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The CT scan is an important diagnostic procedure for COVID-19. CT images tend to reveal similar features in most COVID-19 cases, including ground-glass opacity in the early stages and pulmonary consolidation in the later stages. The work presented here demonstrates the feasibility of developing a classification system for Covid-19 CT lung scans, which would assist doctors in distinguishing COVID-19 from healthy cases. Three architec-tures, ResN50, Inception-V3, and Xception, were trained, validated, and tested to achieve the highest accuracy. Furthermore, the influence of hyper-parameters on the accuracy of each model was evaluated, searching for minimal loss values. With this system, classification of CT scans can be performed. © 2022 CAD Solutions, LLC.

This paper aims to investigate the use of transfer learning architectures in the detection of COVID-19 from CT lung scans. The study evaluates the performances of various transfer learning architectures, as well as the effects of the standard Histogram Equalization and Contrast Limited Adaptive Histogram Equalization. The findings of this study suggest that transfer learning-based frameworks are an alternative to the contemporary methods used to detect the presence of the virus in patients. The highest performing model, the VGG-19 implemented with the Contrast Limited Adaptive Histogram Equalization, on a SARS-CoV-2 dataset, achieved an accuracy and recall of 95.75% and 97.13%, respectively.

This paper presents results of measurements of 99mTc activity concentration in air and nuclear medical personnel blood during ventilation–perfusion SPECT lung scans. 99mTc activity measurements were conducted at the Nuclear Medicine Department, John Paul II Hospital, Krakow. Technicians and nurses who perform examinations were equipped with personal aspirators enabling air sampling to determine the radiation exposure at their workplaces. Measurements allowed to evaluate the concentration of 99mTc in 14 air samples and it ranged from 7800 ± 600 to 10,000 ± 1000 Bq m−3 for air samples collected by technicians and from 390 ± 30 to 600 ± 40 Bq m−3 for air samples collected by nurses. In addition 99mTc concentrations in blood of medical personnel were determined in 24 samples. For technicians the maximum 99mTc blood concentration levels reached 920 ± 70 Bq L−1 and 1300 ± 100 Bq L−1. In the case of nurses, the maximum estimated activity concentrations were about ten times lower, namely 71 ± 7 Bq L−1 and 39 ± 3 Bq L−1. Although the intakes appear to be relatively high, the resulting annual effective doses are about 34 µSv for technicians and only 2 µSv for nurses.

This study introduces a novel technique of generating high-resolution 3D ventilation maps from hyperpolarized helium-3 MRI. It is the first study to demonstrate that regions of poor or absent ventilation seen on 3He MRI are primarily the result of airway closure.

Lung ultrasound used for semi-quantification of lung aeration and assessment of lung pathology. lung scan in the longitudinal approach could be identified in between the ribs. Transverse scan has the ability of visualization of longer pleural and more artifacts using lung scoring system or pathological identification. We included 50 patients from Benha University Hospital and Alexandria main university hospital eligible for our study scanned by lung ultrasound in long and transverse scanning technique and do comparison using CT scan as a gold standard. The study proved that transverse technique show more artifact and had both sensitivity and specificity for all lung pathology included.

ObjectivesGround-glass opacity (GGO) — a hazy, gray appearing density on computed tomography (CT) of lungs — is one of the hallmark features of SARS-CoV-2 in COVID-19 patients. This AI-driven study is focused on segmentation, morphology, and distribution patterns of GGOs.MethodWe use an AI-driven unsupervised machine learning approach called PointNet++ to detect and quantify GGOs in CT scans of COVID-19 patients and to assess the severity of the disease. We have conducted our study on the “MosMedData”, which contains CT lung scans of 1110 patients with or without COVID-19 infections. We quantify the morphologies of GGOs using Minkowski tensors and compute the abnormality score of individual regions of segmented lung and GGOs.ResultsPointNet++ detects GGOs with the highest evaluation accuracy (98%), average class accuracy (95%), and intersection over union (92%) using only a fraction of 3D data. On average, the shapes of GGOs in the COVID-19 datasets deviate from sphericity by 15% and anisotropies in GGOs are dominated by dipole and hexapole components. These anisotropies may help to quantitatively delineate GGOs of COVID-19 from other lung diseases.ConclusionThe PointNet++ and the Minkowski tensor based morphological approach together with abnormality analysis will provide radiologists and clinicians with a valuable set of tools when interpreting CT lung scans of COVID-19 patients. Implementation would be particularly useful in countries severely devastated by COVID-19 such as India, where the number of cases has outstripped available resources creating delays or even breakdowns in patient care. This AI-driven approach synthesizes both the unique GGO distribution pattern and severity of the disease to allow for more efficient diagnosis, triaging and conservation of limited resources.Key PointsOur approach to GGO analysis has four distinguishing features:We combine an unsupervised computer vision approach with convex hull and convex points algorithms to segment and preserve the actual structure of the lung.To the best of our knowledge, we are the first group to use PointNet++ architecture for 3D visualization, segmentation, classification, and pattern analysis of GGOs.We make abnormality predictions using a deep network and Cox proportional hazards model using lung CT images of COVID-19 patients.We quantify the shapes and sizes of GGOs using Minkowski tensors to understand the morphological variations of GGOs within the COVID-19 cohort.

INTRODUCTION Hybrid single photon emission computed tomography (SPECT) with CT (SPECT/CT) may improve diagnostic accuracy in suspected acute pulmonary embolism, but further research is needed. We evaluated whether the use of attenuation correction and/or the depiction of lung pathology with hybrid SPECT/CT could significantly reduce potentially false-positive ventilation-perfusion (VQ) SPECT studies or obviate the need for a ventilation study. METHODS Two specialists (S1 and S2) reviewed prospectively acquired VQ SPECT/CT in 165 patients. Studies were reported using standard criteria and compared to VQ SPECT and Q SPECT/CT. RESULTS S1 and S2 recorded positive VQ SPECT in 54 (32.7%) and 42 (25.6%) cases, respectively. Hybrid SPECT/CT showed non-embolic pathology in 41 (S1) and 46 (S2) patients, but compared to VQ SPECT, neither hybrid SPECT/CT nor attenuation correction SPECT/CT had significantly fewer positive studies. Intra-observer agreement with VQ SPECT/CT was almost perfect (k = 0.91 for S1 and k = 0.95 for S2; P

This paper presents the results of measurements of 99mTc activity concentrations in indoor air in a nuclear medicine department and resulting estimated 99mTc intake by medical personnel. 99mTc air activity measurements were conducted at the Nuclear Medicine Department, John Paul II Hospital, Krakow, Poland, during ventilation–perfusion SPECT lung scans. Technetium from the air was collected by means of a mobile aerosol sampler with a Petryanov filter operating at an average flow rate of 10 dm3 min−1. Measured activities ranged from 99 ± 11 to 6.1 ± 0.5 kBq m−3. The resulting daily average intake of 99mTc by medical staff was estimated to be 5.4 kBq, 4.4 kBq, 3.0 kBq and 2.5 kBq, respectively, for male technicians, female technicians, male nurses and female nurses. Corresponding annual effective doses were 1.6 µSv for technicians and 1 µSv for nurses. The highest equivalent dose values were determined for extrathoracic (ET) airways: 5 µSv and 10 µSv for nurses and technicians, respectively. It is concluded that estimated annual absorbed doses are over three orders of magnitude lower than the dose limit established in the Polish Atomic Law Act and in recommendations of the International Commission on Radiological Protection for medical staff.

Chronic thromboembolism pulmonary hypertension (CTEPH) is a common cause of severe pulmonary hypertension, resulting in significant morbidity and mortality. In patients with unexplained pulmonary hypertension, a ventilation-perfusion (VQ) scan should be considered the initial diagnostic test of choice. VQ scans are widely available with excellent sensitivity, specificity, and diagnostic accuracy. However, the occurrence of a normal VQ scan in the presence of CTEPH is believed to be rare. In fact, the rate of actual false negatives in VQ scans is unknown because pulmonary digital subtraction angiography and computed tomography pulmonary angiography are rarely performed in patients with a normal VQ scan. This study reports a patient with a high clinical likelihood of CTEPH due to a hypercoagulable state, recurrent deep vein thrombosis, and prior history of acute pulmonary embolism with negative VQ scans. He subsequently underwent pulmonary digital subtraction angiography, which revealed bilateral extensive emboli with partial recanalization of the organized thrombus. The patient underwent successful pulmonary endarterectomy, with marked improvement of his symptoms postoperatively. Keywords: CTEPH, VQ scan, CTPA, DSA, Pulmonary hypertension

This paper proposes an automatic method for accurate detection and visualization of B-lines in ultrasound lung scans, which provides a quantitative measure for the number of B-lines present. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Herlev, Denmark) driving a 5.5-MHz linear transducer (BK Ultrasound). Four healthy subjects and four patients, after major surgery with pulmonary edema, were scanned at four locations on each lung for B-line examination. Eight sequences of 50 frames were acquired for each subject yielding 64 sequences in total. The proposed algorithm was applied to all 3200 in-vivo lung ultrasound images. The results showed that the average number of B-lines was 0.28±0.06 (Mean±Std) in scans belonging to the patients compared to 0.03 ± 0.06 (Mean ± Std) in the healthy subjects. Also, the Mann–Whitney test showed a significant difference between the two groups with the $p$ -value of 0.015, and indicating that the proposed algorithm was able to differentiate between the healthy volunteers and the patients. In conclusion, the method can be used to automatically and to quantitatively characterize the distribution of B-lines for diagnosing pulmonary edema.

Chronic Pulmonary Aspergillosis (CPA) is a complex type of fungal infection caused by the Aspergillus fungus that mostly affects people with pre-existing lung lesions or weakened immune systems. Pleural thicknening, fungal balls and cavities visualized on CT scans are used to score the extent and gravity of CPA, in a qualitative manner. This work focuses on the use of deep-learning to improve current standards in localising and scoring CPA signs for longitudinal follow-up. We propose an original framework fully implemented in 3D, combining imaging and time series encoding, to provide activation maps, CPA severity scores and 5-years mortality prediction.

Background COVID-19 pandemic has currently no vaccines. Thus, the only feasible solution for prevention relies on the detection of COVID-19-positive cases through quick and accurate testing. Since artificial intelligence (AI) offers the powerful mechanism to automatically extract the tissue features and characterise the disease, we therefore hypothesise that AI-based strategies can provide quick detection and classification, especially for radiological computed tomography (CT) lung scans. Methodology Six models, two traditional machine learning (ML)-based (k-NN and RF), two transfer learning (TL)-based (VGG19 and InceptionV3), and the last two were our custom-designed deep learning (DL) models (CNN and iCNN), were developed for classification between COVID pneumonia (CoP) and non-COVID pneumonia (NCoP). K10 cross-validation (90% training: 10% testing) protocol on an Italian cohort of 100 CoP and 30 NCoP patients was used for performance evaluation and bispectrum analysis for CT lung characterisation. Results Using K10 protocol, our results showed the accuracy in the order of DL > TL > ML, ranging the six accuracies for k-NN, RF, VGG19, IV3, CNN, iCNN as 74.58 ± 2.44%, 96.84 ± 2.6, 94.84 ± 2.85%, 99.53 ± 0.75%, 99.53 ± 1.05%, and 99.69 ± 0.66%, respectively. The corresponding AUCs were 0.74, 0.94, 0.96, 0.99, 0.99, and 0.99 (p-values

Background The SwiftScan solution (General Electric Healthcare) combines a new low-energy high-resolution sensitivity collimator and a tomographic step-and-shoot continuous (SSC) mode acquisition. The purpose of this study is to determine whether SSC mode can be used in clinical practice with shorter examination times, while preserving image quality and ensuring accurate semi-quantification. Twenty bone scan and 10 lung scan studies were randomly selected over a period of 2 months. Three sets of image datasets were produced: step-and-shoot (SS) acquisition, simulated 25% count reduction using the Poisson resampling method (SimSS), and SimSS continuous acquisition (SimSSC), where SimSS was summed with counts acquired during detector head rotation. Visual assessment (5-point Likert scale, 2 readers) and semi-quantitative evaluation (50 focal uptake from 10 bone studies), assessed by SUVmean, coefficient of variation (COV), and contrast-to-noise ratio (CNR), were performed using t test and Bland-Altman analysis. Results Intra-reader agreement was substantial for reader 1 (k = 0.71) and for reader 2 (k = 0.61). Inter-reader agreement was substantial for SS set (k = 0.93) and moderate for SimSSC (k = 0.52). Bland-Altman analysis showed a good interchangeability of SS and SimSSC SUV values. The mean CNR between SS and SimSSC was not significantly different: 42.9 ± 43.7 [23.7–62.1] vs. 43.1 ± 46 [22.9–63.3] (p = 0.46), respectively. COV values, assessing noise level, did not deviate significantly between SS and SimSSC: 0.20 ± 0.08 [0.18–0.23] vs. 0.21 ± 0.08, [0.18–0.23] (p = 0.15), respectively, whereas a significant difference was demonstrated between SS and SimSS: 0.20 ± 0.08 [0.18–0.23] vs. 0.23 ± 0.09 [0.20–0.25] (p < 0.0001), respectively. Conclusions SSC mode acquisition decreases examination time by approximately 25% in bone and lung SPECT/CT studies compared to SS mode (~ 2 min per single-bed SPECT), without compromising image quality and signal quantification. This SPECT sensitivity improvement also offers the prospect of more comfortable exams, with less motion artifacts, especially in painful or dyspneic patients.

The zero echo time (ZTE) technique has improved the detection of lung nodules in PET/MRI but respiratory motion remains a challenge in lung scan. We investigated the feasibility and performance of fractionated deep-inspiration breath-hold (FDIBH) three-dimensional (3D) ZTE FDG PET/MRI for assessing lung nodules in patients with proved malignancy. Sixty patients who had undergone ZTE FDG PET/MRI and chest CT within a three-day interval were retrospectively included. Lung nodules less than 2 mm were excluded for analysis. Two physicians checked the adequacy of FDIBH ZTE and compared the lung nodule detection rates of FDIBH 3D ZTE and free-breathing (FB) four-dimensional (4D) ZTE, with chest CT as the reference standard. FDIBH resolved the effect of respiratory motion in 49 patients. The mean number and size of the pulmonary nodules identified in CT were 15 ± 31.3 per patient and 5.9 ± 4.6 mm in diameter. The overall nodule detection rate was 71% for FDIBH 3D ZTE and 70% for FB 4D ZTE (p = 0.73). FDIBH 3D ZTE significantly outperformed FB 4DZTE in detecting lung base nodules (72% and 68%; p = 0.03), especially for detecting those less than 6 mm (61% and 55%; p = 0.03). High inter-rater reliability for FDIBH 3D ZTE and FB 4D ZTE (k = 0.9 and 0.92) was noted. In conclusion, the capability of FDIBH 3D ZTE in respiratory motion resolution was limited with a technical failure rate of 18%. However, it could provide full expansion of the lung in a shorter scan time which enabled better detection of nodules (

A pulmonary nodule is a small round or oval-shaped growth in the lung. Pulmonary nodules are detected in Computed Tomography (CT) lung scans. Early and accurate detection of such nodules could help in successful diagnosis and treatment of lung cancer. In recent years, the demand for CT scans has increased substantially, thus increasing the workload on radiologists who need to spend hours reading through CT-scanned images. Computer-Aided Detection (CAD) systems are designed to assist radiologists in the reading process and thus making the screening more effective. Recently, applying deep learning to medical images has gained attraction due to its high potential. In this paper, inspired by the successful use of deep convolutional neural networks (DCNNs) in natural image recognition, we propose a detection system based on DCNNs which is able to detect pulmonary nodules in CT images. In addition, this system does not use image segmentation or post-classification false-positive r eduction t echniques which are commonly used in other detection systems. The system achieved an accuracy of 63.49% on the publicly available Lung Image Database Consortium (LIDC) dataset which contains 1018 thoracic CT scans with pulmonary nodules of different shapes and sizes.

The ventilation/perfusion lung scan has been in continuous use for approximately half a century, the same lifetime as Seminars in Nuclear Medicine. Remarkably, the founding Editors-in-Chief have continued to guide the journal over this entire period. In this Feschrift issue celebrating their enormous contribution, we review the history of the lung scan, its highs and lows, the transition from planar to SPECT/CT V/Q scans, and the future that is in store in this age of multimodality functional imaging. We concur with the published view of one of the retiring editors (LMF) that V/Q scintigraphy is indeed alive and well and has a definite future in clinical medicine.

BACKGROUND. The link between mucus plugs and airflow obstruction has not been established in chronic severe asthma, and the role of eosinophils and their products in mucus plug formation is unknown. METHODS. In clinical studies, we developed and applied a bronchopulmonary segment–based scoring system to quantify mucus plugs on multidetector computed tomography (MDCT) lung scans from 146 subjects with asthma and 22 controls, and analyzed relationships among mucus plug scores, forced expiratory volume in 1 second (FEV1), and airway eosinophils. Additionally, we used airway mucus gel models to explore whether oxidants generated by eosinophil peroxidase (EPO) oxidize cysteine thiol groups to promote mucus plug formation. RESULTS. Mucus plugs occurred in at least 1 of 20 lung segments in 58% of subjects with asthma and in only 4.5% of controls, and the plugs in subjects with asthma persisted in the same segment for years. A high mucus score (plugs in ≥ 4 segments) occurred in 67% of subjects with asthma with FEV1 of less than 60% of predicted volume, 19% with FEV1 of 60%–80%, and 6% with FEV1 greater than 80% (P < 0.001) and was associated with marked increases in sputum eosinophils and EPO. EPO catalyzed oxidation of thiocyanate and bromide by H2O2 to generate oxidants that crosslink cysteine thiol groups and stiffen thiolated hydrogels. CONCLUSION. Mucus plugs are a plausible mechanism of chronic airflow obstruction in severe asthma, and EPO-generated oxidants may mediate mucus plug formation. We propose an approach for quantifying airway mucus plugging using MDCT lung scans and suggest that treating mucus plugs may improve airflow in chronic severe asthma. TRIAL REGISTRATION. Clinicaltrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01718197","term_id":"NCT01718197"}}NCT01718197, {"type":"clinical-trial","attrs":{"text":"NCT01606826","term_id":"NCT01606826"}}NCT01606826, {"type":"clinical-trial","attrs":{"text":"NCT01750411","term_id":"NCT01750411"}}NCT01750411, {"type":"clinical-trial","attrs":{"text":"NCT01761058","term_id":"NCT01761058"}}NCT01761058, {"type":"clinical-trial","attrs":{"text":"NCT01761630","term_id":"NCT01761630"}}NCT01761630, {"type":"clinical-trial","attrs":{"text":"NCT01759186","term_id":"NCT01759186"}}NCT01759186, {"type":"clinical-trial","attrs":{"text":"NCT01716494","term_id":"NCT01716494"}}NCT01716494, and {"type":"clinical-trial","attrs":{"text":"NCT01760915","term_id":"NCT01760915"}}NCT01760915. FUNDING. NIH grants P01 HL107201, R01 HL080414, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109146","term_id":"1051682664"}}HL109146, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109164","term_id":"1051682685"}}HL109164, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109172","term_id":"1051682699"}}HL109172, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109086","term_id":"1051682577"}}HL109086, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109250","term_id":"1051682815"}}HL109250, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109168","term_id":"1051682692"}}HL109168, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109257","term_id":"1051682826"}}HL109257, U10 {"type":"entrez-nucleotide","attrs":{"text":"HL109152","term_id":"1051682671"}}HL109152, and P01 HL107202 and National Center for Advancing Translational Sciences grants UL1TR0000427, UL1TR000448, and KL2TR000428.

Repeated CT scans are known to increase the risk of cancer; thus, it is paradoxical to use multiple follow-up CT scans to monitor the development of a lung nodule and conduct early treatment of the nodule. In the case of a solitary lung nodule, regional scanning and region of interest (ROI) reconstruction are likely to restore the internal area at the nodule. A limited-range few-view CT is proposed in this paper for lung nodule follow-ups with extremely reduced X-radiation. For a planned scanning of an ROI, where a solitary lung nodule is positioned, a limited-range few-view CT can be employed, and thus, less tissue is exposed to X-radiation per view. An ROI reconstruction method is also proposed that makes full use of the former standard lung scan. The experimental results show that the nodule size and shape are preserved. In the case of a 40-mm ROI, the number of exposed X-rays can be reduced by 99.6% for a circular scan and 99.9% for a 3-D scan.

That CT angiography demonstrates evidence for chronic thrombus while the perfusion pattern on lung scintigraphy is normal can be readily explained. This case will demonstrate this “discrepancy” and underscores the value of a normal VQ scan in ruling out operable chronic thromboembolic disease.

COVID-19 was first discovered in Wuhan, China, and has spread rapidly around the world. The most important manifestation of COVID-19 was ARDS-like lung injury at first, but the involvement of other organs, such as kidney, heart, liver, and skin, was gradually reported. It is important to report and share all atypical manifestations of this disease to help other physicians to gain more knowledge about this new viral disease. As mentioned, there are also studies that show different types of cutaneous involvement in these patients, but due to the lack of more detailed studies in this field, and on the other hand, the possible usefulness of skin lesions as a diagnostic or alarming sign in the COVID-19 era, in this study we report a COVID-19 patient with a large hemorrhagic blister similar to sepsis-induced skin lesion. Despite the lack of common symptoms of the disease, the lung scan of the patient was positive for COVID-19.

The ventilation/perfusion lung scan is recommended to exclude chronic thromboembolic pulmonary hypertension in the diagnostic algorithm of pulmonary hypertension, but its role in pulmonary arterial hypertension (PAH) has not been well explored. We characterized the lung perfusion pattern assessed by lung perfusion scintigraphy in idiopathic PAH (IPAH) patients and evaluate the potential prognostic significance of the patchy pattern perfusion defect. A total of 318 patients with IPAH confirmed by right heart catheterization who performed lung perfusion scintigraphy were included. On lung perfusion scintigraphy, 134 patients had normal lung perfusion and 184 patients showed patchy perfusion defects. In comparison to patients with normal lung perfusion, patients with patchy perfusion defects experienced significantly higher mean pulmonary arterial pressure (58.0 ± 15.4 mmHg vs. 54.1 ± 16.2 mmHg, P = 0.027) and total pulmonary resistance (1192.6 ± 533.7 dyn·s·cm −5 vs. 1067.2 ± 549.3 dyn·s·cm −5 , P = 0.042). During a median follow-up period of 884.0 days, 53 patients reached the primary endpoint of all-cause mortality. On univariate Cox analysis, the patchy pattern of perfusion defect was significantly associated with the all-cause mortality (hazard ratio [HR] = 2.47, 95% confidence interval [CI] = 1.32–4.63, P = 0.005). Patients with patchy perfusion defects had a worse outcome (log-rank = 8.605, P = 0.003). On multivariate analysis, the patchy pattern remained as a significant independent predictor of the endpoint (HR = 2.30, 95% CI = 1.22–4.31, P = 0.010). IPAH patients presented with heterogeneity in lung perfusion and the patchy pattern of lung perfusion defect commonly existed. Patients with patchy pattern identified by lung perfusion scintigraphy were associated with more severe disease and worse outcome.

Introduction: The study aimed to analyse the results of radiographer’s image interpretation of nuclear medicine (NM) examinations following a nine-month postgraduate module. Methods: Twenty participants completed 60 summative image commentaries each at the end of the module from prospective NM worklists in England. Each submitted a mixed selection of examinations in bone, lung, renal, and thyroid scans. Prevalence of abnormalities was 51% incorporating acute and chronic pathology, normal variants and incidental findings. Every commentary was marked against reference standard radiologist definitive reports. Statistical analysis included Kappa (k), intraclass correlation coefficient (ICC) and Spearman’s rank correlation coefficient (RS). Results: Bone scan sensitivity and specificity was 93% (95% CI 91.3-95.6) and 88% (95% CI 84.3-90.9) respectively, accuracy at 91.5% (95% CI 88.6-93.7), with k=0.82, ICC= 0.904, RS=0.826. Lung scans demonstrated a sensitivity of 92.6% (95% CI 85.7-96.8), specificity was 92.1% (95% CI 88.7-94.1), accuracy 92.3% (95% CI 87.7-95.0), k=0.83, ICC=0.910, RS=0.835. Renal scan sensitivity was 95% (95% CI 91.0-97.3), with 95.2% specificity (95% CI 91.8-97.3), accuracy were 95% (95% CI 91.4-97.3), k=0.90, ICC=0.948, RS=0.907. Thyroid scans sensitivity was 88% (95% CI 83.1-91.4), with 93% specificity (95% CI 85.9-96.8), accuracy were 90.2% (95% CI 84.3-93.8), k=0.80, ICC=0.897, RS=0.813. Conclusion: In this small pilot study, the image interpretation ability in assessing prospective NM examinations in a clinical environment displayed encouraging results. Further work is recommended to evaluate a larger sample and case selection.

Background Computed tomography (CT) of the chest has replaced lung scans and pulmonary angiography as the criterion standard for the diagnosis of pulmonary embolism (PE). Most of these examinations are negative for PE, but they frequently have incidental findings that may require further evaluation. Objective In order to examine common incidental findings and their possible clinical ramifications and required workup, we reviewed data from relevant studies in which chest CTs were performed and incidental findings discovered. Discussion The most common incidental findings on chest CT are pulmonary nodules and lymph nodes. Nodules are significantly more commonly found in smokers and are also more likely to be malignant in smokers. The recently updated 2017 Fleischner Society recommendations provide guidance to clinicians in deciding which nodules should be further evaluated. Enlarged lymph nodes similarly represent potential malignancy and most will need further evaluation with positron emission tomography scans or by transbronchial needle aspiration. Conclusions Enlarged lymph nodes and pulmonary nodules are both common incidental findings on chest CT. Each represents the potential for malignancy, and under certain conditions requires additional workup and further evaluation. The majority will be benign, even in high-risk populations. However, because of the increasing prevalence of the chest CT and the frequency with which incidental findings will be seen, it is important that the emergency physician be aware of common features and recommended subsequent evaluation.

The optimal duration of anticoagulant therapy after a first episode of unprovoked pulmonary thromboembolism is not fully defined. The identification of patients more prone to recurrence would be useful in this context but is currently relatively unreliable. Perfusion lung scan (PLS) is an established approach for the follow-up of patients with pulmonary embolism to identify recurrences and to help in the diagnosis of chronic thromboembolic pulmonary hypertension. The aim of the study was to investigate the potential role of residual perfusion defects at follow-up perfusion scans in predicting pulmonary embolism recurrences. We retrospectively analyzed PLSs of 252 patients with a first episode of unprovoked, symptomatic pulmonary embolism. The agreement between two experienced readers, as assessed by the kappa test, was good, with kappa indices ranging from 0.84 (baseline scan) to 0.98 (last prerecurrence available scan). Sixteen patients developed a late (at least 1 month from the index episode) recurrence identified through the appearance of (a) new perfusion defect(s) not matching radiograph alterations. When patients were divided based on the presence or absence of at least two unperfused segments at the 6-month follow-up lung scan, the probability of recurrence was significantly higher in the latter (P = 0.03 by log-rank test). The use of persistent perfusion defects at follow-up PLS as a guide to determine optimal duration of anticoagulant therapy after a first, unprovoked episode of acute pulmonary thromboembolism is a viable strategy that should be further investigated.

The purpose of this study was to evaluate the utility of radionuclide perfusion lung scanning in the evaluation of primary pulmonary vein stenosis (PVS) in pediatric patients by comparing it with angiography.We retrospectively identified pediatric patients with primary PVS who underwent both lung scanning and angiography. A cohort of 34 patients was evaluated. The presence of PVS in the right upper, right lower, left upper, and left lower pulmonary veins on angiograms was recorded. Two nuclear medicine physicians evaluated the lung scans for perfusion defects. Agreement between lung scan and angiographic findings was assessed with contingency tables. Sensitivity and specificity of lung scanning for accurate detection of PVS with angiographic findings as the reference standard were assessed by ROC analysis.Angiography depicted PVS in 90 of the total 136 pulmonary veins (66%). Lung scans correctly depicted 65 (72%) of the cases of PVS diagnosed with angiography. The sensitivity and specificity of lung scans were 76.0% and 88.9% for the right upper pulmonary vein, 70.6% and 94.1% for the right lower pulmonary vein, 77.3% and 58.3% for the left upper pulmonary vein, and 65.4% and 87.5% for the left lower pulmonary vein.Lung scan findings correlate with angiographic findings in the detection of primary PVS in pediatric patients. Perfusion lung scanning may have a role in angiographically diagnosed PVS by noninvasively showing relative perfusion at the tissue level.

The purpose of this study was: (1) to determine the prevalence of deep vein thrombosis (DVT) after the use of a mechanical compression device only, without pharmacological thromboprophylaxis; (2) to investigate the factors associated with DVT; and (3) to investigate the natural course of DVT and PE. We reviewed consecutive series of 874 patients (1434 knees) who received treatment with a mechanical compression device only for prevention of DVT after primary TKA. The prevalence of DVT was 6.6% (94 of 1434 knees). Proximal thrombi were found in 6 of 1434 knees (0.4%). No patient had PE on perfusion lung scans. Further sonograms and venograms for the patients with thrombi at 6 months after the operation revealed that all thrombi were resolved.

Pulmonary hypertension (PH): mean pulmonary arterial pressure (mPAP) ≥ 25 mm Hg on right heart catheterization at rest. Pulmonary arterial hypertension (PAH): mPAP ≥ 25 mm Hg, pulmonary capillary wedge pressure (PCWP) ≤ 15 mm Hg and pulmonary vascular resistances (PVR) >3 Wood units. Patients with compatible symptoms (exertional dyspnea, syncopes, signes of right heart failure) can show signs of PH on cardiac echography and therefore need to be investigated in search of the cause of PH. After ruling out the frequent causes of PH (left heart and chronic respiratory diseases), the V/Q lung scan is used to screen for patients with post-embolic PH, that need to be further investigated hemodynamically and radiologically in order to decide operability. For the rest of the patients, only right heart catheterization can identify patients with precapillary PH and these patients must be further evaluated (clinically, by blood samples and by imaging techniques) in order to be classified in one the PH groups of the classification. For the future the discovery of novel risk factors and understanding the mechanism involved with the already known ones represent two major points of research.

OBJECTIVE Differential regional lung uptake (DRLU) analysis of a lung perfusion scan is used to provide information on diversion of the radiotracer from areas supplied by obstructed pulmonary artery branches to areas with patent vessels, which could assist in the diagnosis of pulmonary embolism (PE), especially the intermediate-probability studies. METHODS Lung perfusion scans performed over 3 years (n=121) were analyzed using a computer overlay of six regions of interest per lung on the posterior view. DRLU was defined for neighboring region pairs as the ratio of the difference in the average count rate to the sum of the count rate in the region pair for a total of 18 region pairs per study. RESULTS Comparison of the DRLU for high-probability studies (n=30) with normal scans (n=40) showed significant deviation in a least three region pairs per study. For low-probability scans (n=30), there was no significant deviation from the normal. For the intermediate category (n=21), a subgroup (n=7) showed significant deviation in at least three region pairs, which also had a positive computed tomography pulmonary angiography for PE, and another subgroup (n=14) had deviation in two or fewer region pairs with a negative computed tomography pulmonary angiography. CONCLUSION Using DRLU analysis, intermediate scans for PE could be redefined as low or high probability, on the basis of the number of region pairs showing deviation of DRLU. This could lead to improved diagnostic performance of the study without recourse to additional maneuvers or specialized equipment and would obviate the need for more tests on the patient.

Rationale and Objectives Today, lung volumes can be easily calculated from chest computed tomography (CT) scans. Modern postprocessing workstations allow automated volume measurement of data sets acquired. However, there are challenges in the use of lung volume as an indicator of pulmonary disease when it is obtained from routine CT. Intra-individual variation and methodologic aspects have to be considered. Our goal was to assess the reliability of volumetric measurements in routine CT lung scans. Materials and Methods Forty adult cancer patients whose lungs were unaffected by the disease underwent routine chest CT scans in 3-month intervals, resulting in a total number of 302 chest CT scans. Lung volume was calculated by automatic volumetry software. On average of 7.2 CT scans were successfully evaluable per patient (range 2–15). Intra-individual changes were assessed. Results In the set of patients investigated, lung volume was approximately normally distributed, with a mean of 5283 cm 3 (standard deviation = 947 cm 3 , skewness = −0.34, and curtosis = 0.16). Between different scans in one and the same patient the median intra-individual standard deviation in lung volume was 853 cm 3 (16% of the mean lung volume). Conclusions Automatic lung segmentation of routine chest CT scans allows a technically stable estimation of lung volume. However, substantial intra-individual variations have to be considered. A median intra-individual deviation of 16% in lung volume between different routine scans was found.