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Rationale and Objectives: Efficiently detecting and characterizing metastatic bone lesions on staging CT is crucial for prostate cancer (PCa) care. However, it demands significant expert time and additional imaging such as PET/CT. We aimed to develop an ensemble of two automated deep learning AI models for 1) bone lesion detection and segmentation and 2) benign vs. metastatic lesion classification on staging CTs and to compare its performance with radiologists., Materials and Methods: This retrospective study developed two AI models using 297 staging CT scans (81 metastatic) with 4601 benign and 1911 metastatic lesions in PCa patients. Metastases were validated by follow-up scans, bone biopsy, or PET/CT. Segmentation AI (3DAISeg) was developed using the lesion contours delineated by a radiologist. 3DAISeg performance was evaluated with the Dice similarity coefficient, and classification AI (3DAIClass) performance on AI and radiologist contours was assessed with F1-score and accuracy. Training/validation/testing data partitions of 70:15:15 were used. A multi-reader study was performed with two junior and two senior radiologists within a subset of the testing dataset (n = 36)., Results: In 45 unseen staging CT scans (12 metastatic PCa) with 669 benign and 364 metastatic lesions, 3DAISeg detected 73.1% of metastatic (266/364) and 72.4% of benign lesions (484/669). Each scan averaged 12 extra segmentations (range: 1-31). All metastatic scans had at least one detected metastatic lesion, achieving a 100% patient-level detection. The mean Dice score for 3DAISeg was 0.53 (median: 0.59, range: 0-0.87). The F1 for 3DAIClass was 94.8% (radiologist contours) and 92.4% (3DAISeg contours), with a median false positive of 0 (range: 0-3). Using radiologist contours, 3DAIClass had PPV and NPV rates comparable to junior and senior radiologists: PPV (semi-automated approach AI 40.0% vs. Juniors 32.0% vs. Seniors 50.0%) and NPV (AI 96.2% vs. Juniors 95.7% vs. Seniors 91.9%). When using 3DAISeg, 3DAIClass mimicked junior radiologists in PPV (pure-AI 20.0% vs. Juniors 32.0% vs. Seniors 50.0%) but surpassed seniors in NPV (pure-AI 93.8% vs. Juniors 95.7% vs. Seniors 91.9%)., Conclusion: Our lesion detection and classification AI model performs on par with junior and senior radiologists in discerning benign and metastatic lesions on staging CTs obtained for PCa., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Bradford J. Wood: Principal investigator on cooperative research and development agreement (CRADA) between National Institutes of Health (NIH) and Philips and CRADAs with industry partners unrelated to this work; travel support related to CRADAs; royalties from NIH related to Philips licensing agreement; patents planned, issued, or pending. Peter L. Choyke: Receives payment from royalties paid to the U.S. government for patents on MRI US fusion biopsy licensed to Philips Medical. Peter A. Pinto: Institutional CRADA with Philips; royalties from NIH related to Philips licensing agreement; NIH-related patents planned, issued, or pending (U.S. patent nos. 8 447 384 and 10 215 830). Baris Turkbey: CRADAs with NVIDIA and Philips; royalties from NIH; patents planned, issued, or pending in the field of artificial intelligence. Dong Yang, Ziyue Xu, Jesse Tetreault, Daguang Xu: employee of NVIDIA Corporation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)

Purpose: Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the direct use of a large dataset with only clinically generated annotations in development of high-performance segmentation models for small research-quality challenge datasets., Materials and Methods: We used a large retrospective dataset from our institution comprised of 1,620 clinically generated segmentations, and two challenge datasets (PROMISE12: 50 patients, ProstateX-2: 99 patients). We trained a 3D U-Net convolutional neural network (CNN) segmentation model using our entire dataset, and used that model as a template to train models on the challenge datasets. We also trained versions of the template model using ablated proportions of our dataset, and evaluated the relative benefit of those templates for the final models. Finally, we trained a version of the template model using an out-of-domain brain cancer dataset, and evaluated the relevant benefit of that template for the final models. We used five-fold cross-validation (CV) for all training and evaluation across our entire dataset., Results: Our model achieves state-of-the-art performance on our large dataset (mean overall Dice 0.916, average Hausdorff distance 0.135 across CV folds). Using this model as a pre-trained template for refining on two external datasets significantly enhanced performance (30% and 49% enhancement in Dice scores respectively). Mean overall Dice and mean average Hausdorff distance were 0.912 and 0.15 for the ProstateX-2 dataset, and 0.852 and 0.581 for the PROMISE12 dataset. Using even small quantities of data to train the template enhanced performance, with significant improvements using 5% or more of the data., Conclusion: We trained a state-of-the-art model using unrefined clinical prostate annotations and found that its use as a template model significantly improved performance in other prostate segmentation tasks, even when trained with only 5% of the original dataset., Competing Interests: LSM and AMP report a financial interest in Avenda Health outside the submitted work. BT reports IP-related royalties from Philips outside the submitted work. The NIH has cooperative research and development agreements with NVIDIA, Philips, Siemens, Xact Robotics, Celsion Corp, and Boston Scientific outside the submitted work. The NIH has research partnerships with Angiodynamics, ArciTrax, and Exact Imaging outside the submitted work. CWA has received research equipment from NVIDIA Corporation, outside the submitted work. No commercial funding or equipment was used in the execution of this study. No other authors have competing interests to disclose.

The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using RT-PCR for testing. As a complimentary tool with diagnostic imaging, chest Computed Tomography (CT) has been shown to be able to reveal visual patterns characteristic for COVID-19, which has definite value at several stages during the disease course. To facilitate CT analysis, recent efforts have focused on computer-aided characterization and diagnosis with chest CT scan, which has shown promising results. However, domain shift of data across clinical data centers poses a serious challenge when deploying learning-based models. A common way to alleviate this issue is to fine-tune the model locally with the target domains local data and annotations. Unfortunately, the availability and quality of local annotations usually varies due to heterogeneity in equipment and distribution of medical resources across the globe. This impact may be pronounced in the detection of COVID-19, since the relevant patterns vary in size, shape, and texture. In this work, we attempt to find a solution for this challenge via federated and semi-supervised learning. A multi-national database consisting of 1704 scans from three countries is adopted to study the performance gap, when training a model with one dataset and applying it to another. Expert radiologists manually delineated 945 scans for COVID-19 findings. In handling the variability in both the data and annotations, a novel federated semi-supervised learning technique is proposed to fully utilize all available data (with or without annotations). Federated learning avoids the need for sensitive data-sharing, which makes it favorable for institutions and nations with strict regulatory policy on data privacy. Moreover, semi-supervision potentially reduces the annotation burden under a distributed setting. The proposed framework is shown to be effective compared to fully supervised scenarios with conventional data sharing instead of model weight sharing., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set (not included in training and validation) of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations.

Rationale and Objectives: The use of chest computed tomography (CT) in the era of the COVID-19 pandemic raises concern regarding the transmission risks to patients and staff caused by CT room contamination. Meanwhile the Center for Disease Control guidance for air exchange in between patients may heavily impact workflows. To design a portable custom isolation device to reduce imaging equipment contamination during a pandemic., Materials and Methods: Center for Disease Control air exchange guidelines and requirements were reviewed. Device functional requirements were outlined and designed. Engineering requirements were reviewed. Methods of practice and risk mitigation plans were outlined including donning and doffing procedures and failure modes. Cost impact was assessed in terms of CT patient throughput., Results: CT air exchange solutions and alternatives were reviewed. Multiple isolation bag device designs were considered. Several designs were custom fabricated, prototyped and reduced to practice. A final design was tested on volunteers for comfort, test-fit, air seal, and breathability. Less than 14 times enhanced patient throughput was estimated, in an ideal setting, which could more than counterbalance the cost of the device itself., Conclusion: A novel isolation bag device is feasible for use in CT and might facilitate containment and reduce contamination in radiology departments during the COVID Pandemic., (Published by Elsevier Inc.)

Computer aided diagnosis (CAD) tools help radiologists to reduce diagnostic errors such as missing tumors and misdiagnosis. Vision researchers have been analyzing behaviors of radiologists during screening to understand how and why they miss tumors or misdiagnose. In this regard, eye-trackers have been instrumental in understanding visual search processes of radiologists. However, most relevant studies in this aspect are not compatible with realistic radiology reading rooms. In this study, we aim to develop a paradigm shifting CAD system, called collaborative CAD (C-CAD), that unifies CAD and eye-tracking systems in realistic radiology room settings. We first developed an eye-tracking interface providing radiologists with a real radiology reading room experience. Second, we propose a novel algorithm that unifies eye-tracking data and a CAD system. Specifically, we present a new graph based clustering and sparsification algorithm to transform eye-tracking data (gaze) into a graph model to interpret gaze patterns quantitatively and qualitatively. The proposed C-CAD collaborates with radiologists via eye-tracking technology and helps them to improve their diagnostic decisions. The C-CAD uses radiologists' search efficiency by processing their gaze patterns. Furthermore, the C-CAD incorporates a deep learning algorithm in a newly designed multi-task learning platform to segment and diagnose suspicious areas simultaneously. The proposed C-CAD system has been tested in a lung cancer screening experiment with multiple radiologists, reading low dose chest CTs. Promising results support the efficiency, accuracy and applicability of the proposed C-CAD system in a real radiology room setting. We have also shown that our framework is generalizable to more complex applications such as prostate cancer screening with multi-parametric magnetic resonance imaging (mp-MRI)., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The detection of distant metastases at the initial diagnosis of prostate cancer (PCa) establishes the treatment approach and has a prognostic value, nevertheless it is not well established. Since proposed staging approaches often contradict each other, we aimed to compare the current imaging techniques for staging of advanced PCa, including future applications of the most innovative methods. Conventional imaging techniques, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) have been employed for metastatic staging (both N and M staging) of men with high-risk PCa, but surgical pelvic dissection remains the gold standard for N staging. However, functional MRI by using diffusion-weighted imaging, MR lymphography (MRL) with ultra-small paramagnetic iron oxide particles (USPIO), and hybrid PET/MRI imaging showed both high sensitivity and high specificity for nodal staging and depicting metastases. The standard of practice for M staging in PCa includes the radionuclide bone scan and targeted X-ray film, but their performance has generally been poor. Recently, MRI showed promising results with applications in both local and distant staging. Finally, with the development of new PET tracers, PET/CT and PET/MRI offer a combination of excellent pharmacokinetic characteristics, functional information, and precise anatomic localization and morphological correlation of tumor lesions.

Background: Carbonic anhydrase IX (CA-IX) is a potential imaging biomarker of clear cell renal cell carcinoma (ccRCC). Here, we report the results of a phase II clinical trial of a small molecule radiotracer targeting CA-IX ((18)F-VM4-037) in ccRCC., Methods: Between October 2012 and May 2013, 11 patients with kidney masses underwent (18)F-VM4-037 PET/CT prior to surgery. Dynamic imaging was performed for the first 45 min post injection and whole-body imaging was obtained at 60 min post injection. Tumors were surgically excised or biopsied within 4 weeks of imaging., Results: All patients tolerated the radiotracer well with no adverse events. Ten of the 11 patients had histologically confirmed malignancy. One patient had a Bosniak Type 3 cyst with no tumor found at surgery. Two patients had extrarenal disease and 9 had tumors only in the kidney. Primary ccRCC lesions were difficult to visualize on PET alone due to high uptake of the tracer in the adjacent normal kidney parenchyma, however when viewed in conjunction with CT, the tumors were easily localized. Metastatic lesions were clearly visible on PET. Mean SUV for primary kidney lesions was 2.55 in all patients; in patients with histologically confirmed ccRCC, the mean SUV was 3.16. The time-activity curves (TAC) are consistent with reversible ligand binding with peak activity concentration at 8 min post injection followed by washout. Distribution Volume Ratio (DVR) of the lesions was measured using the Logan graphical analysis method. The mean DVR value across the 9 kidney lesions was 5.2 ± 2.8, (range 0.68-10.34)., Conclusion: 18F-VM4-037 is a well-tolerated PET agent that allows same day imaging of CA-IX expression. The agent demonstrated moderate signal uptake in primary tumors and excellent visualization of CA-IX positive metastases. While the evaluation of primary ccRCC lesions is challenging due to high background activity in the normal kidney parenchyma, 18F-VM4-037 may be most useful in the evaluation of metastatic ccRCC lesions.

Purpose: (18)F-FDG PET/CT is used to characterize many malignancies, but is not recommended for localized prostate cancer. This study explores the value of multi-parametric MRI (mpMRI) in characterizing incidental prostate (18)F-FDG uptake., Methods: Thirty-one patients who underwent (18)F-FDG PET/CT for reasons unrelated to prostate cancer and prostate mpMRI were eligible for this retrospective study. The mpMRI included T2-weighted (T2W), dynamic contrast enhancement (DCE), apparent diffusion coefficient (ADC), and MR spectroscopy (MRS) sequences. Fourteen patients were excluded (n = 8 insufficient histopathology, n = 6 radical prostatectomy before PET), and final analysis included 17 patients. A nuclear medicine physician, blinded to clinicopathologic findings, identified suspicious areas and maximum standardized uptake values (SUV max) on (18)F-FDG PET/CT. Sector-based imaging findings were correlated with annotated histopathology from whole-mount or MRI/transrectal ultrasound fusion biopsy samples. Positive predictive values (PPVs) were estimated using generalized estimating equations with logit link. Results were evaluated with Kruskal-Wallis and Dunn's multiple comparisons tests., Results: The PPV of (18)F-FDG PET alone in detecting prostate cancer was 0.65. Combining (18)F-FDG PET as a base parameter with mpMRI (T2W, DCE, ADC, and MRS) increased the PPV to 0.82, 0.83, 0.83, and 0.94, respectively. All benign lesions had SUV max < 6. Malignant lesions had higher SUV max values that correlated with Gleason scores. There was a significant difference in SUV max per prostate between the Gleason ≥ 4 + 5 and benign categories (p = 0.03)., Conclusions: Focal incidental prostate (18)F-FDG uptake has low clinical utility alone, but regions of uptake may harbor high-grade prostate cancer, especially if SUV max > 6. Using mpMRI to further evaluate incidental (18)F-FDG uptake aids the diagnosis of prostate cancer.

Purpose of Review: Imaging plays an important role in the clinical management of prostate cancer (PCa). Thus, much effort has gone into improving imaging modalities in PCa. This review focuses on the recent advancements in transrectal ultrasound, MRI and PET during the past year., Recent Findings: Contrast-enhanced transrectal ultrasound with microbubbles may be useful in PCa, but needs further evaluation before more widespread use. Multiparametric MRI has emerged as a valuable tool to assist clinical management of PCa, and great progress has been made in the past year. Several radionuclides for PET/computed tomography have been tested in clinical trials; most of the studies have used radiolabeled choline. However, new PET tracers such as (18)F-1-amino-3-fluorine 18-fluorocyclobutane-1-carboxylic acid and (68)Ga-labeled prostate-specific membrane antigen ligands are demonstrating promising results. PET/MRI may further improve imaging in PCa, but this imaging modality needs to be evaluated further., Summary: Several advances in the imaging of PCa have been made during the past year. In particular, important clinical developments have been reported in multiparametric MRI, PET/computed tomography, and PET/MRI. The continuing development of imaging techniques in PCa has the potential to optimize treatment of PCa. However, the optimal imaging strategies for each of the major clinical scenarios in PCa have not yet been identified.

Purpose: To characterize uptake of 1-amino-3-fluorine 18-fluorocyclobutane-1-carboxylic acid ((18)F FACBC) in patients with localized prostate cancer, benign prostatic hyperplasia (BPH), and normal prostate tissue and to evaluate its potential utility in delineation of intraprostatic cancers in histopathologically confirmed localized prostate cancer in comparison with magnetic resonance (MR) imaging., Materials and Methods: Institutional review board approval and written informed consent were obtained for this HIPAA-compliant prospective study. Twenty-one men underwent dynamic and static abdominopelvic (18)F FACBC combined positron emission tomography (PET) and computed tomography (CT) and multiparametric (MP) 3-T endorectal MR imaging before robotic-assisted prostatectomy. PET/CT and MR images were coregistered by using pelvic bones as fiducial markers; this was followed by manual adjustments. Whole-mount histopathologic specimens were sliced with an MR-based patient-specific mold. (18)F FACBC PET standardized uptake values (SUVs) were compared with those at MR imaging and histopathologic analysis for lesion- and sector-based (20 sectors per patient) analysis. Positive and negative predictive values for each modality were estimated by using generalized estimating equations with logit link function and working independence correlation structure., Results: (18)F FACBC tumor uptake was rapid but reversible. It peaked 3.6 minutes after injection and reached a relative plateau at 15-20 minutes (SUVmax[15-20min]). Mean prostate tumor SUVmax(15-20min) was significantly higher than that of the normal prostate (4.5 ± 0.5 vs 2.7 ± 0.5) (P < .001); however, it was not significantly different from that of BPH (4.3 ± 0.6) (P = .27). Sector-based comparison with histopathologic analysis, including all tumors, revealed sensitivity and specificity of 67% and 66%, respectively, for (18)F FACBC PET/CT and 73% and 79%, respectively, for T2-weighted MR imaging. (18)F FACBC PET/CT and MP MR imaging were used to localize dominant tumors (sensitivity of 90% for both). Combined (18)F FACBC and MR imaging yielded positive predictive value of 82% for tumor localization, which was higher than that with either modality alone (P < .001)., Conclusion: (18)F FACBC PET/CT shows higher uptake in intraprostatic tumor foci than in normal prostate tissue; however, (18)F FACBC uptake in tumors is similar to that in BPH nodules. Thus, it is not specific for prostate cancer. Nevertheless, combined (18)F FACBC PET/CT and T2-weighted MR imaging enable more accurate localization of prostate cancer lesions than either modality alone., (RSNA, 2013)

Unlabelled: This work characterizes the uptake of (11)C-acetate in prostate cancer (PCa), benign prostate hyperplasia, and normal prostate tissue in comparison with multiparametric MRI, whole-mount histopathology, and clinical markers to evaluate the potential utility of (11)C-acetate for delineating intraprostatic tumors in a population of patients with localized PCa., Methods: Thirty-nine men with presumed localized PCa underwent dynamic-static abdominal-pelvic (11)C-acetate PET/CT for 30 min and 3-T multiparametric MRI before prostatectomy. PET/CT images were registered to MR images using pelvic bones for initial rotation-translation, followed by manual adjustments to account for prostate motion and deformation from the MRI endorectal coil. Whole-mount pathology specimens were sectioned using an MRI-based patient-specific mold resulting in improved registration between the MRI, PET, and pathology. (11)C-acetate PET standardized uptake values were compared with multiparametric MRI and pathology., Results: (11)C-acetate uptake was rapid but reversible, peaking at 3-5 min after injection and reaching a relative plateau at approximately 10 min. The average maximum standardized uptake value (10-12 min) of tumors was significantly higher than that of normal prostate tissue (4.4 ± 2.05 [range, 1.8-9.2] vs. 2.1 ± 0.94 [range, 0.7-3.4], respectively; P < 0.001); however, it was not significantly different from that of benign prostatic hyperplasia (4.8 ± 2.01 [range, 1.8-8.8]). A sector-based comparison with histopathology, including all tumors greater than 0.5 cm, revealed a sensitivity and specificity of 61.6% and 80.0%, respectively, for (11)C-acetate PET/CT and 82.3% and 95.1%, respectively, for MRI. The (11)C-acetate accuracy was comparable to that of MRI when only tumors greater than 0.9 cm were considered. In a small cohort (n = 9), (11)C-acetate uptake was independent of fatty acid synthase expression using immunohistochemistry., Conclusion: (11)C-acetate PET/CT demonstrates higher uptake in tumor foci than in normal prostate tissue; however, (11)C-acetate uptake in tumors is similar to that in benign prostate hyperplasia nodules. Although (11)C-acetate PET/CT is not likely to have utility as an independent modality for evaluation of localized PCa, the high uptake in tumors may make it useful for monitoring focal therapy when tissue damage after therapy may limit anatomic imaging methods.

Patient management in oncology increasingly relies on imaging for diagnosis, response assessment, and follow-up. The clinical availability of combined functional/anatomical imaging modalities, which integrate the benefits of visualizing tumor biology with those of high-resolution structural imaging, revolutionized clinical management of oncologic patients. Conventional high-resolution anatomical imaging modalities such as computed tomography (CT) and MRI excel at providing details on lesion location, size, morphology, and structural changes to adjacent tissues; however, these modalities provide little insight into tumor physiology. With the increasing focus on molecularly targeted therapies, imaging radiolabeled compounds with PET and single-photon emission tomography (SPECT) is often carried out to provide insight into a tumor's biological functions and its surrounding microenvironment. Despite their high sensitivity and specificity, PET and SPECT alone are substantially limited by low spatial resolution and inability to provide anatomical detail. Integrating SPECT or PET with a modality capable of providing these (i.e. CT or MR) maximizes their separate strengths and provides anatomical localization of physiological processes with detailed visualization of a tumor's structure. The availability of multimodality (hybrid) imaging with PET/CT, SPECT/CT, and PET/MR improves our ability to characterize lesions and affect treatment decisions and patient management. We have just begun to exploit the truly synergistic capabilities of multimodality imaging. Continued advances in the development of instrumentation and imaging agents will improve our ability to noninvasively characterize disease processes. This review will discuss the evolution of hybrid imaging technology and provide examples of its current and potential future clinical uses.

Small bowel wall thickening detected on computed tomography is a frequent finding in patients referring to emergency room with acute abdominal pain. In this pictorial review, we aim to discuss patterns of small bowel wall thickening and to explain hints for differential diagnosis with imaging findings.

Prostate cancer is a common cancer in men and continues to be a major health problem. Imaging plays an important role in the clinical management of patients with prostate cancer. An important goal for prostate cancer imaging is more accurate disease characterization through the synthesis of anatomic, functional, and molecular imaging information. Positron emission tomography (PET)/computed tomography (CT) in oncology is emerging as an important imaging tool. The most common radiotracer for PET/CT in oncology, (18)F-fluorodeoxyglucose (FDG), is not very useful in the imaging of prostate cancer. However, in recent years other PET tracers have improved the accuracy of PET/CT imaging of prostate cancer. Among these, choline labeled with (18)F or (11)C, (11)C-acetate, and (18)F-fluoride has demonstrated promising results, and other new radiopharmaceuticals are under development and evaluation in preclinical and clinical studies. Large prospective clinical PET/CT trials are needed to establish the role of PET/CT in prostate cancer patients. Because there are only limited available therapeutic options for patients with advanced metastatic prostate cancer, there is an urgent need for the development of more effective treatment modalities that could improve outcome. Prostate cancer represents an attractive target for radioimmunotherapy (RIT) for several reasons, including pattern of metastatic spread (lymph nodes and bone marrow, sites with good access to circulating antibodies) and small volume disease (ideal for antigen access and antibody delivery). Furthermore, prostate cancer is also radiation sensitive. Prostate-specific membrane antigen is expressed by virtually all prostate cancers, and represents an attractive target for RIT. Antiprostate-specific membrane antigen RIT demonstrates antitumor activity and is well tolerated. Clinical trials are underway to further improve upon treatment efficacy and patient selection. This review focuses on the recent advances of clinical PET/CT imaging and RIT of prostate cancer., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The emergence of CT angiography (CTA) has a groundbreaking impact on the evaluation of renal vessels and is gradually replacing the conventional catheter angiography as the standard imaging procedure. In this review, we aimed to describe the renal CTA technique and imaging findings of several renal arterial (i.e. atherosclerosis, fibromuscular dysplasia, aneurysms of the renal arteries, dissection, vasculitidis, follow-up of patients with renal arterial stent) and venous (i.e. nut-cracker syndrome, pelvic congestion syndrome) pathologies.

Exogenous lipoid pneumonia is a rare condition caused by aspiration of mineral, vegetable or animal oils. The aspiration of mineral oil is the most common cause of lipoid pneumonia in children. We present a 27-year-old man with a lipoid pneumonia with a history of daily use of Vaseline applied to cotton balls for ear plugging before swimming and shower.

Objective: The purposes of this essay are to outline MDCT angiographic techniques for the evaluation of the mesenteric arterial vasculature and to review anatomic variants depicted on MDCT angiograms., Conclusion: MDCT angiography has distinct advantages over conventional angiography in imaging of the mesenteric arterial vasculature.

Determination of renal neoplasms, hematoma, infarct, urinoma, cysts, and pyelonephritis may require contrast material administration following unenhanced CT in patients with flank pain. In this pictorial review, we aimed to clarify when contrast material administration is needed following vague urinary system findings on unenhanced CT.

Multidetector computed tomography (MDCT) is a useful technique for imaging the inferior mesenteric vein. The aim of the present review was to discuss the normal anatomy and the pathologies of the inferior mesenteric vein, including partial or total thrombosis secondary to inflammation (pyophlebitis) and malignancy, occlusion, dilatation and reversed flow, which are rarely encountered. Optimal reconstruction techniques are also discussed. The pathologies of the inferior mesenteric vein can be clearly demonstrated using MDCT using curved-planar reformatted multiplanar reconstruction (MPR) and minimum intensity projection (MIP) images.

Purpose: The objective of this study is to describe the computed tomography findings of peritoneal carcinomatosis of urinary bladder cancer., Material and Method: Patients with urinary bladder cancer were reviewed from patient database of our hospital, and 384 patients with urinary bladder cancer were identified. Computed tomography scans of 105 patients with urinary bladder cancer were retrospectively reviewed. Images were reviewed for presence of peritoneal implant, ascites, solid organ metastases, and retroperitoneal lymphadenopathy. Surgical history and follow-up courses of the patients were reviewed., Results: Computed tomography findings of peritoneal metastases were found in eight (7.6%) patients. Peritoneal involvement was diffuse in three patients and was in the form of implantation in five patients. In two patients, liver metastases were detected; additionally, one patient had accompanying pleural implants and one patient had adrenal gland metastases. Peritoneal involvement was detected in the preoperative stage in five patients., Conclusion: Presence of peritoneal carcinomatosis in cancer patients is an indicator of poor prognosis. Detection of peritoneal involvement in urinary bladder cancer patients can alter treatment strategy and may prevent unnecessary aggressive surgical interventions.

Pulmonary hypertension secondary to pulmonary venoocclusive disease (PVOD) is increasingly recognized (Wagenvoort, Chest 69:82-86, [20]; Scully et al., N Engl J Med 308:823-834, [21]). The clinical presentation is usually progressive pulmonary hypertension. It should be kept in mind when there is pulmonary arterial hypertension, pulmonary edema, and a normal pulmonary artery wedge pressure. Importance of diagnosing this condition is to protect patient from fatal pulmonary edema when using prostacyclins that are effective for treatment of primary pulmonary hypertension. Herein, we present multidetector computed tomography findings of PVOD in a pregnant woman that presented with pulmonary hypertension.

Objective: To assess impact of scanning direction on heart rates at certain levels of heart in electrocardiogram-gated 16-multidetector computed tomography (MDCT) detection of coronary artery bypass grafts and native coronary arteries., Methods: Ninety patients with 219 grafts were studied by 16-MDCT. Forty-five patients were scanned craniocaudally. The remaining 45 patients were scanned caudocranially. Heart rates at each level were noted and compared between the 2 groups., Results: The difference between mean heart rates of craniocaudal and caudocranial groups was found to be statistically significant at midcardiac, internal mammary artery origin, and cardiac base levels (P < 0.05). For the remaining levels, there was no statistically significant difference in mean heart rates., Conclusions: Performing electrocardiogram-gated 16-MDCT angiography for the evaluation of coronary arteries and bypass grafts in caudocranial direction provides lower heart rate at midcardiac and cardiac base levels of the heart, which are more prone to motion artifacts.

To assess the impact of scanning direction on the image quality of coronary artery bypass grafts (CABGs), native coronary arteries (NCAs) were examined by electrocardiographically (ECG) gated 16-row multidetector computed tomography (16-MDCT). Eighty-two patients with 209 grafts were studied by 16-MDCT. Forty-one patients with 111 grafts were scanned craniocaudally. Forty-one patients with 98 grafts were scanned caudocranially. CABG, native coronary arteries were examined in four (proximal, middle, distal, distal anastomoses), three (proximal, middle, distal) segments, respectively. Subjective image quality on a four-point scale was calculated for segments. Scores of groups were compared. Results Image quality scores of proximal, distal segments of the right coronary artery (RCA) were better in caudocranially scanned group (P<0.05). When we subgrouped patients according to initial heart rates (IHR) (group 1, <65 beats/min; group 2, > or =65 beats/min), there was no statistical significance between image quality scores of coronary arteries, CABG when IHR was <65 beats/min in groups regardless of scanning direction. Scores of anastomotic segment of CABG to RCA, middle segments of circumflex coronary artery, proximal and distal segments of RCA in caudocranially scanned group were better when the IHR is > or =65 beats/min compared with the craniocaudally scanned group. When the IHR of the patient is > or =65 beats/min, performing ECG-gated 16-MDCT angiography in the caudocranial direction provides better image quality for evaluation of coronary arteries and CABGs.

A case of bleeding pulmonary artery pseudoaneurysm secondary to squamous cell lung cancer is reported. The patient presented with massive hemoptysis, diagnosis was made with multidetector computed tomography, and the pseudoaneurysm was successfully embolized with platinum coils. Hemoptysis ceased following the procedure.