People with chronic cough (a cough lasting more than 8 weeks) are often referred to different specialists and undergo numerous diagnostic tests, but clear guidance is lacking. This work summarizes a consensus (an agreement) among medical specialists who are involved in managing people with chronic cough: primary care physicians (family doctors), pulmonologists (doctors who specialize in lung conditions), allergists (medical professionals specializing in allergies) and ear, nose and throat (ENT) specialists. They discussed how to perform a basic assessment of people with chronic cough in primary care (day-to-day healthcare given by a general practitioner or family doctor) and how to refer them to different specialists based on clinical findings or test results.

UNASSIGNED: Distinguishing between large-vessel diseases such as acute aortic syndrome (AAS) and pulmonary embolism (PE), and non-large-vessel diseases, such as acute coronary syndrome (ACS), heart failure (HF), and neurogenic diseases, in patients presenting with chest symptoms remains a challenge, which can result in a significant number of misdiagnoses. Simultaneously distinguishing both AAS and PE is essential because large-vessel diseases require angio-computed tomography (CT) during initial presentation whereas, non-large-vessel diseases do not. This study aimed to determine the optimal method for differentiating between large-vessel and non-large-vessel diseases using D-dimer, troponin I, and pretest probability scores.
UNASSIGNED: From the 11683 patients who presented with chest symptoms including chest pain, discomfort, or dyspnea, this retrospective observational study included 1817 patients who had complete data for essential biomarkers; 105 with AAS, 139 with PE, 1093 with ACS, 451 with HF, and 83 with neurogenic diseases.
UNASSIGNED: D-dimer, D-dimer/troponin I ratio (DT ratio), and troponin I results distinguished the 2 groups: D-dimer (>2.38 μg/mL), AUC 0.935; DT ratio, AUC 0.827; and troponin I, AUC 0.653. For predicting AAS, the performances of D-dimer level and aortic dissection detection risk score (ADD-RS) were AUCs of 0.915 (p < 0.0001) and 0.67 (p = 0.0004), respectively; for predicting PE, the AUCs of D-dimer level and modified Wells score were 0.95 (p = 0.0001) and 0.857 (p < 0.0001), respectively.
UNASSIGNED: The D-dimer levels proved to be a crucial discriminator for identifying AAS and PE, even when compared with the ADD-RS and modified Wells scores. Moderately elevated D-dimer levels suggest the need to consider AAS and PE diagnoses via angio-CT for patients with chest symptoms.

OBJECTIVE: Diagnosing subcentimeter solid pulmonary nodules (SSPNs) remains challenging in clinical practice. Deep learning may perform better than conventional methods in differentiating benign and malignant pulmonary nodules. This study aimed to develop and validate a model for differentiating malignant and benign SSPNs using CT images.
METHODS: This retrospective study included consecutive patients with SSPNs detected between January 2015 and October 2021 as an internal dataset. Malignancy was confirmed pathologically; benignity was confirmed pathologically or via follow-up evaluations. The SSPNs were segmented manually. A self-supervision pre-training-based fine-grained network was developed for predicting SSPN malignancy. The pre-trained model was established using data from the National Lung Screening Trial, Lung Nodule Analysis 2016, and a database of 5478 pulmonary nodules from the previous study, with subsequent fine-tuning using the internal dataset. The model\'s efficacy was investigated using an external cohort from another center, and its accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were determined.
RESULTS: Overall, 1276 patients (mean age, 56 ± 10 years; 497 males) with 1389 SSPNs (mean diameter, 7.5 ± 2.0 mm; 625 benign) were enrolled. The internal dataset was specifically enriched for malignancy. The model\'s performance in the internal testing set (316 SSPNs) was: AUC, 0.964 (95% confidence interval (95%CI): 0.942-0.986); accuracy, 0.934; sensitivity, 0.965; and specificity, 0.908. The model\'s performance in the external test set (202 SSPNs) was: AUC, 0.945 (95% CI: 0.910-0.979); accuracy, 0.911; sensitivity, 0.977; and specificity, 0.860.
CONCLUSIONS: This deep learning model was robust and exhibited good performance in predicting the malignancy of SSPNs, which could help optimize patient management.

Epithelioid angiosarcoma is a rare high-grade vascular neoplasm with a poor prognosis. We present an anticoagulated 77-year-old man, with a history of popliteal/soleal vein thrombosis in the previous month, complaining of ipsilateral persistent lower limb pain and claudication. Absent popliteal/distal pulses prompted an arterial doppler ultrasound (DUS), revealing thrombosis of the distal superficial femoral artery and a popliteal mass. As the arterial wall\'s integrity could not be appropriately evaluated by DUS, adventitial cystic disease of the popliteal artery was suspected. Computed tomography angiography and magnetic resonance imaging findings were also suggestive. Due to refractory pain, he was submitted to a popliteal mass excision along with a femoral-posterior tibial bypass. Pathology revealed an epithelioid angiosarcoma. He was referred to a Sarcoma Center, requiring hospitalization for agitation and fever. A positron emission tomography (PET) scan revealed extensive lower limb disease persistence and distant metastases. He died on the 56th day after surgery. To our knowledge, there are only 15 cases of angiosarcoma of the popliteal artery described in the literature. Ours stands out as the first one unrelated to a popliteal aneurysm. Being a highly-aggressive tumor, an early diagnosis is challenging but essential to a successful treatment, warranting the need for suspicion of this neoplasm. An early core biopsy or surgical sample may expedite the diagnosis.

OBJECTIVE: To evaluate the diagnostic performance of quantitative magnetic resonance (MR) imaging biomarkers in distinguishing between inflammatory pancreatic masses (IPM) and pancreatic cancer (PC).
METHODS: A literature search was conducted using PubMed, Embase, the Cochrane Library, and Web of Science through August 2023. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the risk of bias and applicability of the studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the DerSimonian-Laird method. Univariate meta-regression analysis was used to identify the potential factors of heterogeneity.
RESULTS: Twenty-four studies were included in this meta-analysis. The two main types of IPM, mass-forming pancreatitis (MFP) and autoimmune pancreatitis (AIP), differ in their apparent diffusion coefficient (ADC) values. Compared with PC, the ADC value was higher in MFP but lower in AIP. The pooled sensitivity/specificity of ADC were 0.80/0.85 for distinguishing MFP from PC and 0.82/0.84 for distinguishing AIP from PC. The pooled sensitivity/specificity for the maximal diameter of the upstream main pancreatic duct (dMPD) was 0.86/0.74, with a cutoff of dMPD ≤ 4 mm, and 0.97/0.52, with a cutoff of dMPD ≤ 5 mm. The pooled sensitivity/specificity for perfusion fraction (f) was 0.82/0.68, and 0.82/0.77 for mass stiffness values.
CONCLUSIONS: Quantitative MR imaging biomarkers are useful in distinguishing between IPM and PC. ADC values differ between MFP and AIP, and they should be separated for consideration in future studies.
CONCLUSIONS: Quantitative MR parameters could serve as non-invasive imaging biomarkers for differentiating malignant pancreatic neoplasms from inflammatory masses of the pancreas, and hence help to avoid unnecessary surgery.
CONCLUSIONS: • Several quantitative MR imaging biomarkers performed well in differential diagnosis between inflammatory pancreatic mass and pancreatic cancer. • The ADC value could discern pancreatic cancer from mass-forming pancreatitis or autoimmune pancreatitis, if the two inflammatory mass types are not combined. • The diameter of main pancreatic duct had the highest specificity for differentiating autoimmune pancreatitis from pancreatic cancer.

Amplification of wideband high-frequency and microwave signals is a fundamental element within every high-frequency circuit and device. Ultra-wideband (UWB) sensor applications use circuits designed for their specific application. The article presents the analysis, design, and implementation of ultra-wideband differential amplifiers for M-sequence-based UWB applications. The designed differential amplifiers are based on the Cherry-Hooper structure and are implemented in a low-cost 0.35 µm SiGe BiCMOS semiconductor process. The article presents an analysis and realization of several designs focused on different modifications of the Cherry-Hooper amplifier structure. The proposed amplifier modifications are focused on achieving the best result in one main parameter\'s performance. Amplifier designs modified by capacitive peaking to achieve the largest bandwidth, amplifiers with the lowest possible noise figure, and designs focused on achieving the highest common mode rejection ratio (CMRR) are described. The layout of the differential amplifiers was created and the chip was manufactured and wire-bonded to the QFN package. For evaluation purposes, a high-frequency PCB board was designed. Schematic simulations, post-layout simulations, and measurements of the individual parameters of the designed amplifiers were performed. The designed and fabricated ultra-wideband differential amplifiers have the following parameters: a supply current of 100-160 mA at -3.3 V or 3.3 V, bandwidth from 6 to 12 GHz, gain (at 1 GHz) from 12 to 16 dB, noise figure from 7 to 13 dB, and a common mode rejection ratio of up to 70 dB.

OBJECTIVE: To investigate the computed tomography (CT) characteristics of air-containing space and its specific patterns in neoplastic and non-neoplastic ground glass nodules (GGNs) for clarifying their significance in differential diagnosis.
METHODS: From January 2015 to October 2022, 1328 patients with 1,350 neoplastic GGNs and 462 patients with 465 non-neoplastic GGNs were retrospectively enrolled. Their clinical and CT data were analyzed and compared with emphasis on revealing the differences of air-containing space and its specific patterns (air bronchogram and bubble-like lucency [BLL]) between neoplastic and non-neoplastic GGNs and their significance in differentiating them.
RESULTS: Compared with patients with non-neoplastic GGNs, female was more common (P < 0.001) and lesions were larger (P < 0.001) in those with neoplastic ones. Air bronchogram (30.1% vs. 17.2%), and BLL (13.0% vs. 2.6%) were all more frequent in neoplastic GGNs than in non-neoplastic ones (each P < 0.001), and the BLL had the highest specificity (93.6%) in differentiation. Among neoplastic GGNs, the BLL was more frequently detected in the larger (14.9 ± 6.0 mm vs. 11.4 ± 4.9 mm, P < 0.001) and part-solid (15.3% vs. 10.7%, P = 0.011) ones, and its incidence significantly increased along with the invasiveness (9.5-18.0%, P = 0.001), whereas no significant correlation was observed between the occurrence of BLL and lesion size, attenuation, or invasiveness.
CONCLUSIONS: The air containing space and its specific patterns are of great value in differentiating GGNs, while BLL is a more specific and independent sign of neoplasms.

Patients with an infected charcot spine (ICS) may experience little or no back pain despite severe vertebral destruction. Understanding the pathophysiology underlying ICS and its differential diagnoses is crucial for its accurate diagnosis. Worsening symptoms of chronic charcot spine should raise suspicions of an infection.

The chest radiograph is the most common imaging examination performed in most radiology departments, and one of the more common indications for these studies is suspected infection. Radiologists must therefore be aware of less common radiographic patterns of pulmonary infection if they are to add value in the interpretation of chest radiographs for this indication. This review uses a case-based format to illustrate a range of imaging findings that can be associated with acute pulmonary infection and highlight findings that should prompt investigation for diseases other than community-acquired pneumonia to prevent misdiagnosis and delays in appropriate management.

This study aimed to examine the imaging characteristics and clinical implications of atypical pleural lesions that mimic bone tumors and form along the inner margins of consecutive ribs. This retrospective analysis included 45 atypical pleural lesions arising from 13 patients who underwent chest computed tomography (CT) between April 2021 and March 2023. The clinical features, CT findings, and radiologic diagnoses prior to pathologic identification were examined. Pathological findings were reviewed in the surgically resected case. Subgroup analysis was performed based on the presence of concurrent typical pleural plaques. The mean age of the patients was 69.3±8.4 years with a predominance of males (76.9%). The lesions primarily exhibited unilateral involvement (84.6%), being most frequently located in the right mid-level posterior region. Calcification was present in 75.6% of cases, typically seen continuously along the ribs (82.4%). Adjacent rib changes were observed in 28.9% of cases. These lesions were frequently misdiagnosed as osteochondromas or bony spurs (55.6%) by thoracic radiologists. No significant growth was observed during follow-up (n=11, 47±41 months), and the pathological findings were consistent with pleural plaques. Patients with concurrent typical pleural plaques had more atypical pleural lesions without statistical significance (P=0.071) and showed a more even distribution (P=0.039). In conclusion, atypical pleural lesions resembling bone tumors along consecutive ribs represent a distinct subset of pleural plaques. Their unique distribution and morphology should be recognized by radiologists to avoid misinterpretation and unnecessary interventions.