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The clinical risk factors and risk of developing pulmonary embolism (PE) in patients with acute isolated distal deep venous thrombosis (IDDVT) were assessed using single complete-duplex ultrasound (CDUS) imaging to reduce over-testing and over-treatment. This observational study was conducted from January 2020 to December 2022. Retrospective analysis was performed on CT pulmonary angiography (CTPA), blood coagulation markers, myocardial injury markers, blood gas analysis, and CDUS imaging of the lower extremity blood vessels of 146 patients with newly diagnosed IDDVT. Binary logistic regression was used to evaluate the relationship between these indicators and PE. After stepwise regression analysis, the predictors included in the regression model were D-dimer (DD), the sum of the thrombus length, and the maximum value of the thrombus width, with odds ratios (ORs) of 1.307 (p <0.001), 1.018 (p = 0.005), and 1.613 (p = 0.018), respectively. The combined prediction model achieved an area under the receiver operating characteristic curve (AUC) of 0.832 [95% confidence interval (CI): 0.761, 0.902]. By balancing the sensitivity and specificity of DD, combined single CDUS improves the predictive value for PE in patients with IDDVT. Key Words: Venous thrombosis, Pulmonary embolism, Ultrasonography, D-dimer, Diagnosis.

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Introduction: Pulmonary thromboembolism (PTE) has a wide range of clinical presentations. With the advances in computed tomography (CT) technology and easier access to CT, the incidence of incidentally diagnosed cases of PTE has increased. The main aim of our study was to determine the frequency of patients incidentally diagnosed with PTE and whether these patients differ from patients with symptomatic PTE in terms of case characteristics. Materials and Methods: We retrospectively analysed the charts of 148 patients with PTE diagnosed and treated in 2022. Demographic characteristics, thrombus localisation, risk factors, and treatment modalities were compared between symptomatic patients with clinically suspected PTE and patients with incidentally diagnosed PTE by imaging methods performed for other purposes without clinically suspected PTE. Result: Out of 148 patients with PTE, 42 (28.3%) were diagnosed incidentally. The rate of concomitant malignancy was significantly higher in patients with incidental PTE (54.8%) than in patients with symptomatic PTE (28.3%) (p < 0.01). There was no significant difference between symptomatic and incidental PTE patients in terms of the pulmonary artery segment in which the thrombus was located (p > 0.05). Conclusions: In our patient group, approximately one out of four patients diagnosed with PTE were incidentally diagnosed. Patients with malignancies may not have symptoms suspicious for PTE or their symptoms may go unrecognized.

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A man in his early 50s with previously treated pulmonary tuberculosis (TB) presented with a 3-month history of cough, expectoration and progressive breathlessness, accompanied by significant weight loss. Examination revealed tachycardia, tachypnoea, hypoxaemia and unilateral diminished breath sounds. Investigations showed anaemia, leucocytosis and a homogeneous opacity on the left side of the CXR. ECG and echocardiography suggested pulmonary thromboembolism (PTE). A CT pulmonary angiogram confirmed a chronic embolus and a severely fibrosed left lung. A comprehensive thrombophilia workup yielded normal results and the PTE was attributed to his history of TB. Sputum analysis confirmed reactivated TB, leading to the initiation of antitubercular therapy. The patient improved clinically with plans for a repeat CT pulmonary angiography to assess the need for pulmonary thromboendarterectomy after completing TB treatment. This case highlights the possible association of TB and PTE, its management and why it should be considered as a differential diagnosis in patients with a history of TB presenting with exacerbated breathlessness.

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AIM: The objective was to evaluate the serum levels of neutrophil gelatinase-associated lipocalin (NGAL), hypoxia-induced factor-1 alpha (HIF-1α), and apelin 13 in patients with acute pulmonary thromboembolism (PE) and to investigate their diagnostic and prognostic role in PE patients with different mortality risk groups. MATERIAL AND METHODS: This study was conducted in a tertiary referral center and included 124 subjects with 94 cases of PE and 30 cases of healthy control group. All subjects were 18 years of age or older. The diagnosis of PE was done with computed tomography angiography of the thorax. After the diagnosis of acute PE, the serum levels of neutrophil gelatinase-associated lipocalin (NGAL), hypoxia-induced factor-1 alpha (HIF-1α), and apelin 13 levels were measured with a commercial enzyme-linked immunosorbent assay (ELISA) kit. RESULTS: The median and IQR (interquartile range) age of patients and control groups were 68 (56-76) and 61.5 (56-67) years, respectively. The majority of patients with PE had risk factors (97.88 %), and only two (2.12 %) had no known risk factors. HIF-1 alpha level was found to be higher in the patient group than in the control group (p = 0.03). At the same time, the HIF-1 alpha level was found to be higher in the high mortality risk group than in the control group, low mortality risk group and intermediate-low mortality risk group (p = 0.000, 0.011, 0.002, respectively). While there was no significant difference in NGAL level between the patient group and the control group, a significant difference was observed between the mortality groups. NGAL level was found to be higher in the high mortality risk group than the control group, low mortality risk group, and medium-low mortality risk group (p = 0.001, 0.000, 0.010, respectively). Apelin 13 levels did not differ significantly in all groups. CONCLUSION: HIF-1 alpha is a promising biomarker in distinguishing between patients and control groups and in identifying those with high mortality risk in the patient group. At the same time, NGAL can be used as a successful biomarker in determining the group with high mortality risk in cases of PE.

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INTRODUCTION: The pulmonary Hot Clot artifact (HCa) on 18F-FDG PET/CT is a poorly understood phenomenon, corresponding to the presence of a focal tracer uptake without anatomical lesion on combined CTscan. The hypothesis proposed in the literature is of microembolic origin. Our objectives were to determine the incidence of HCa, to analyze its characteristics and to identify associated factors. METHODS: All 18F-FDG PET/CT retrieved reports containing the keywords (artifact/vascular adhesion/no morphological abnormality) during the period June 2021-2023 at Brest University Hospital were reviewed for HCa. Each case was associated with 2 control patients (same daily work-list). The anatomical and metabolic characteristics of HCa were analyzed. Factors related to FDG preparation/administration, patient and vascular history were investigated. Case-control differences between variables were tested using Chi-2 test and OR (qualitative) or Student's t-test (quantitative). RESULTS: Of the 22,671 18F-FDG PET/CT performed over 2 years, 211 patients (0.94%) showed HCa. The focus was single in 97.6%, peripheral in 75.3%, and located independently in the right or left lung (51.1% vs. 48.9%). Mean ± SD values for SUVmax, SUVmean, MTV and TLG were 11.3 ± 16.5, 5.1 ± 5.0, 0.3 ± 0.3 ml and 1.5 ± 2.1 g respectively. The presence of vascular adhesion (p < 0.001), patient age (p = 0.002) and proximal venous access (p = 0.001) were statistically associated with the presence of HCa. CONCLUSION: HCa is a real but rare phenomenon (incidence around 1%), mostly unique, intense, small in volume (< 1 ml), and associated with the presence of vascular FDG uptake, confirming the hypothesis of a microembolic origin due to probable vein wall trauma at the injection site.

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BACKGROUND: Kyphoplasty-associated cement extravasation into surrounding tissue and vasculature can lead to life-threatening complications. We present a rare case of significant inferior vena cava cement burden that resulted in pulmonary embolism. CASE PRESENTATION: A 74-year-old Caucasian woman with a history of severe osteoporosis, recurrent falls, and spinal compression fracture status post-kyphoplasty of the L4-L5 vertebrae, presents to the emergency department 2 days post-vertebral kyphoplasty due to chest pain, back pain, and dyspnea. Computed tomography of the chest and abdomen showed a metallic density within the inferior vena cava extending superiorly approximately 10 cm from the vertebral L5 level. She was also found to have right lower lobe pneumonia. The patient finished a 10-day course of antibiotics and was discharged home with a 1-month long course of anticoagulation with apixaban per recommendations of a multidisciplinary team consisting of Hematology/Oncology, Interventional Radiology, Vascular Surgery, and Orthopedic Surgery. Unfortunately, the patient was readmitted a month later with shortness of breath. Work up was notable for an influenza type A infection and computed tomography findings of pulmonary cement embolism. The respiratory distress was resolved with supportive care. Despite pulmonary cement burden, the multidisciplinary care team recommended no further anticoagulation. Patient was discharged home with close clinical follow-up and 6 months has since passed at the time of this report without reported complications. CONCLUSIONS: A large cement burden in the inferior vena cava leading to pulmonary cement embolism is a rare event. A high burden of cement predisposes development of pulmonary embolism. A short course of anticoagulation may only be needed for asymptomatic patients.

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BACKGROUND: Identification of pulmonary embolism (PE) across a cohort currently requires burdensome manual review. Previous approaches to automate capture of PE diagnosis have either been too complex for widespread use or have lacked external validation. We sought to develop and validate the Regular Expression Aided Determination of PE (READ-PE) algorithm, which uses a portable text-matching approach to identify PE in reports from computed tomography with angiography (CTA). METHODS: We identified derivation and validation cohorts of final radiology reports for CTAs obtained on adults (≥ 18 years) at two independent, quaternary academic emergency departments (EDs) in the United States. All reports were in the English language. We manually reviewed CTA reports for PE as a reference standard. In the derivation cohort, we developed the READ-PE algorithm by iteratively combining regular expressions to identify PE. We validated the READ-PE algorithm in an independent cohort, and compared performance against three prior algorithms with sensitivity, specificity, positive-predictive-value (PPV), negative-predictive-value (NPV), and the F1 score. RESULTS: Among 2948 CTAs in the derivation cohort 10.8 % had PE and the READ-PE algorithm reached 93 % sensitivity, 99 % specificity, 94 % PPV, 99 % NPV, and 0.93 F1 score, compared to F1 scores ranging from 0.50 to 0.85 for three prior algorithms. Among 1206 CTAs in the validation cohort 9.2 % had PE and the algorithm had 98 % sensitivity, 98 % specificity, 85 % PPV, 100 % NPV, and 0.91 F1 score. CONCLUSIONS: The externally validated READ-PE algorithm identifies PE in English-language reports from CTAs obtained in the ED with high accuracy. This algorithm may be used in the electronic health record to accurately identify PE for research or surveillance. If implemented at other EDs, it should first undergo local validation and may require maintenance over time.

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BACKGROUND: Computed tomography pulmonary angiography (CTPA) simplifies the diagnosis of pulmonary embolism (PE) but is not suitable for all patients. Transthoracic lung ultrasound (LUS) is a potential alternative; this meta-analysis evaluates its accuracy for diagnosing PE. METHODS: We systematically searched PubMed, Embase and Cochrane Library from the inception of each database up to April 2024 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies guidelines. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool, and a bivariate random effects model was used to pool sensitivity and specificity. RESULTS: A total of 18 studies with 2158 patients were analyzed. Lung ultrasound showed a sensitivity of 0.80 (95 %, confidence interval (CI): 0.71-0.86; I2 = 85.2 %) and specificity of 0.87 (95 %, CI: 0.81-0.92; I2 = 87.3 %). The diagnostic score was 3.27 (95 %, CI: 2.75-3.78; I2 = 61.9 %), and the diagnostic odds ratio was 26 (95 %, CI: 16-44; I2 = 100.0 %). The pooled positive likelihood ratio was 6.2 (95 %, CI: 4.2-9.1; I2 = 79.2 %), and the negative likelihood ratio was 0.24 (95 %, CI: 0.16-0.34; I2 = 83.7 %). The summary area under the curve was 0.91 (95 %, CI: 0.88-0.93). Significant heterogeneity was observed, which may impact the generalisability of the results, and no publication bias was detected. CONCLUSION: Transthoracic LUS shows potential as an alternative to CTPA for PE diagnosis, but further research is needed to improve its accuracy and establish standardised diagnostic criteria. The observed heterogeneity highlights the need for a cautious interpretation of the results.

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OBJECTIVE: This study aimed to retrospectively assess the benefits of combining low-dose computed tomography (LDCT) with ventilation/perfusion single-photon emission computed tomography (V/Q SPECT) for the diagnosis of pulmonary embolism (PE). METHODS: A retrospective analysis was performed on 92 patients with suspected PE who underwent V/Q SPECT with ldCT (V/Q SPECT CT) between January 2020 and December 2022 at King Khalid Hospital Najran. Data were collected using the hospital's picture archiving and communication system. Scans were categorized on the basis of perfusion defects, matched or mismatched ventilation, and CT findings. The specificity of V/Q SPECT CT was compared with that of Q SPECT CT. RESULTS: This study included 92 patients (54 females and 38 males; median age, 53 years). The results demonstrated that V/Q SPECT CT had higher specificity (93%) than V/Q SPECT alone (88%). If CT had been used as a ventilation substitute, 21% of patients would have been reported to be positive for PE (8% false-positive), yielding a specificity of 60% for Q SPECT CT. These findings align with the existing literature, although discrepancies in specificity values were noted due to the different study designs and sample sizes. CONCLUSION: This study highlights the enhanced specificity of V/Q SPECT CT compared to V/Q SPECT and Q SPECT CT alone. Including low-dose CT improves diagnostic accuracy by reducing false positives and providing detailed anatomical information. V/Q SPECT CT offers superior specificity in diagnosing PE compared with V/Q SPECT alone, supporting its use in clinical practice.

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BACKGROUND: Swyer-James-MacLeod syndrome (SJMS) is a rare lung condition characterized by a unilateral lung hyperlucency and reduction in the pulmonary vasculature, with or without the presence of bronchiectasis. In the 1950s, Swyer, James, and Macleod simultaneously characterized the syndrome for the first time. It is typically diagnosed in childhood. Adult-onset cases are extremely rare, with little literature available on its clinical presentation and diagnostic challenges. Swyer-James-MacLeod syndrome can mimic other lung disorders, resulting in misdiagnosis and improper treatment. CASE PRESENTATION: A 49- year-old woman from Debre Berhan, Ethiopia, presented to the emergency department of Hakim Gizaw Teaching Hospital with symptoms and radiographic findings mimicking acute pulmonary embolism. On the basis of the clinical presentation and radiographic findings, the patient was first treated as a probable case of pulmonary embolism. Anticoagulant therapy and oxygen support were initiated. Nevertheless, additional testing using a chest computed tomography angiography revealed left lung hyperlucency, decreased vascularity, bronchiectasis, and a negative result for pulmonary embolism. As a result, Swyer-James-MacLeod syndrome was diagnosed. CONCLUSION: The symptoms of Swyer-James-MacLeod syndrome can be mistaken for pulmonary embolism, which could lead to ineffective treatment and needless expenses. In individuals presenting with symptoms suggestive of pulmonary embolism, this case emphasizes the significance of considering Swyer-James-MacLeod syndrome as a differential diagnosis, especially in the absence of established risk factors for pulmonary embolism.

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PURPOSE: Diagnosing pulmonary embolism (PE) is still challenging due to other conditions that can mimic its appearance, leading to incomplete or delayed management and several inter-observer variabilities. This study evaluated the performance and clinical utility of an artificial intelligence (AI)-based application designed to assist clinicians in the detection of PE on CT pulmonary angiography (CTPA). PATIENTS AND METHODS: CTPAs from 230 US cities acquired on 57 scanner models from 6 different vendors were retrospectively collected. Three US board certified expert radiologists defined the ground truth by majority agreement. The same cases were analyzed by CINA-PE, an AI-driven algorithm capable of detecting and highlighting suspected PE locations. The algorithm's performance at a per-case and per-finding level was evaluated. Furthermore, cases with PE not mentioned in the clinical report but correctly detected by the algorithm were analyzed. RESULTS: A total of 1204 CTPAs (mean age 62.1 years ± 16.6[SD], 44.4 % female, 14.9 % positive) were included in the study. Per-case sensitivity and specificity were 93.9 % (95%CI: 89.3 %-96.9 %) and 94.8 % (95%CI: 93.3 %-96.1 %), respectively. Per-finding positive predictive value was 89.5 % (95%CI: 86.7 %-91.9 %). Among the 196 positive cases, 29 (15.6 %) were not mentioned in the clinical report. The algorithm detected 22/29 (76 %) of these cases, leading to a reduction in the miss rate from 15.6 % to 3.8 % (7/186). CONCLUSIONS: The AI-based application may improve diagnostic accuracy in detecting PE and enhance patient outcomes through timely intervention. Integrating AI tools in clinical workflows can reduce missed or delayed diagnoses, and positively impact healthcare delivery and patient care.

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Objective.The diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH) is challenging due to nonspecific early symptoms, complex diagnostic processes, and small lesion sizes. This study aims to develop an automatic diagnosis method for CTEPH using non-contrasted computed tomography (NCCT) scans, enabling automated diagnosis without precise lesion annotation.Approach.A novel cascade network (CN) with multiple instance learning (CNMIL) framework was developed to improve the diagnosis of CTEPH. This method uses a CN architecture combining two Resnet-18 CNN networks to progressively distinguish between normal and CTEPH cases. Multiple instance learning (MIL) is employed to treat each 3D CT case as a 'bag' of image slices, using attention scoring to identify the most important slices. An attention module helps the model focus on diagnostically relevant regions within each slice. The dataset comprised NCCT scans from 300 subjects, including 117 males and 183 females, with an average age of 52.5 ± 20.9 years, consisting of 132 normal cases and 168 cases of lung diseases, including 88 cases of CTEPH. The CNMIL framework was evaluated using sensitivity, specificity, and the area under the curve (AUC) metrics, and compared with common 3D supervised classification networks and existing CTEPH automatic diagnosis networks.Main results. The CNMIL framework demonstrated high diagnostic performance, achieving an AUC of 0.807, accuracy of 0.833, sensitivity of 0.795, and specificity of 0.849 in distinguishing CTEPH cases. Ablation studies revealed that integrating MIL and the CN significantly enhanced performance, with the model achieving an AUC of 0.978 and perfect sensitivity (1.000) in normal classification. Comparisons with other 3D network architectures confirmed that the integrated model outperformed others, achieving the highest AUC of 0.8419.Significance. The CNMIL network requires no additional scans or annotations, relying solely on NCCT. This approach can improve timely and accurate CTEPH detection, resulting in better patient outcomes.

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This review explores the clinical presentation of lower extremity DVT and pulmonary embolism (PE), treatment strategies, and outcomes for venous thromboembolism (VTE) in the pediatric population. Traditional therapy for pediatric VTE was anticoagulation alone with thrombolysis and surgery reserved only in life or limb-threatening cases. Catheter-directed thrombolysis (CDT), pharmacomechanical thrombectomy (PMT) and mechanical thrombectomy (MT) have emerged as effective and safe treatment options for VTE management. Although most data are from adult studies, early pediatric studies suggest that these interventional procedures can be effective in children. The significant clinical impact of post-thrombotic syndrome (PTS) is also discussed, as PTS can lead to lifelong physical symptoms and psychosocial damage.

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This paper presents an artificial intelligence-based classification model for the detection of pulmonary embolism in computed tomography angiography. The proposed model, developed from public data and validated on a large dataset from a tertiary hospital, uses a two-dimensional approach that integrates temporal series to classify each slice of the examination and make predictions at both slice and examination levels. The training process consists of two stages: first using a convolutional neural network InceptionResNet V2 and then a recurrent neural network long short-term memory model. This approach achieved an accuracy of 93% at the slice level and 77% at the examination level. External validation using a hospital dataset resulted in a precision of 86% for positive pulmonary embolism cases and 69% for negative pulmonary embolism cases. Notably, the model excels in excluding pulmonary embolism, achieving a precision of 73% and a recall of 82%, emphasizing its clinical value in reducing unnecessary interventions. In addition, the diverse demographic distribution in the validation dataset strengthens the model's generalizability. Overall, this model offers promising potential for accurate detection and exclusion of pulmonary embolism, potentially streamlining diagnosis and improving patient outcomes.

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The intersection of COVID-19 and pulmonary embolism (PE) has posed unprecedented challenges in medical diagnostics. The critical nature of PE and its increased incidence during the pandemic underline the need for improved detection methods. This study evaluates the effectiveness of advanced deep learning techniques in enhancing PE detection in post-COVID-19 patients through Computed Tomography Pulmonary Angiography (CTPA) scans. Using a dataset of 746 anonymized CTPA images from 25 patients, we fine-tuned the state-of-the-art Ultralytics YOLOv8 object detection model, which was trained on 676 images with 1,517 annotated bounding boxes and validated on 70 images with 108 bounding boxes. After 200 epochs of training, which lasted approximately 1.021 hours, the YOLOv8 model demonstrated significant diagnostic proficiency, achieving a mean Average Precision (mAP) of 0.683 at an IoU threshold of 0.50 and a mAP of 0.246 at the IoU range of 0.50:0.95 in the validation dataset. Notably, the model reached a maximum precision of 0.85949 and a maximum recall of 0.81481, though these metrics were observed in separate epochs. These findings emphasize the model's potential for high diagnostic accuracy and offer a promising direction for deploying AI tools in clinical settings, significantly contributing to healthcare innovation and patient care post-pandemic.

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BACKGROUND: Hepatocellular adenoma is a rare benign liver tumor. Typically, hepatocellular adenomas are solitary and are found in young women who use estrogen-containing contraceptives. The occurrence of multiple hepatocellular adenoma has been linked to higher body mass index, and as the prevalence of overweight increases, multiple hepatocellular adenomas are seen more often. An hepatocellular adenoma does not always necessitate treatment, as they can regress under conservative strategies. In incidental cases, an adenoma presents owing to bleeding, which is mostly self-limiting. If it is not, embolization of hepatic involved vessels is indicated. CASE PRESENTATION: In this case report, we discuss a 42-year old Caucasian woman with multiple hepatocellular bleeds, treated by multiple endovascular procedures. After the first embolization of an adenoma in the right liver lobe, a second bleed occurred in the left lobe, necessitating additional endovascular intervention. During admittance, treatment was complicated by pulmonary embolism and a pneumonia. During follow-up, our patient was diagnosed with antiphospholipid syndrome. CONCLUSION: Hepatocellular adenoma is a rare diagnosis that requires centralized expertise. This particular case illustrates the complexity of treatment strategies for associated intra-abdominal bleeding and possible complications. Although liver adenoma is often an incidental finding, it can also result in significant morbidity. Centralization of treatment leads to expertise in managing complex treatment strategies.

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