Machine learning to predict lymph node metastasis in T1 esophageal squamous cell carcinoma: a multicenter study.

Background: Existing models do poorly when it comes to quantifying the risk of lymph node metastases (LNM). This study aimed to develop a machine-learning model for LNM in patients with T1 esophageal squamous cell carcinoma (ESCC).

Methods And Results: The study is multicenter and population based.

Enhanced quantum secret sharing protocol for anonymous secure communication utilizing W states.

Quantum secret sharing (QSS) represents the fusion of quantum mechanics principles with secret information sharing, allowing a sender to distribute a secret among receivers for collective recovery. This paper introduces the concept of quantum anonymous secret sharing (QASS) to enhance the practicality of such protocols. We propose a QASS protocol leveraging W states, ensuring both recover-security and anonymity of shared secrets.

Correlation between Mean Platelet Volume and Gensini Score in Patients with Coronary Heart Disease in Different Diabetic States.

Subject: To investigate the correlation between mean platelet volume (MPV) levels and Gensini scores in stable coronary heart disease (CHD) patients with or without diabetes.

Methods: A retrospective analysis was conducted on 2525 patients with stable CHD in Zhongshan Hospital, Fudan University. There were 1274 in the low MPV group and 1251 in the high MPV group, divided by a median MPV level of 10.

Enhanced phase sensitivity in a Mach-Zehnder interferometer via photon recycling.

We propose an alternative scheme for phase estimation in a Mach-Zehnder interferometer (MZI) with photon recycling. It is demonstrated that with the same coherent-state input and homodyne detection, our proposal possesses a phase sensitivity beyond the traditional MZI. For instance, it can achieve an enhancement factor of ∼9.

Sensitivity and specificity of magnetic resonance imaging in routine diagnosis of pulmonary lesions: a comparison with computed tomography.

Background: State-of-the-art thoracic magnetic resonance imaging (MRI) plays a complementary role in the assessment of pulmonary nodules/masses which potentially indicate to cancer. We aimed to evaluate the sensitivity and specificity of MRI in diagnosis of pulmonary nodules/masses.

Methods: Sixty-eight patients with computed tomography (CT)-detected pulmonary nodules/masses underwent 3T MRI (T1-VIBE, T1-starVIBE, T2-fBLADE turbo spin-echo, and T2-SPACE).

Applying a CT texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images in pulmonary nodule diagnosis.

Objective: To investigate the feasibility and accuracy of applying a computed tomography (CT) texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images for classifying pulmonary nodules.

Materials And Methods: CT images of 102 patients, with a total of 118 pulmonary nodules (52 benign, 66 malignant) were retrospectively reconstructed with a deep-learning reconstruction (artificial intelligence iterative reconstruction [AIIR]) and a hybrid iterative reconstruction (HIR) technique. The AIIR data were divided into a training (n = 96) and a validation set (n = 22), and the HIR data were set as the test set (n = 118).

Radiomics nomogram analysis of T2-fBLADE-TSE in pulmonary nodules evaluation.

Objectives: To develop and validate a radiomics nomogram for differentiating between malignant pulmonary nodules and benign nodules.

Methods: 56 benign and 51 malignant nodules from 96 patients were analyzed using manual segmentation of the T2-fBLADE-TSE, while the nodules signal intensity (SIlesion), lesion muscle ratio (LMR) and nodule size were all measured and recorded. The maximum relevance and minimum redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select nonzero coefficients and develop the model in pulmonary nodules diagnosis.

Intra-observer and inter-observer agreements for the measurement of dual-input whole tumor computed tomography perfusion in patients with lung cancer: Influences of the size and inner-air density of tumors.

Background: This study was conducted to assess intra-observer and inter-observer agreements for the measurement of dual-input whole tumor computed tomography perfusion (DCTP) in patients with lung cancer.

Methods: A total of 88 patients who had undergone DCTP, which had proved a diagnosis of primary lung cancer, were divided into two groups: (i) nodules (diameter ≤3 cm) and masses (diameter >3 cm) by size, and (ii) tumors with and without air density. Pulmonary flow, bronchial flow, and pulmonary index were measured in each group.

Bedside chest radiography of novel influenza A (H7N9) virus infections and follow-up findings after short-time treatment.

Background: Influenza A (H7N9) virus infections were first observed in China in March 2013. This type virus can cause severe illness and deaths, the situation raises many urgent questions and global public health concerns. Our purpose was to investigate bedside chest radiography findings for patients with novel influenza A (H7N9) virus infections and the followup appearances after short-time treatment.

Emerging H7N9 influenza A (novel reassortant avian-origin) pneumonia: radiologic findings.

Purpose: To determine the radiologic findings of human infection with a novel reassortant avian-origin influenza A H7N9 virus in March 2013, the first outbreak in humans.

Materials And Methods: The institutional review board approved this retrospective study. Twelve patients (nine men and three women) with novel avian-origin influenza A H7N9 virus infection were enrolled.

Clinical findings for early human cases of influenza A(H7N9) virus infection, Shanghai, China.

A novel strain of influenza A(H7N9) virus has emerged in China and is causing mild to severe clinical symptoms in infected humans. Some case-patients have died. To further knowledge of this virus, we report the characteristics and clinical histories of 4 early case-patients.