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Colorectal cancer (CRC) is a leading tumor worldwide. In CRC, the angiogenic pathway plays a crucial role in cancer development and the process of metastasis. Thus, anti-angiogenic drugs represent a milestone for metastatic CRC (mCRC) treatment and lead to significant improvement of clinical outcomes. Nevertheless, not all patients respond to treatment and some develop resistance. Therefore, the identification of predictive factors able to predict response to angiogenesis pathway blockade is required in order to identify the best candidates to receive these agents. Unfortunately, no predictive biomarkers have been prospectively validated to date. Over the years, research has focused on biologic factors such as genetic polymorphisms, circulating biomarkers, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and microRNA. Moreover, research efforts have evaluated the potential correlation of molecular biomarkers with imaging techniques used for tumor assessment as well as the application of imaging tools in clinical practice. In addition to functional imaging, radiomics, a relatively newer technique, shows real promise in the setting of correlating molecular medicine to radiological phenotypes.

Background & Aims: Assessment of computed tomography (CT)/magnetic resonance imaging Liver Imaging Reporting and Data System (LI-RADS) v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. We assessed the performance and added-value of a machine learning (ML)-based algorithm in assessing CT LI-RADS major features and categorisation of liver observations compared with qualitative assessment performed by a panel of radiologists., Methods: High-risk patients as per LI-RADS v2018 with pathologically proven liver lesions who underwent multiphase contrast-enhanced CT at diagnosis between January 2015 and March 2019 in seven centres in five countries were retrospectively included and randomly divided into a training set (n = 84 lesions) and a test set (n = 345 lesions). An ML algorithm was trained to classify non-rim arterial phase hyperenhancement, washout, and enhancing capsule as present, absent, or of uncertain presence. LI-RADS major features and categories were compared with qualitative assessment of two independent readers. The performance of a sequential use of the ML algorithm and independent readers were also evaluated in a triage and an add-on scenario in LR-3/4 lesions. The combined evaluation of three other senior readers was used as reference standard., Results: A total of 318 patients bearing 429 lesions were included. Sensitivity and specificity for LR-5 in the test set were 0.67 (95% CI, 0.62-0.72) and 0.91 (95% CI, 0.87-0.96) respectively, with 242 (70.1%) lesions accurately categorised. Using the ML algorithm in a triage scenario improved the overall performance for LR-5. (0.86 and 0.93 sensitivity, 0.82 and 0.76 specificity, 78% and 82.3% accuracy for the two independent readers)., Conclusions: Quantitative assessment of CT LI-RADS v2018 major features is feasible and diagnoses LR-5 observations with high performance especially in combination with the radiologist's visual analysis in patients at high-risk for HCC., Impact and Implications: Assessment of CT/MRI LI-RADS v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. Rather than replacing radiologists, our results highlight the potential benefit from the radiologist-artificial intelligence interaction in improving focal liver lesions characterisation by using the developed algorithm as a triage tool to the radiologist's visual analysis. Such an AI-enriched diagnostic pathway may help standardise and improve the quality of analysis of liver lesions in patients at high risk for HCC, especially in non-expert centres in liver imaging. It may also impact the clinical decision-making and guide the clinician in identifying the lesions to be biopsied, for instance in patients with multiple liver focal lesions., Competing Interests: Five authors (VM, RQ, LD, JHL and NC) are GE Healthcare France employees. The remaining authors, who are not employees of or consultants for GE Healthcare, had control of inclusion of all data and information that might present a conflict of interest for authors who are employees for GE Healthcare. Please refer to the accompanying ICMJE disclosure forms for further details., (© 2023 The Author(s).)

Living in an enriched environment (EE) produces a notable impact on several rodent behaviors, including those motivated by drugs of abuse. This picture is somewhat less clear when referring to alcohol-motivated behaviors. With the intent of contributing to this research field with data from one of the few rat lines selectively bred for excessive alcohol consumption, the present study investigated the effect of EE on operant oral alcohol self-administration in Sardinian alcohol-preferring (sP) rats. Starting from Postnatal Day (PND) 21, male sP rats were kept under 3 different housing conditions: impoverished environment (IE; single housing in shoebox-like cages with no environmental enrichment); standard environment (SE; small colony cages with 3 rats and no environmental enrichment); EE (large colony cages with 6 rats and multiple elements of environmental enrichment, including 2 floors, ladders, maze, running wheels, and shelter). From PND 60, rats were exposed to different phases of shaping and training of alcohol self-administration. IE, SE, and EE rats were then compared under (i) fixed ratio (FR) 4 (FR4) schedule of alcohol reinforcement for 20 daily sessions and (ii) progressive ratio (PR) schedule of alcohol reinforcement in a final single session. Acquisition of the lever-responding task (shaping) was slower in EE than IE and SE rats, as the likely consequence of a "devaluation" of the novel stimuli provided by the operant chamber in comparison to those to which EE rats were continuously exposed in their homecage or an alteration, induced by EE, of the rat "emotionality" state when facing the novel environment represented by the operant chamber. Training of alcohol self-administration was slower in EE than IE rats, with SE rats displaying intermediate values. A similar ranking order (IE>SE>EE) was also observed in number of lever-responses for alcohol, amount of self-administered alcohol, and breakpoint for alcohol under FR4 and PR schedules of reinforcement. These data suggest that living in a complex environment reduced the reinforcing and motivational properties of alcohol in sP rats. These results are interpreted in terms of the reinforcing and motivational properties of the main components of EE (i.e., social interactions, physical activities, exploration, novelty) substituting, at least partially, for those of alcohol., (Copyright © 2022 Elsevier Inc. All rights reserved.)

We map single energy CT (SECT) scans to synthetic dual-energy CT (synth-DECT) material density iodine (MDI) scans using deep learning (DL) and demonstrate their value for liver segmentation. A 2D pix2pix (P2P) network was trained on 100 abdominal DECT scans to infer synth-DECT MDI scans from SECT scans. The source and target domain were paired with DECT monochromatic 70 keV and MDI scans. The trained P2P algorithm then transformed 140 public SECT scans to synth-DECT scans. We split 131 scans into 60% train, 20% tune, and 20% held-out test to train four existing liver segmentation frameworks. The remaining nine low-dose SECT scans tested system generalization. Segmentation accuracy was measured with the dice coefficient (DSC). The DSC per slice was computed to identify sources of error. With synth-DECT (and SECT) scans, an average DSC score of 0.93±0.06 (0.89±0.01) and 0.89±0.01 (0.81±0.02) was achieved on the held-out and generalization test sets. Synth-DECT-trained systems required less data to perform as well as SECT-trained systems. Low DSC scores were primarily observed around the scan margin or due to non-liver tissue or distortions within ground-truth annotations. In general, training with synth-DECT scans resulted in improved segmentation performance with less data.

Texture analysis has arisen as a tool to explore the amount of data contained in images that cannot be explored by humans visually. Radiomics is a method that extracts a large number of features from radiographic medical images using data-characterisation algorithms. These features, termed radiomic features, have the potential to uncover disease characteristics. The goal of both radiomics and texture analysis is to go beyond size or human-eye based semantic descriptors, to enable the non-invasive extraction of quantitative radiological data to correlate them with clinical outcomes or pathological characteristics. In the latest years there has been a flourishing sub-field of radiology where texture analysis and radiomics have been used in many settings. It is difficult for the clinical radiologist to cope with such amount of data in all the different radiological sub-fields and to identify the most significant papers. The aim of this review is to provide a tool to better understand the basic principles underlining texture analysis and radiological data mining and a summary of the most significant papers of the latest years., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Purpose: To explore the association between carotid artery length and tortuosity, and the occurrence of stroke., Material and Methods: In this retrospective study, IRB approved, 411 consecutive patients (males: 245; median age: 56 ± 12 years, age range: 21-93 years) with anterior circulation ischemic stroke were included. Only patients that underwent CTA within 7 days were considered and stroke caused by cardiac embolism and thoracic aorta embolism were excluded. For each patient, both carotid arteries were considered, and the ICA, CCA-ICA length and tortuosity were calculated. Inter-observer analysis was quantified with the Bland-Altman test. Mann-Whitney test and logistic regression analysis were also calculated to test the association between length and tortuosity with the occurrence of stroke., Results: In the final analysis, 166 patients (males: 72; median age: 54 ± 12 years, age range: 24-89 years) with anterior circulation ischemic stroke that were admitted to our hospital between February 2008 and December 2013 were included. The results showed a good concordance for the length of the vessels with a mean variation of 0.7% and 0.5% for CCA-ICA and ICA length respectively an for the tortuosity with a mean variation of 0.2% and -0.4% for CCA-ICA and ICA respectively. The analysis shows a statistically significant association between the tortuosity index of the ICA and CCA-ICA sides with stroke ( P value = 0.0001 in both cases) and these findings were confirmed also with the logistic regression analysis., Conclusion: Results of this study suggest that tortuosity index is associated with the presence of stroke whereas the length of the carotid arteries does not play a significant role.

Artificial intelligence (AI) has been successful at solving numerous problems in machine perception. In radiology, AI systems are rapidly evolving and show progress in guiding treatment decisions, diagnosing, localizing disease on medical images, and improving radiologists' efficiency. A critical component to deploying AI in radiology is to gain confidence in a developed system's efficacy and safety. The current gold standard approach is to conduct an analytical validation of performance on a generalization dataset from one or more institutions, followed by a clinical validation study of the system's efficacy during deployment. Clinical validation studies are time-consuming, and best practices dictate limited re-use of analytical validation data, so it is ideal to know ahead of time if a system is likely to fail analytical or clinical validation. In this paper, we describe a series of sanity tests to identify when a system performs well on development data for the wrong reasons. We illustrate the sanity tests' value by designing a deep learning system to classify pancreatic cancer seen in computed tomography scans., Competing Interests: CK was employed at Paige, a commercial company, during the preparation of this manuscript. This company played no role in the sponsorship, design, data collection and analysis, decision to publish, or preparation of the manuscript. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Mahmood, Shrestha, Bates, Mannelli, Corrias, Erdi and Kanan.)

Introduction : The recognition and therapy of patients with stroke is becoming progressively intricate as additional treatment choices become accessible and new associations between disease characteristics and treatment response are incessantly uncovered. Therefore, clinicians must regularly learn new skill, stay up to date with the literature and integrate advances into daily practice. The application of artificial intelligence (AI) to assist clinical decision making could diminish inter-rater variation in routine clinical practice and accelerate the mining of vital data that could expand recognition of patients with stroke, forecast of treatment responses and patient outcomes. Areas covered : In this review, the authors provide an up-to-date review of AI in stroke, analyzing the latest papers on this subject. These have been divided in two main groups: stroke diagnosis and outcome prediction. Expert opinion : The highest value of AI is its capability to merge, select and condense a large amount of clinical and imaging features of a single patient and to associate these with fitted models that have gone through robust assessment and optimization with large cohorts of data to support clinical decision making.

Purpose : The lack of standardization in quantitative radiomic measures of tumors seen on computed tomography (CT) scans is generally recognized as an unresolved issue. To develop reliable clinical applications, radiomics must be robust across different CT scan modes, protocols, software, and systems. We demonstrate how custom-designed phantoms, imprinted with human-derived patterns, can provide a straightforward approach to validating longitudinally stable radiomic signature values in a clinical setting. Approach : Described herein is a prototype process to design an anatomically informed 3D-printed radiomic phantom. We used a multimaterial, ultra-high-resolution 3D printer with voxel printing capabilities. Multiple tissue regions of interest (ROIs), from four pancreas tumors, one lung tumor, and a liver background, were extracted from digital imaging and communication in medicine (DICOM) CT exam files and were merged together to develop a multipurpose, circular radiomic phantom (18 cm diameter and 4 cm width). The phantom was scanned 30 times using standard clinical CT protocols to test repeatability. Features that have been found to be prognostic for various diseases were then investigated for their repeatability and reproducibility across different CT scan modes. Results : The structural similarity index between the segment used from the patients' DICOM image and the phantom CT scan was 0.71. The coefficient variation for all assessed radiomic features was < 1.0 % across 30 repeat scans of the phantom. The percent deviation (pDV) from the baseline value, which was the mean feature value determined from repeat scans, increased with the application of the lung convolution kernel, changes to the voxel size, and increases in the image noise. Gray level co-occurrence features, contrast, dissimilarity, and entropy were particularly affected by different scan modes, presenting with pDV > ± 15 % . Conclusions : Previously discovered prognostic and popular radiomic features are variable in practice and need to be interpreted with caution or excluded from clinical implementation. Voxel-based 3D printing can reproduce tissue morphology seen on CT exams. We believe that this is a flexible, yet practical, way to design custom phantoms to validate and compare radiomic metrics longitudinally, over time, and across systems., (© 2021 The Authors.)

Introduction: Oncologic patients who develop chemotherapy-associated liver injury (CALI) secondary to chemotherapy treatment tend to have worse outcomes. Biopsy remains the gold standard for the diagnosis of hepatic steatosis. The purpose of this article is to compare 2 alternatives: Proton-Density-Fat-Fraction (PDFF) MRI and MultiMaterial-Decomposition (MMD) DECT., Materials and Methods: 49 consecutive oncologic patients treated with Chemotherapy underwent abdominal DECT and abdominal MRI within 2 weeks of each other. Two radiologists tracked Regions of Interest independently both in the PDFF fat maps and in the MMD DECT fat maps. Non-parametric exact Wilcoxon signed rank test and Cohen's K were used to compare the 2 sequences and to evaluate the agreement., Results: There was no statistically significant difference in the fat fraction measured as a continuous value between PDFF and DECT between 2 readers. Within the same imaging method (PDFF) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.88 (p-value < 0.05). Similarly, for single-source DECT(ssDECT) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.97 (p-value < 0.05)., Conclusions: The results of this study demonstrate that the hepatic fat fraction of ssDECT with MMD are not significantly different from PDFF. This could be an advantage in an oncological population that undergoes serial CT scans for follow up of chemotherapy response., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2021.)

Four-dimensional (4D) flow sequences are an innovative type of MR sequences based upon phase contrast (PC) sequences which are a type of application of Angio-MRI together with the Time of Flight (TOF) sequences and Contrast-Enhanced Magnetic Resonance Acquisition (CE-MRA). They share the basic principles of PC, but unlike PC sequences, 4D flow has velocity encoding along all three flow directions and three-dimensional (3D) anatomic coverage. They guarantee the analysis of flow with multiplanarity on a post-processing level, which is a unique feature among MR sequences. Furthermore, this technique provides a completely new level to the in vivo flow analysis as it allows measurements in never studied districts such as intracranial applications or some parts of the heart never studied with echo-color-doppler, which is its sonographic equivalent. Furthermore, this technique provides a completely new level to the in vivo flow analysis as it allows accurate measurement of the flows in different districts (e.g., intracranial, cardiac) that are usually studied with echo-color-doppler, which is its sonographic equivalent. Of note, the technique has proved to be affected by less inter and intra-observer variability in several application. 4D-flow basic principles, advantages, limitations, common pitfalls and artefacts are described. This review will outline the basis of the formation of PC image, the construction of a 4D-flow and the huge impact the technique is having on the cardiovascular non-invasive examination. It will be then studied how this technique has had a huge impact on cardiovascular examinations especially on a central heart level., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/cdt.2020.02.08). The series “Advanced Imaging in The Diagnosis of Cardiovascular Diseases” was commissioned by the editorial office without any funding or sponsorship. LS served as the unpaid Guest Editor of the series and serves as an unpaid editorial board member of Cardiovascular Diagnosis and Therapy from July 2019 to June 2021. FC serves as an unpaid editorial board member of Cardiovascular Diagnosis and Therapy from July 2019 to June 2021. The authors have no other conflicts of interest to declare., (2020 Cardiovascular Diagnosis and Therapy. All rights reserved.)

The goal of assessing tumour response on imaging is to identify patients who are likely to benefit - or not - from anticancer treatment, especially in relation to survival. The World Health Organization was the first to develop assessment criteria. This early score, which assessed tumour burden by standardising lesion size measurements, laid the groundwork for many of the criteria that followed. This was then improved by the Response Evaluation Criteria in Solid Tumours (RECIST) which was quickly adopted by the oncology community. At the same time, many interventional oncology treatments were developed to target specific features of liver tumours that result in significant changes in tumours but have little effect on tumour size. New criteria focusing on the viable part of tumours were therefore designed to provide more appropriate feedback to guide patient management. Targeted therapy has resulted in a breakthrough that challenges conventional response criteria due to the non-linear relationship between response and tumour size, requiring the development of methods that emphasize the appearance of tumours. More recently, research into functional and quantitative imaging has created new opportunities in liver imaging. These results have suggested that certain parameters could serve as early predictors of response or could predict later tumour response at baseline. These approaches have now been extended by machine learning and deep learning. This clinical review focuses on the progress made in the evaluation of liver tumours on imaging, discussing the rationale for this approach, addressing challenges and controversies in the field, and suggesting possible future developments., Competing Interests: The authors declare that they do not have anything to disclose regarding funding or conflict of interest with respect to this manuscript. Please refer to the accompanying ICMJE disclosure forms for further details., (© 2020 The Author(s).)

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications., (© 2020 The Authors. Published by the British Institute of Radiology.)

Purpose: The aim of the study is to explore the patient's and scan's parameters that affect the iodine concentration in the abdomen using dual energy computed tomography (DECT) in an oncologic population., Method: This is a retrospective study with consecutive patients with different cancers who underwent a single-source DECT (ssDECT) examinations at our institution between years 2015 and 2017. On axial IODINE images, the radiologist manually drew a circular ROI along the inner contour of the aorta. Mean iodine concentration and ROI areas were recorded. Body mass index for every patient was recorded. Descriptive statistics were summarized for iodine concentration and patient/scan characteristics. Linear regression was used to examine associations between iodine concentration in aorta and studied characteristics. Statistical significance was set at a p value < 0.05., Results: The univariate analysis, showed a statistically significant association between iodine concentration within the aorta and the area of ROI (Estimated Coefficient β: -0.013), the rate of injection (Estimated Coefficient β: 2.09), the acquisition time (Estimated Coefficient β: -0.195). In multivariable analysis iodine concentration in the aorta increased with higher rate of injection (4 ml/sec), smaller ROI area and lower BMI., Conclusion: Our results showed how iodine concentration is highly dependent on some intrinsic and extrinsic parameters of the examination. These parameters should be taken into account since lower concentration of iodine decrease contrast-to-noise ratio, and in longitudinal follow up studies, they would affect iodine quantitive assessments in cancer patients with frequent chemotherapy-induced variations in BMI and cardiac function., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Purpose: To develop and optimize a rapid magnetic resonance imaging (MRI) screening protocol for pancreatic cancer to be performed in conjunction with breast MRI screening in breast cancer susceptibility gene (BRCA)-positive individuals., Methods: An IRB-approved prospective study was conducted. The rapid screening pancreatic MR protocol was designed to be less than 10 min to be performed after a standard breast MRI protocol. Protocol consisted of coronal NT T2 SSFSE, axial NT T2 SSFSE and axial NT rFOV FOCUS DWI, and axial T1. Images were acquired with the patient in the same prone position of breast MRI using the built-in body coil. Image quality was qualitatively assessed by two radiologists with 12 and 13 years of MRI experience, respectively. The imaging protocol was modified until an endpoint of five consecutive patients with high-quality diagnostic images were achieved. Signal-to-noise ratio and contrast-to-noise ratio were assessed., Results: The rapid pancreas MR protocol was successfully completed in all patients. Diagnostic image quality was achieved for all patients. Excellent image quality was achieved for low b values; however, image quality at higher b values was more variable. In one patient, a pancreatic neuroendocrine tumor was found and the patient was treated surgically. In four patients, small pancreatic cystic lesions were detected. In one subject, a hepatic mass was identified and confirmed as adenoma by liver MRI., Conclusion: Rapid MR protocol for pancreatic cancer screening is feasible and has the potential to play a role in screening BRCA patients undergoing breast MRI., Key Point: • Develop and optimize a rapid magnetic resonance imaging (MRI) screening protocol for pancreatic cancer to be performed in conjunction with breast MRI screening in BRCA mutation positive individuals.

Purpose: To investigate the value of second-opinion interpretation of cross-sectional images by subspecialized radiologists to diagnose recurrent pancreatic cancer after surgery., Methods: The IRB approved and issued a waiver of informed consent for this retrospective study. Initial and second-opinion interpretations of 69 consecutive submitted MRI or CT follow-up after pancreatic cancer resection between January 1, 2009 and December 31, 2013 were evaluated by one oncologic imaging radiologist, who was blinded to patient's clinical details and histopathologic data. The reviewer was asked to classify each interpretation in reference of the diagnosis of PDAC recurrence. It was also recorded if the radiologic interpretation recommended additional imaging studies to confirm recurrence. The diagnosis of recurrence was determined by pathology when available, otherwise by imaging follow-up, clinical, or laboratory assessments. Cohen's kappa statistic was used to assess agreement between initial and second-opinion interpretations. The differences between the initial and second-opinion interpretations were examined using McNemar test or Bowker's test of symmetry., Results: Disagreement on recurrence between the initial report and the second-opinion interpretation was observed in 32% of cases (22/69; k = 0.44). Second-opinion interpretations had a higher sensitivity and a higher specificity on recurrence compared to the initial interpretations (0.93 vs. 0.75 and 0.90 vs. 0.68, respectively), and the difference in specificity was significant (p = 0.016). Additional imaging studies were recommended more frequently in the initial interpretation (22% vs. 6%, p = 0.006)., Conclusions: Our study shows the second-opinion interpretation by subspecialized radiologists improves the detection of pancreatic cancer recurrence after surgical resection.

Rationale and Objectives: The purpose of this study is to compare image quality, presence and grade of artifacts, signal-to-noise ratio, and apparent diffusion coefficient (ADC) values in pancreatic tissue between high-resolution navigator-triggered (NT) restricted field of view (rFOV) FOCUS single-shot (SS) echo-planar imaging (EPI) diffusion-weighted imaging (DWI) and NT large FOV SS-EPI DWI., Materials and Methods: Magnetic resonance imaging examinations were performed with GE 3-T systems using a 32-channel body array coil. Seventeen consecutive patients were imaged. A 5-point scale semiquantitative grading system was used to evaluate image quality and general artifacts. Signal-to-noise ratio and ADC were measured in the head, body, and tail of the pancreas. Statistical analysis was performed using Student t test and Wilcoxon signed rank test, with differences considered significant for P value less than 0.05., Results: More artifacts were present on large FOV compared with rFOV FOCUS SS-EPI DW images (P < 0.01). Restricted field of view image quality was subjectively better (P < 0.01). No difference in the signal-to-noise ratio was demonstrated between the 2 image datasets. Apparent diffusion coefficient values were significantly lower (P < 0.01) when calculated from rFOV images than large FOV images., Conclusions: Our results demonstrate better image quality and reduced artifacts in rFOV images compared with large FOV DWI. Measurements from ADC maps derived from rFOV DWI show significantly lower ADC values when compared with ADC maps derived from large FOV DWI.

This retrospective study evaluated implant survival rate (SR) and marginal bone loss around dental implants placed with ultrasonic implant site preparation. A total of 156 implants were placed in 28 totally and partially edentulous patients. Bone loss was measured on intraoral paralleling digital radiographs taken at the impression phase and after 4 years of loading. As 3 implants (1.92%) failed at the second surgery stage, the SR was 98.08% after 4 years. The mean marginal bone loss was 0.52 ± 0.33 mm (0.51 ± 0.35 mm mesially and 0.53 ± 0.35 mm distally), with comparable values for implants inserted into the maxilla (0.52 ± 0.32 mm) and the mandible (0.52 ± 0.35 mm).

Background: Cancer patients often have a history of chemotherapy, putting them at increased risk of liver toxicity and pancytopenia, leading to elevated liver fat and elevated liver iron respectively. T1-in-and-out-of-phase, the conventional MR technique for liver fat assessment, fails to detect elevated liver fat in the presence of concomitantly elevated liver iron. IDEAL-IQ is a more recently introduced MR fat quantification method that corrects for multiple confounding factors, including elevated liver iron., Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. We reviewed the MRI studies of 50 cancer patients (30 males, 20 females, 50-78 years old) whose exams included (1) T1-in-and-out-of-phase, (2) IDEAL-IQ, and (3) T2* mapping. Two readers independently assessed fat and iron content from conventional and IDEAL-IQ MR methods. Intraclass correlation coefficient (ICC) was estimated to evaluate agreement between conventional MRI and IDEAL-IQ in measuring R2* level (a surrogate for iron level), and in measuring fat level. Agreement between the two readers was also assessed. Wilcoxon signed rank test was employed to compare iron level and fat fraction between conventional MRI and IDEAL-IQ., Results: Twenty percent of patients had both elevated liver iron and moderate/severe hepatic steatosis. Across all patients, there was high agreement between readers for IDEAL-IQ fat fraction (ICC = 0.957) and IDEAL R2* (ICC = 0.971) measurements, but lower agreement for conventional fat fraction measurements (ICC = 0.626). The fat fractions calculated with IOP were statistically significantly different from those calculated with IDEAL-IQ (reader 1: p < 0.001, reader 2: p < 0.001)., Conclusion: Fat measurements using IDEAL-IQ and IOP diverged in patients with concomitantly elevated liver fat and liver iron. Given prior work validating IDEAL-IQ, these diverging measurements indicate that IOP is inadequate to screen for hepatic steatosis in our cancer population.

Introduction: Chemotherapy prolongs the survival of patients with advanced and metastatic tumors. Since the liver plays an active role in the metabolism of chemotherapy agents, hepatic injury is a common adverse effect. The purpose of this study is to compare a novel quantitative chemical shift encoded magnetic resonance imaging (CSE-MRI) method with conventional T1-weighted In and Out of phase (T1 IOP) MR for evaluating the reproducibility of the methods in an oncologic population exposed to chemotherapy., Materials and Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. The study included patients who underwent chemotherapy, no suspected liver iron overload, and underwent upper abdomen MRI. Two radiologists independently draw circular ROIsin the liver parenchyma. The fat fraction was calculated from IOP imaging and measured from IDEAL-IQ fat fraction maps. Two different equations were used to estimate fat with IOP sequences. Intra-class correlation coefficient and repeatability coefficient were estimated to evaluate agreement between two readers on iron level and fat fraction measurement., Results: CSE-MRI showed a higher reliability in fat quantification compared with both IOP methods, with a substantially higher inter-reader agreement (0.961 vs 0.372). This has important clinical implications., Conclusion: The novel CSE-MRI method described here provides increased reproducibility and confidence in diagnosing hepatic steatosis in a oncologic clinical setting. IDEAL-IQ has been proved to be more reproducible than conventional IOP imaging., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Rationale: Hepatic epithelioid hemangioendothelioma (EHE) is a rare malignant vascular tumor of endothelial origin with a highly variable clinical presentation and natural history. Given its vascular origin, new therapies with inhibitors of vascular endothelial growth factor (VEGF) have been introduced in the treatment of these patients and have shown promising results. Few reports have described the role of F-Fluorodeoxyglucose positron emission tomography/contrast-enhanced computed tomography (F-FDG PET/CT) in the evaluation of this tumor after treatment with anti-angiogenic agents. Our case reports how F-FDG PET-CT scan was critical in the assessment of this tumor after treatment with an anti-angiogenic agent, Pazopanib, demonstrating complete metabolic response., Patient Concerns: A 30-year-old man with no previous significant medical history presented with pain in the right upper quadrant for over a year., Diagnoses: Multiple hepatic masses were found on abdominal ultrasound. Liver biopsy confirmed the diagnosis of epithelioid hemangioendothelioma. F-FDG PET/CT was performed for staging. Multiple FDG-avid hepatic, splenic, and lymph nodes lesions were detected on F-FDG PET/CT. A subsequent spleen biopsy confirmed splenic involvement. Immunohistochemistry was positive for CD31, CD34, and ERG, supporting the diagnosis of epithelioid hemangioendothelioma., Interventions: A 1-year cyclophosphamide treatment was provided followed by Pazopanib for 17 months., Outcomes: Six years after the first F-FDG PET/CT, F-FDG PET/CT performed for restaging demonstrated complete metabolic response to therapy. Follow-up CT demonstrated no interval changes in size of some of the treated lesions., Lesson: F-FDG PET/CT is useful for baseline assessment and posttreatment follow-up of this rare cancer.

Background: Gastroenteropancreatic neuroendocrine tumors (NETs) are rare entities arising from neuroendocrine cells in the gastroenteric tract and pancreas. The purpose of this article is to present four cases of gastroenteropancreatic NETs that featured a challenging diagnosis., Case Presentation: We report a case series of four NETs, each with different features. All NETs were suspected based on clinical and biochemical data. The workup of the abnormalities was performed with CT, PET or MRI., Conclusion: The diagnosis of NETs is challenging and generally based on clinical manifestations, blood biochemical tests, imaging techniques, and pathology., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Rationale and Objectives: To determine the impact of second-opinion assessment on cancer staging and patient management in patients with pancreatic ductal adenocarcinoma., Methods and Materials: This retrospective study was approved by our institutional review board with a waiver of informed consent. Second-opinion reports between January 1, 2009 and December 31, 2013, alongside outside reports for 65 consecutive cases of biopsy-proven pancreatic adenocarcinomas, were presented in random order to two experienced abdominal surgeons who independently reviewed them blinded to the origin of the report, images of the examinations, and patient identifier. Each surgeon filled in a questionnaire for each report recommending cancer staging and patient management. Recommended patient management and staging were evaluated against reference standards (actual patient management at 6 months following second-opinion assessment, and pathology or other clinical and imaging reference standards at 6 months or longer, respectively) using Cohen kappa., Results: Cancer staging differed in 13% (9 of 65) of cases for surgeon 1 and in 18.4% (12 of 65) for surgeon 2. Patient management changed in 38.4% (25 of 65) of cases for surgeon 1 and in 20% (13 of 65) for surgeon 2. When compared to the pathologic staging gold standard, second opinion was correct in 85.7% (six of seven) of the time for both surgeons. Recommended patient management from second-opinion reports showed good agreement with the reference standard (weighted k = 0.6467 [0.4014-0.892] and weighted k = 0.6262 [0.3954-0.857] for surgeon 2)., Conclusion: Second-opinion review by subspecialized oncologic radiologists can impact patient care, specifically in terms of management decision., (Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Objective: To evaluate the accuracy of single-source dual-energy computed tomography (ssDECT) in iodine quantification using various segmentation methods in an ex vivo model., Methods: Ten sausages, injected with variable quantities of iodinated contrast, were inserted into 2 livers and scanned with ssDECT. Material density iodine images were reconstructed. Three radiologists segmented each sausage. Iodine concentration, volume, and absolute quantity were measured. Agreement between the measured and injected iodine was assessed with the concordance correlation coefficient (CCC). Intrareader agreement was assessed using the intraclass correlation coefficient (ICC)., Results: Air bubbles were observed in sausage (IX). Sausage (X) was within the same view as hyper-attenuating markers used for localization. With IX and X excluded, CCC and ICC were greater than 0.98 and greater than 0.88. When included, CCC and ICC were greater than 0.94 and greater than 0.79., Conclusions: Iodine quantification was reproducible and precise. However, accuracy reduced in sausages consisting of air filled cavities and within the same view as hyperattenuating markers.

Rationale: Mediastinal nonseminomatous germ cell tumor (NSGCT) is an uncommon entity. Metastatic hepatic sarcomatous transformation is rare., Patient Concerns: We report a 24-year-old man with no previous related medical history presented with chest pain and left arm numbness., Diagnoses: The x-ray showed an anterior mediastinal mass. The chest computed tomography (CT) confirmed the presence of a mildly enhancing mass in the same location, without invasion of any vascular structure. A CT-guided biopsy was performed, revealing a primary mediastinal nonseminomatous germ cell tumor (NSGCT), yolk sac histology, with areas of somatic transformation to malignant nerve sheath tumor. After surgery patient was followed-up with imaging. Two years later a CT scan showed a new hepatic hyper vascular lesion, confirmed by a subsequent magnetic resonance imaging (MRI) and positron emission tomography (PET) scan. A CT-guided biopsy revealed a hepatic metastatic transformation to angiosarcoma of the primitive NSGCT., Interventions: The patient went on to received palliative chemotherapy., Outcomes: The patient is being followed-up regularly at the outpatient department., Lessons: Because of the potential of metastatic sarcoma arising from germ cell tumors, these patients should undergo periodical follow-up, with periodical scans. PET\CT scan might have a role in the follow-up of these patients., (Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Rationale: Glucagonoma is an uncommon disease but it has been associated with a pattern of symptoms defined as glucagonoma syndrome. These symptoms, if promptly recognized, could help to speed up the diagnosing process., Patient Concerns: We report a case of a 68-year-old woman with a pancreatic glucagonoma. Her symptoms at the onset were typical of the glucagonoma syndrome., Diagnoses: After a significant weight loss, she underwent a computer tomography scan of the abdomen, which showed a hypervascular lesion of the tail of the pancreas and hypervascular lesions of the liver. An ultrasound guided biopsy was performed and pathology was consistent with glucagonoma. Her blood glucagon levels were elevated., Outcomes: She was treated with chemotherapy and somatostatin analogs. After 4 years, the disease had a malignant transformation, and metastases suddenly started to grow up. She stopped being responsive to treatment and eventually passed away., Lessons: Due to its rarity, clinical diagnosis is challenging and generally it comes after a long interval since the onset of symptoms. Awareness of physicians and dermatologists of the characteristic necrolytic migratory erythema, and of the other symptoms, often leads to early diagnosis., (Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.)

A previously healthy 4-year-old girl presented with petechial rash and low platelet count. There were no other symptoms. On abdominal ultrasound, a 4.7-cm heterogeneous mass was demonstrated anterior to the left kidney. An abdominal MRI subsequently performed demonstrated a heterogeneously enhancing mass at the same location extending to the pancreas and spleen. A surgical biopsy of the mass was obtained. Pathology reported a malignant epithelioid neoplasm consistent with pancreatoblastoma. The mass demonstrated intense FDG uptake on PET and an FDG avid retrocaval lymph node.

The neuropsychiatric manifestations of alcoholism can be amended by neutralizing the somatic effects of alcohol on nervous centers. Tiapride acts electively on the mesolimbic area. Promising results have been obtained with tiapride in the various clinical forms of alcohol intoxication. Sixty patients (40 men and 20 women) were given tiapride for abnormal symptoms due to alcohol. Tolerance was good: no side-effects were recorded, with the exception of extrapyramidal manifestations in one patient. Symptoms due to alcohol abuse were alleviated. Relief of tremor was significant. Tiapride proved helpful in anxiety and depression and caused hallucinations to disappear in 35 cases.