralateral parenchyma. Decreased glucoCEST contrast was substantiated by FDG-PET in cortex following multiple sonications. Immunohistochemistry showed significantly dilated vessels and decreased neuronal glucose transporter (GLUT3) expression in sonicated cortex and hippocampus without changes in neuronal counts. These results suggest the importance to standardize MRI protocols in concert with advanced imaging techniques when evaluating long term effects of pFUS+MB BBBO in clinical trials for neurological diseases., (Copyright © 2020 Tu, Kovacs, Sundby, Witko, Papadakis, Reid, Hammoud and Frank.)

We are being confronted with the most consequential pandemic since the Spanish flu of 1918‑1920 to the extent that never before have 4 billion people quarantined simultaneously; to address this global challenge we bring to the forefront the options for medical treatment and summarize SARS‑CoV2 structure and functions, immune responses and known treatments. Based on literature and our own experience we propose new interventions, including the use of amiodarone, simvastatin, pioglitazone and curcumin. In mild infections (sore throat, cough) we advocate prompt local treatment for the naso‑pharynx (inhalations; aerosols; nebulizers); for moderate to severe infections we propose a tried‑and‑true treatment: the combination of arginine and ascorbate, administered orally or intravenously. The material is organized in three sections: i) Clinical aspects of COVID‑19; acute respiratory distress syndrome (ARDS); known treatments; ii) Structure and functions of SARS‑CoV2 and proposed antiviral drugs; iii) The combination of arginine‑ascorbate.

COVID-19 has led to an unprecedented healthcare crisis with millions of infected people across the globe often pushing infrastructures, healthcare workers and entire economies beyond their limits. The scarcity of testing kits, even in developed countries, has led to extensive research efforts towards alternative solutions with high sensitivity. Chest radiological imaging paired with artificial intelligence (AI) can offer significant advantages in diagnosis of novel coronavirus infected patients. To this end, transfer learning techniques are used for overcoming the limitations emanating from the lack of relevant big datasets, enabling specialized models to converge on limited data, as in the case of X-rays of COVID-19 patients. In this study, we present an interpretable AI framework assessed by expert radiologists on the basis on how well the attention maps focus on the diagnostically-relevant image regions. The proposed transfer learning methodology achieves an overall area under the curve of 1 for a binary classification problem across a 5-fold training/testing dataset., (Copyright: © Tsiknakis et al.)

The new era of artificial intelligence (AI) has introduced revolutionary data‑driven analysis paradigms that have led to significant advancements in information processing techniques in the context of clinical decision‑support 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.

This study aims to examine a time-extended dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocol and report a comparative study with three different pharmacokinetic (PK) models, for accurate determination of subtle blood-brain barrier (BBB) disruption in patients with multiple sclerosis (MS). This time-extended DCE-MRI perfusion protocol, called Snaps, was applied on 24 active demyelinating lesions of 12 MS patients. Statistical analysis was performed for both protocols through three different PK models. The Snaps protocol achieved triple the window time of perfusion observation by extending the magnetic resonance acquisition time by less than 2 min on average for all patients. In addition, the statistical analysis in terms of adj- R 2 goodness of fit demonstrated that the Snaps protocol outperformed the conventional DCE-MRI protocol by detecting 49% more pixels on average. The exclusive pixels identified from the Snaps protocol lie in the low k trans range, potentially reflecting areas with subtle BBB disruption. Finally, the extended Tofts model was found to have the highest fitting accuracy for both analyzed protocols. The previously proposed time-extended DCE protocol, called Snaps, provides additional temporal perfusion information at the expense of a minimal extension of the conventional DCE acquisition time., Competing Interests: Conflict of interest: The authors state no conflict of interest., (© 2020 Eleftherios Kontopodis et al., published by De Gruyter.)

Competing Interests: Conflict of Interest: None

Background: Young patients with Cushing Syndrome (CS) may develop cognitive and behavioral alterations during disease course., Methods: To investigate the effects of CS on the brain, we analyzed consecutive MRI scans of patients with (n = 29) versus without CS (n = 8). Multiple brain compartments were processed for total and gray/white matter (GM/WM) volumes and intensities, and cortical volume, thickness, and surface area. Dynamics (last/baseline scans ratio per parameter) were analyzed versus cortisol levels and CS status (persistent, resolved, and non-CS)., Results: Twenty-four-hour urinary free cortisol (24hUFC) measurements had inverse correlation with the intensity of subcortical GM structures and of the corpus callosum, and with the cerebral WM intensity. 24hUFC dynamics had negative correlation with volume dynamics of multiple cerebral and cerebellar structures. Patients with persistent CS had less of an increase in cortical thickness and WM intensity, and less of a decrease in WM volume compared with patients with resolution of CS. Patients with resolution of their CS had less of an increase in subcortical GM and cerebral WM volumes, but a greater increase in cortical thickness of frontal lobe versus controls., Conclusion: Changes in WM/GM consistency, intensity, and homogeneity in patients with CS may correlate with CS clinical consequences better than volume dynamics alone., (Published by Oxford University Press on behalf of the Endocrine Society 2019.)

Orbital and ocular anatomy is quite complex, consisting of several tissues, which can give rise to both benign and malignant tumors, while several primary neoplasms can metastasize to the orbital and ocular space. Early detection, accurate staging and re‑staging, efficient monitoring of treatment response, non‑invasive differentiation between benign and malignant lesions, and accurate planning of external radiation treatment, are of utmost importance for the optimal and individualized management of ophthalmic oncology patients. Addressing these challenges requires the employment of several diagnostic imaging techniques, such as high‑definition digital fundus photography, ultrasound imaging, optical coherence tomography, optical coherence tomography (OCT)‑angiography, computed tomography (CT) and magnetic resonance imaging (MRI). In recent years, technological advances have enabled the development of hybrid positron emission tomography (PET)/CT and PET/MRI systems, setting new standards in cancer diagnosis and treatment. The capability of simultaneously targeting several cancer‑related biochemical procedures using positron emitting‑radiopharmaceuticals, while morphologically characterizing lesions by CT or MRI, together with the intrinsic quantitative capabilities of PET‑imaging, provide incremental diagnostic information, enabling accurate, highly efficient and personalized treatment strategies. Aim of the current review is to discuss the current applications of hybrid PET/CT and PET/MRI imaging in the management of patients presenting with the most commonly encountered orbital and ocular tumors.

Summary: Adrenococortical carcinoma (ACC) is a rare cancer, occurring at the rate of one case in two million person years. Cushing syndrome or a mixed picture of excess androgen and glucocorticoid production are the most common presentations of ACC. Other uncommon presentations include abdominal pain and adrenal incidentalomas. In the present report, a 71-year-old male presented with abdominal pain and was eventually diagnosed with ACC. He was found to have pulmonary thromboembolism following an investigation for hypoxemia, with the tumor thrombus extending upto the right atrium. This interesting case represents the unique presentation of a rare tumor, which if detected late or left untreated is associated with poor outcomes, highlighting the need for a low index of suspicion for ACC when similar presentations are encountered in clinical practice., Learning Points: ACC is a rare but aggressive tumor. ACC commonly presents with rapid onset of hypercortisolism, combined hyperandrogenism and hypercortisolism, or uncommonly with compressive symptoms. Clinicians should have a low index of suspicion for ACC in patients presenting with rapid onset of symptoms related to hypercortisolism and/or hyperandrogenism. Venous thromboembolism and extension of the tumor thrombus to the right side of the heart is a very rare but serious complication of ACC that clinicans should be wary of. The increased risk of venous thromboembolism in ACC could be explained by direct tumor invasion, tumor thrombi or hypercoagulability secondary to hypercortisolism. Early diagnosis and prompt treatment can improve the long-term survival of patients with ACC.

Potentially suspicious breast neoplasms could be masked by high tissue density, thus increasing the probability of a false‑negative diagnosis. Furthermore, differentiating breast tissue type enables patient pre‑screening stratification and risk assessment. In this study, we propose and evaluate advanced machine learning methodologies aiming at an objective and reliable method for breast density scoring from routine mammographic images. The proposed image analysis pipeline incorporates texture [Gabor filters and local binary pattern (LBP)] and gradient‑based features [histogram of oriented gradients (HOG) as well as speeded‑up robust features (SURF)]. Additionally, transfer learning approaches with ImageNet trained weights were also used for comparison, as well as a convolutional neural network (CNN). The proposed CNN model was fully trained on two open mammography datasets and was found to be the optimal performing methodology (AUC up to 87.3%). Thus, the findings of this study indicate that automated density scoring in mammograms can aid clinical diagnosis by introducing artificial intelligence‑powered decision‑support systems and contribute to the 'democratization' of healthcare by overcoming limitations, such as the geographic location of patients or the lack of expert radiologists.

Intraductal papillary mucinous neoplasm (IPMN) is a precursor to pancreatic ductal adenocarcinoma. While over half of patients are diagnosed with pancreatic cancer at a distant stage, patients who are diagnosed early enjoy a much higher 5-year survival rate of 34% compared to 3% in the former; hence, early diagnosis is key. Unique challenges in the medical imaging domain such as extremely limited annotated data sets and typically large 3D volumetric data have made it difficult for deep learning to secure a strong foothold. In this work, we construct two novel "inflated" deep network architectures, InceptINN and DenseINN , for the task of diagnosing IPMN from multisequence (T1 and T2) MRI. These networks inflate their 2D layers to 3D and bootstrap weights from their 2D counterparts (Inceptionv3 and DenseNet121 respectively) trained on ImageNet to the new 3D kernels. We also extend the inflation process by further expanding the pre-trained kernels to handle any number of input modalities and different fusion strategies. This is one of the first studies to train an end-to-end deep network on multisequence MRI for IPMN diagnosis, and shows that our proposed novel inflated network architectures are able to handle the extremely limited training data (139 MRI scans), while providing an absolute improvement of 8.76% in accuracy for diagnosing IPMN over the current state-of-the-art. Code is publicly available at https://github.com/lalonderodney/INN-Inflated-Neural-Nets.

Fibrous dysplasia (FD) is a mosaic skeletal disorder resulting in fractures, deformity, and functional impairment. Clinical evaluation has been limited by a lack of surrogate endpoints capable of quantitating disease activity. The purpose of this study was to investigate the utility of 18 F-NaF PET/CT imaging in quantifying disease activity in patients with FD. Fifteen consecutively evaluated subjects underwent whole-body 18 F-NaF PET/CT scans, and FD burden was assessed by quantifying FD-related 18 F-NaF activity. 18 F-NaF PET/CT parameters obtained included (i) SUV max (standardized uptake value [SUV] of the FD lesion with the highest uptake); (ii) SUV mean (average SUV of all 18 F-NaF-positive FD lesions); (iii) total volume of all 18 F-NaF-positive FD lesions (TV); and (iv) total FD lesion activity determined as the product of TV multiplied by SUV mean (TA =  TV ×  SUV mean ) (TA). Skeletal outcomes, functional outcomes, and bone turnover markers were correlated with 18 F-NaF PET/CT parameters. TV and TA of extracranial FD lesions correlated strongly with skeletal outcomes including fractures and surgeries (p values ≤ 0.003). Subjects with impaired ambulation and scoliosis had significantly higher TV and TA values (P < 0.05), obtained from extracranial and spinal lesions, respectively. Craniofacial surgeries correlated with TV and TA of skull FD lesions (P < 0.001). Bone turnover markers, including alkaline phosphatase, N-telopeptides, and osteocalcin, were strongly correlated with TV and TA (P < 0.05) extracted from FD lesions in the entire skeleton. No associations were identified with SUV max or SUV mean . Bone pain and age did not correlate with 18 F-NaF PET/CT parameters. FD burden evaluated by 18 F-NaF-PET/CT facilitates accurate assessment of FD activity, and correlates quantitatively with clinically-relevant skeletal outcomes. © 2019 American Society for Bone and Mineral Research., (© 2019 American Society for Bone and Mineral Research.)

Imaging biomarkers (IBs) play a critical role in the clinical management of breast cancer (BRCA) patients throughout the cancer continuum for screening, diagnosis, and therapy assessment, especially in the neoadjuvant setting. However, certain model-based IBs suffer from significant variability due to the complex workflows involved in their computation, whereas model-free IBs have not been properly studied regarding clinical outcome. In this study, IBs from 35 BRCA patients who received neoadjuvant chemotherapy (NAC) were extracted from dynamic contrast-enhanced MR imaging (DCE-MRI) data with two different approaches, a model-free approach based on pattern recognition (PR), and a model-based one using pharmacokinetic compartmental modeling. Our analysis found that both model-free and model-based biomarkers can predict pathological complete response (pCR) after the first cycle of NAC. Overall, eight biomarkers predicted the treatment response after the first cycle of NAC, with statistical significance (p-value < 0.05), and three at the baseline. The best pCR predictors at first follow-up, achieving high AUC and sensitivity and specificity more than 50%, were the hypoxic component with threshold 2 (AUC 90.4%) from the PR method, and the median value of k ep (AUC 73.4%) from the model-based approach. Moreover, the 80 th percentile of v e achieved the highest pCR prediction at baseline with AUC 78.5%. The results suggest that the model-free DCE-MRI IBs could be a more robust alternative to complex, model-based ones such as k ep and favor the hypothesis that the PR image-derived hypoxic image component captures actual tumor hypoxia information able to predict BRCA NAC outcome.

Benign thyroid nodules are among the most common endocrine disorders. Recent advances in diagnostic imaging and pathology have significantly contributed to better risk stratification of thyroid nodules. However, current treatment options, beyond surgical approaches are limited. The following placebo-controlled study presents, to the best of our knowledge, the first results of a non-invasive therapy for benign thyroid nodules. The efficacy and safety of a supplement containing spirulina, curcumin and Boswellia in euthyroid patients with benign thyroid nodules, was assessed by a 3 month, double-blind, placebo-controlled study which was completed by 34 patients. Patients with benign (FNAB documented) single thyroid nodules between 2 and 5 cm were evaluated in a prospective placebo-controlled cross-over trial, across 12 weeks (3 visits with six-week intervals). At each visit, the target thyroid nodule was recorded in two dimensions. In addition, plasma levels of thyroid stimulating hormone, free thyroxine and copper were assessed. The mean initial nodule area at V1 was 4.38±3.14 cm2, at V2 3.87±2.79 cm2, and at V3 3.53±2.84 cm2; P<0.04. Administration of the active substances (n=34) was followed by a mean area decrease of 0.611 cm2±0.933 (SD), while placebo administration (n=29) was followed by a mean decrease of 0.178 cm2±0.515 (SD), (P=0.027). The presented findings suggest that the combination of spirulina-curcumin-Βoswellia is effective in reducing the size of benign thyroid nodules. However, additional studies are needed in order to elucidate the exact mechanisms through which the suggested supplement facilitates a decrease in the size of benign thyroid nodules.

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 × 10 7  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.

Although the idea of the personalization of patient care dates back to the time of Hippocrates, recent advances in diagnostic medical imaging and molecular medicine are gradually transforming healthcare services, by offering information and diagnostic tools enabling individualized patient management. Facilitating personalized / precision medicine requires taking into account multiple heterogenous parameters, such as sociodemographics, gene variability, environmental and lifestyle factors. Therefore, one of the most critical challenges in personalized medicine is the need to transform large, multi-modal data into decision support tools, capable of bridging the translational gap to the clinical setting. Towards these challenges, deep learning (DL) provides a novel approach, which enables obtaining or developing high-accuracy, multi-modal predictive models, that allow the implementation of the personalized medicine vision in the near future. DL is a highly effective strategy in addressing these challenges, with DL-based models leading to unprecedented results, matching or even improving state-of-the-art prediction/detection rates based on both intuitive and non-intuitive disease descriptors. These results hold promise for significant socio-economic benefits from the application of DL personalized medicine.

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.

Melorheostosis is a rare hyperostotic disease of the long bones classically characterized by a "dripping candle-wax" radiographic appearance. We recently described somatic activating mutations in MAP2K1 as a cause of melorheostosis. Here, we report distinguishing characteristics of patients with MAP2K1-positive melorheostosis. Fifteen unrelated patients with radiographic appearance of melorheostosis underwent paired biopsies of affected and unaffected bone for whole-exome sequencing, histology, and cell culture. Eight patients with mutations in MAP2K1 in affected bone were compared to the seven MAP2K1-negative patients to identify distinguishing characteristics. Patients with MAP2K1-positive melorheostosis had a distinct phenotype with classic "dripping candle-wax" appearance on radiographs (p = 0.01), characteristic vascular lesions on skin overlying affected bone (p = 0.01), and higher prevalence of extraosseous mineralization and joint involvement (p = 0.04 for both). Melorheostotic bone from both MAP2K1-positive and MAP2K1-negative patients showed two zones of distinct morphology-an outer segment of parallel layers of primary lamellar bone and a deeper zone of intensely remodeled highly porous osteonal-like bone. Affected bone from MAP2K1-positive patients showed excessive osteoid (p = 0.0012), increased number of osteoblasts (p = 0.012) and osteoclasts (p = 0.04), and increased vascularity on histology in comparison to paired unaffected bone which was not seen in affected bone in most MAP2K1-negative patients. The identification of a distinct phenotype of patients with MAP2K1-positive melorheostosis demonstrates clinical and genetic heterogeneity among patients with the disease. Further studies are needed to better understand the underlying pathophysiology and associated skin findings. © 2018 American Society for Bone and Mineral Research., (© 2018 American Society for Bone and Mineral Research.)

Melorheostosis (MEL) is a rare disease of high bone mass with patchy skeletal distribution affecting the long bones. We recently reported somatic mosaic mutations in MAP2K1 in 8 of 15 patients with the disease. The unique anatomic distribution of melorheostosis is of great interest. The disease remains limited to medial or lateral side of the extremity with proximo-distal progression. This pattern of distribution has historically been attributed to sclerotomes (area of bone which is innervated by a single spinal nerve level). In a further analysis of our study on MEL, 30 recruited patients underwent whole body CT scans to characterize the anatomic distribution of the disease. Two radiologists independently reviewed these scans and compared it to the proposed map of sclerotomes. We found that the disease distribution conformed to the distribution of a single sclerotome in only 5 patients (17%). In another 12 patients, the lesions spanned parts of contiguous sclerotomes but did not involve the entire extent of the sclerotomes. Our findings raise concerns about the sclerotomal hypothesis being the definitive explanation for the pattern of anatomic distribution in MEL. We believe that the disease distribution can be explained by clonal proliferation of a mutated skeletal progenitor cell along the limb axis. Studies in mice models on clonal proliferation in limb buds mimic the patterns seen in melorheostosis. We also support this hypothesis by the dorso-ventral confinement of melorheostotic lesion in a patient with low allele frequency of MAP2K1-positive osteoblasts and low skeletal burden of the disease. This suggests that the mutation occurred after the formation of dorso-ventral plane. Further studies on limb development are needed to better understand the etiology, pathophysiology and pattern of disease distribution in all patients with MEL., (Copyright © 2018. Published by Elsevier Inc.)

Colorectal cancer (CRC) is among the most common cancers. In fact, it is placed in the third place among the most diagnosed cancer in men, after lung and prostate cancer, and in the second one for the most diagnosed cancer in women, following breast cancer. Moreover, its high mortality rates classifies it among the leading causes of cancer‑related death worldwide. Thus, in order to help clinicians to optimize their practice, it is crucial to introduce more effective tools that will improve not only early diagnosis, but also prediction of the most likely progression of the disease and response to chemotherapy. In that way, they will be able to decrease both morbidity and mortality of their patients. In accordance with that, colon cancer research has described numerous biomarkers for diagnostic, prognostic and predictive purposes that either alone or as part of a panel would help improve patient's clinical management. This review aims to describe the most accepted biomarkers among those proposed for use in CRC divided based on the clinical specimen that is examined (tissue, faeces or blood) along with their restrictions. Lastly, new insight in CRC monitoring will be discussed presenting promising emerging biomarkers (telomerase activity, telomere length and micronuclei frequency).

Segmentation, denoising, and partial volume correction (PVC) are three major processes in the quantification of uptake regions in post-reconstruction PET images. These problems are conventionally addressed by independent steps. In this study, we hypothesize that these three processes are dependent; therefore, jointly solving them can provide optimal support for quantification of the PET images. To achieve this, we utilize interactions among these processes when designing solutions for each challenge. We also demonstrate that segmentation can help in denoising and PVC by locally constraining the smoothness and correction criteria. For denoising, we adapt generalized Anscombe transformation to Gaussianize the multiplicative noise followed by a new adaptive smoothing algorithm called regional mean denoising. For PVC, we propose a volume consistency-based iterative voxel-based correction algorithm in which denoised and delineated PET images guide the correction process during each iteration precisely. For PET image segmentation, we use affinity propagation (AP)-based iterative clustering method that helps the integration of PVC and denoising algorithms into the delineation process. Qualitative and quantitative results, obtained from phantoms, clinical, and pre-clinical data, show that the proposed framework provides an improved and joint solution for segmentation, denoising, and partial volume correction., (Copyright © 2018 Elsevier B.V. All rights reserved.)

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. 68 Gallium-DOTATATE positron emission tomography with computed tomography ( 68 Ga-DOTATATE PET/CT) is a sensitive imaging technique for detection of NETs. We investigated the prognostic accuracy of 68 Ga-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 68 Ga-DOTATATE PET/CT image analysis and total 68 Ga-DOTATATE-Avid tumor volume ( 68 Ga-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 68 Ga-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 68 Ga-DOTATATE TV and PFS (P = .001) and disease-specific survival (P = .002). A 68 Ga-DOTATATE TV of 7.0 mL or more was associated with higher odds of disease progression (hazard ratio, 3.0; P = .04). A 68 Ga-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 68 Ga-DOTATATE TV in a large cohort of patients with NETs, in terms of PFS and disease-specific mortality., (Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Interstitial lung diseases (ILD) involve several abnormal imaging patterns observed in computed tomography (CT) images. Accurate classification of these patterns plays a significant role in precise clinical decision making of the extent and nature of the diseases. Therefore, it is important for developing automated pulmonary computer-aided detection systems. Conventionally, this task relies on experts' manual identification of regions of interest (ROIs) as a prerequisite to diagnose potential diseases. This protocol is time consuming and inhibits fully automatic assessment. In this paper, we present a new method to classify ILD imaging patterns on CT images. The main difference is that the proposed algorithm uses the entire image as a holistic input. By circumventing the prerequisite of manual input ROIs, our problem set-up is significantly more difficult than previous work but can better address the clinical workflow. Qualitative and quantitative results using a publicly available ILD database demonstrate state-of-the-art classification accuracy under the patch-based classification and shows the potential of predicting the ILD type using holistic image., Competing Interests: Disclosure statement No potential conflict of interest was reported by the authors.

Competing Interests: Competing interests: None declared.

Unstable isotopes and their capacity to emit ionizing radiation have been employed in clinical practice not only for diagnostic, but also for therapeutic purposes, with significant contribution in several fields of medicine and primarily in the management of oncologic patients. Their efficacy is associated with their ability to provide the targeted delivery of ionizing radiation for a determined duration. These compounds can be used for curative or palliative treatment, as well as for a diagnostic-therapeutic (theranostic) approach. This review summarises the most recent trends in radionuclide treatment for several malignancies, including prostate cancer, neuroendocrine tumours, and hematological and thyroid malignancies, in which radionuclide-based therapies have been employed with high effectiveness.

Introduction: In vivo imaging biomarkers of various HIV neuropathologies, including dopaminergic dysfunction, are still lacking. Towards developing dopaminergic biomarkers of brain involvement in HIV, we assessed the pre and postsynaptic components of the dopaminergic system in the HIV-1 transgenic rat (Tg), a well-characterized model of treated HIV+ patients, using small-animal PET imaging., Methods: Fifteen to 18 month-old Tg and wild type (WT) rats were imaged with both [18F]-FP-CMT, a dopamine transporter (DAT) ligand (n=16), and [18F]-Fallypride, a D2/D3 dopamine receptor (D2/D3DR) ligand (n=16). Five to 8 month-old Tg and WT rats (n=18) were also imaged with [18F]-FP-CMT. A subset of animals was imaged longitudinally at 7 and 17 months of age. Multiplex immunohistochemistry staining for DAT, tyrosine hydroxylase, D2DR, D3DR , GFAP, Iba1 and NeuN was performed on a subgroup of the scanned animals., Results: [18F]-FP-CMT and [18F]-Fallypride binding potential (BP ND ) values were significantly lower in 15-18 month-old Tg compared to age-matched WT rats (p<0.0001 and 0.001, respectively). [18F]-FP-CMT BP ND values in 5-8 month-old rats, however, were not significantly different. Longitudinal age-related decrease in [18F]-FP-CMT BP ND was exacerbated in the Tg rat. Immunohistochemistry showed decreased staining of dopaminergic markers in Tg rats. Rats with higher serum gp120 had lower mean BP ND values for both ligands., Conclusions: We found presynaptic and postsynaptic dopaminergic dysfunction/loss in older Tg compared to WT rats. We believe this to be related to neurotoxicity of viral proteins present in the Tg rats' serum and brain., Advances in Knowledge: Our findings confirm prior reports of neurobehavioral abnormalities suggestive of dopaminergic dysfunction in this model. They also suggest similarities between the Tg rat and HIV+ patients as far as dopaminergic dysfunction., Implications for Patient Care: The Tg rat, along with the above-described quantitative PET imaging biomarkers, can have a role in the evaluation of HIV neuroprotective therapies prior to human translation., (Published by Elsevier Inc.)

Pulmonary embolism (PE) during pregnancy remains the leading preventable cause of maternal morbidity and mortality in the developed countries. Diagnosis of PE in pregnant patients is a challenging clinical problem, since pregnancy-related physiologic changes can mimic signs and symptoms of PE. Patient mismanagement may result into unjustified anticoagulant treatment or unnecessary imaging tests involving contrast-related or/and radiation-related risks for both the expectant mother and embryo/fetus. On the other hand, missing or delaying diagnosis of PE could lead to life-threatening conditions for both the mother and the embryo/fetus. Thus, a timely and accurate diagnostic approach is required for the optimal management of pregnant patients with suspected PE. Aim of the current review is to discuss a pregnancy-specific clinical pathway for the early diagnosis of PE with non-ionizing radiation- and ionizing radiation-based imaging modalities taking into account previously reported data on diagnostic value of available imaging tests, and radiation related concerns., (Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Context: Somatic mutations in the ubiquitin-specific protease 8 (USP8) gene have been recently identified as the most common genetic alteration in patients with Cushing disease (CD). However, the frequency of these mutations in the pediatric population has not been extensively assessed., Objective: We investigated the status of the USP8 gene at the somatic level in a cohort of pediatric patients with corticotroph adenomas., Design and Methods: The USP8 gene was fully sequenced in both germline and tumor DNA samples from 42 pediatric patients with CD. Clinical, biochemical, and imaging data were compared between patients with and without somatic USP8 mutations., Results: Five different USP8 mutations (three missense, one frameshift, and one in-frame deletion) were identified in 13 patients (31%), all of them located in exon 14 at the previously described mutational hotspot, affecting the 14-3-3 binding motif of the protein. Patients with somatic mutations were older at disease presentation [mean 5.1 ± 2.1 standard deviation (SD) vs 13.1 ± 3.6 years, P = 0.03]. Levels of urinary free cortisol, midnight serum cortisol, and adrenocorticotropic hormone, as well as tumor size and frequency of invasion of the cavernous sinus, were not significantly different between the two groups. However, patients harboring somatic USP8 mutations had a higher likelihood of recurrence compared with patients without mutations (46.2% vs 10.3%, P = 0.009)., Conclusion: Somatic USP8 gene mutations are a common cause of pediatric CD. Patients harboring a somatic mutation had a higher likelihood of tumor recurrence, highlighting the potential importance of this molecular defect for the disease prognosis and the development of targeted therapeutic options., (Copyright © 2017 Endocrine Society)

Melorheostosis is a rare, nonhereditary, benign, sclerotic bone dysplasia with no sex predilection, typically occurring in late childhood or early adulthood, which can lead to substantial functional morbidity, depending on the sites of involvement. We report on a patient with extensive melorheostosis in the axial and appendicular skeleton, as well as in the soft tissues, who was evaluated with whole-body F-NaF PET/CT scan. All melorheostotic lesions of the skeleton and of the ossified soft-tissue masses demonstrated intensely increased F-NaF activity, suggesting the application of this modality in assessing and monitoring the disease activity.

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 mm 3 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., Competing Interests: Conflicts of interest: The authors declare that they have no conflict of interest., (© Georg Thieme Verlag KG Stuttgart · New York.)

We present a new image quality assessment method for determining whether reducing radiation dose impairs the image quality of computed tomography (CT) in qualitative and quantitative clinical analyses tasks. In this Institutional Review Board-exempt study, we conducted a review of 50 patients (male, 22; female, 28) who underwent reduced-dose CT scanning on the first follow-up after standard-dose multiphase CT scanning. Scans were for surveillance of von Hippel-Lindau disease (N = 26) and renal cell carcinoma (N = 10). We investigated density, morphometric, and structural differences between scans both at tissue (fat, bone) and organ levels (liver, heart, spleen, lung). To quantify structural variations caused by image quality differences, we propose using the following metrics: dice similarity coefficient, structural similarity index, Hausdorff distance, gradient magnitude similarity deviation, and weighted spectral distance. Pearson correlation coefficient and Welch 2-sample t test were used for quantitative comparisons of organ morphometry and to compare density distribution of tissue, respectively. For qualitative evaluation, 2-sided Kendall Tau test was used to assess agreement among readers. Both qualitative and quantitative evaluations were designed to examine significance of image differences for clinical tasks. Qualitative judgment served as an overall assessment, whereas detailed quantifications on structural consistency, intensity homogeneity, and texture similarity revealed more accurate and global difference estimations. Qualitative and quantitative results indicated no significant image quality degradation. Our study concludes that low(er)-dose CT scans can be routinely used because of no significant loss in quantitative image information compared with standard-dose CT scans.

Objective: To determine the association between neuroendocrine tumor (NET) biomarker levels and the extent of disease as assessed by 68 Ga DOTATATE PET/CT imaging., Design: A retrospective analysis of a prospective database of patients with NETs., Methods: Fasting plasma chromogranin A (CgA), neuron-specific enolase (NSE), gastrin, glucagon, vasoactive intestinal peptide (VIP) and pancreatic polypeptide (PP), and 24-h urinary 5-hydroxyindoleacetic acid (5-HIAA) levels were measured. Correlation between biomarkers and total 68 Ga-DOTATATE-avid tumor volume (TV) was analyzed., Results: The analysis included 232 patients. In patients with pancreatic NETs ( n  = 112), 68 Ga-DOTATATE TV correlated with CgA ( r  = 0.6, P  = 0.001, Spearman). In patients with multiple endocrine neoplasia type 1 ( n  = 39), 68 Ga-DOTATATE TV correlated with glucagon ( r  = 0.5, P  = 0.01) and PP levels ( r  = 0.5, P  = 0.049). In patients with von Hippel-Lindau ( n  = 24), plasma VIP ( r  = 0.5, P  = 0.02) and PP levels ( r  = 0.7, P  < 0.001) correlated with 68 Ga-DOTATATE TV. In patients with small intestine NET (SINET, n  = 74), 68 Ga-DOTATATE TV correlated with CgA ( r  = 0.5, P  = 0.02) and 5-HIAA levels ( r  = 0.7, P  < 0.001), with 5-HIAA ≥8.1 mg/24 h associated with metastatic disease with high positive (81.8%) and negative (85.7%) predictive values ( P  = 0.001). 68 Ga-DOTATATE TV in patients with NET of unknown primary ( n  = 16) and those with NET of other primary location ( n  = 30) correlated with 5-HIAA levels ( r  = 0.8, P  = 0.002 and r  = 0.7, P  = 0.02 respectively)., Conclusions: Our data supports the use of specific NET biomarkers based on the site of the primary NET and the presence of hereditary syndrome-associated NET. High urinary 5-HIAA levels indicate the presence of metastatic disease in patients with SINET., (© 2017 European Society of Endocrinology.)

Objective: Insulin-like growth factor (IGF)-axis is involved in human oncogenesis and metastasis development for various solid tumors including breast cancer. Aim of this study was to assess the association between IGF-1, IGF-binding protein-3 (IGFBP-3) serum levels and the presence of circulating tumor cells (CTCs) in the peripheral blood of women diagnosed with early breast cancer (EBC), before and after adjuvant chemotherapy., Design: 171 patients with early-stage breast adenocarcinomas were retrospectively evaluated. Immunoradiometric (IRMA) assays were employed for the in-vitro determination of IGF-1 and IGFBP-3 serum levels in blood samples collected after surgical treatment and before initiation of adjuvant chemotherapy. CTCs' presence was assessed through detection of cytokeratin-19 (CK-19) mRNA transcripts using quantitative real time reverse transcription polymerase chain reaction (RT-PCR). IGF-1, IGFBP-3 serum levels were correlated with CTCs' presence before and after adjuvant chemotherapy as well as with tumor characteristics including tumor size, axillary lymph node status, oestrogen (ER)/progestorene (PR) and human epidermural growth factor receptor 2 (HER2) receptor status. Log-rank test was applied to investigate possible association between IGF-1, IGFBP-3 serum levels and disease-free interval (DFI) and overall survival (OS)., Results: Before initiation of adjuvant therapy IGF-1, IGFBP-3 serum levels were moderately associated (Spearman's rho=0.361, p<0.001) with each other, while presenting significant differences across age groups (all p values<0.05). IGF-1 serum levels did not correlate with the presence of CTCs before initiation (p=0.558) or after completion (p=0.474) of adjuvant chemotherapy. Similarly, IGFBP-3 serum levels did not show significant association with detectable CTCs either before (p=0.487) or after (p=0.134) completion of adjuvant chemotherapy. There was no statistically significant association between the clinical outcome of patients in terms of DFI, OS and IGF-1(DFI: p=0.499; OS: p=0.220) or IGFBP-3 (DFI: p=0.900; OS: p=0.406) serum levels., Conclusions: IGF-1 and IGFBP-3 serum levels before initiation of adjuvant chemotherapy are not indicative of CTCs' presence in the blood and do not correlate with clinical outcome of women with early-stage breast cancer., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Fibrous dysplasia of the bone is a developmental benign skeletal disorder characterized by replacement of normal bone and normal bone marrow with abnormal fibro-osseous tissue. We report on a case of a biopsy-proven fibrous dysplasia lesion in the left temporal bone, with intensely increased activity (SUVmax, 56.7) on Ga-DOTATATE PET/CT. The presented data indicate cell surface overexpression of somatostatin receptors by fibrous dysplastic cells and highlight the need of cautious management of Ga-DOTATATE-avid bone lesions, which could mimic malignancy especially in patients with history of neuroendocrine tumors.

Prolonged exposure to cortisol is one of the major causes of avascular bone necrosis (AVN). We report on a case of a woman with Cushing syndrome attributed to ectopic adrenocorticotropic hormone-secreting tumor who was evaluated with whole-body PET/CT study using Ga-DOTATATE. The scan showed increased activity by both femoral heads, corresponding to the margins of bilateral AVN seen on MRI. The presented data suggests AVN-induced reactive inflammatory alterations adjacent to the necrotic segment of the bone, which can be effectively targeted using radiolabeled somatostatin (SST) analogs.

In this paper, we investigate the automatic detection of white and brown adipose tissues using Positron Emission Tomography/Computed Tomography (PET/CT) scans, and develop methods for the quantification of these tissues at the whole-body and body-region levels. We propose a patient-specific automatic adiposity analysis system with two modules. In the first module, we detect white adipose tissue (WAT) and its two sub-types from CT scans: Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT). This process relies conventionally on manual or semi-automated segmentation, leading to inefficient solutions. Our novel framework addresses this challenge by proposing an unsupervised learning method to separate VAT from SAT in the abdominal region for the clinical quantification of central obesity. This step is followed by a context driven label fusion algorithm through sparse 3D Conditional Random Fields (CRF) for volumetric adiposity analysis. In the second module, we automatically detect, segment, and quantify brown adipose tissue (BAT) using PET scans because unlike WAT, BAT is metabolically active. After identifying BAT regions using PET, we perform a co-segmentation procedure utilizing asymmetric complementary information from PET and CT. Finally, we present a new probabilistic distance metric for differentiating BAT from non-BAT regions. Both modules are integrated via an automatic body-region detection unit based on one-shot learning. Experimental evaluations conducted on 151 PET/CT scans achieve state-of-the-art performances in both central obesity as well as brown adiposity quantification.