다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Background: Thyroid nodules are a common clinical problem, and differentiated thyroid cancer is becoming increasingly prevalent. Since the American Thyroid Association's (ATA's) guidelines for the management of these disorders were revised in 2009, significant scientific advances have occurred in the field. The aim of these guidelines is to inform clinicians, patients, researchers, and health policy makers on published evidence relating to the diagnosis and management of thyroid nodules and differentiated thyroid cancer. Methods: The specific clinical questions addressed in these guidelines were based on prior versions of the guidelines, stakeholder input, and input of task force members. Task force panel members were educated on knowledge synthesis methods, including electronic database searching, review and selection of relevant citations, and critical appraisal of selected studies. Published English language articles on adults were eligible for inclusion. The American College of Physicians Guideline Gr...

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2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer.

As we enter the twenty-first century, research at the interface of polymer chemistry and the biomedical sciences has given rise to the first nano-sized (5-100 nm) polymer-based pharmaceuticals, the 'polymer therapeutics'. Polymer therapeutics include rationally designed macromolecular drugs, polymer-drug and polymer-protein conjugates, polymeric micelles containing covalently bound drug, and polyplexes for DNA delivery. The successful clinical application of polymer-protein conjugates, and promising clinical results arising from trials with polymer-anticancer-drug conjugates, bode well for the future design and development of the ever more sophisticated bio-nanotechnologies that are needed to realize the full potential of the post-genomic age.

The dawning era of polymer therapeutics

Dendrimers in biomedical applications--reflections on the field.

结节病易误诊,据王洪武等~([1])收集国内18篇关于此病误诊的文献,误诊率高达63.2%,当然有误诊就会有误治,如孙永昌等~([2])报道26例结节病在影像学检查诊断的第一印象中拟诊结核5例,其中就有2例完成规范的抗结核治疗,为此应引起临床对本病诊治的重视。

Sarcoidosis

Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology. CNN is designed to automatically and adaptively learn spatial hierarchies of features through backpropagation by using multiple building blocks, such as convolution layers, pooling layers, and fully connected layers. This review article offers a perspective on the basic concepts of CNN and its application to various radiological tasks, and discusses its challenges and future directions in the field of radiology. Two challenges in applying CNN to radiological tasks, small dataset and overfitting, will also be covered in this article, as well as techniques to minimize them. Being familiar with the concepts and advantages, as well as limitations, of CNN is essential to leverage its potential in diagnostic radiology, with the goal of augmenting the performance of radiologists and improving patient care. • Convolutional neural network is a class of deep learning methods which has become dominant in various computer vision tasks and is attracting interest across a variety of domains, including radiology.
 • Convolutional neural network is composed of multiple building blocks, such as convolution layers, pooling layers, and fully connected layers, and is designed to automatically and adaptively learn spatial hierarchies of features through a backpropagation algorithm.
 • Familiarity with the concepts and advantages, as well as limitations, of convolutional neural network is essential to leverage its potential to improve radiologist performance and, eventually, patient care.

/pdf/convolutional-neural-networks-an-overview-and-application-in-2y7aips4x7.pdf

Convolutional neural networks: an overview and application in radiology

PURPOSE: To prospectively evaluate the elastographic appearance of thyroid gland tumors and explore the potential sensitivity and specificity of ultrasonographic (US) elastography for differentiating benign and malignant tumors, with histopathologic analysis as the reference standard. MATERIALS AND METHODS: The study was institutional review board approved, and each patient gave written informed consent. Fifty-two thyroid gland lesions (22 malignant, 30 benign) in 31 consecutive patients (six men, 25 women; mean age, 49.7 years ± 14.7 [standard deviation]) were examined with real-time elastography in the elasticity imaging mode implemented on a clinical US scanner modified for research. In addition, the radiofrequency echo data stored during US were exported from the scanner and used for off-line strain image reconstruction. All elastograms were evaluated for the lesion visibility, relative brightness, and margin regularity and definition by using a four-point scale. In addition, normal thyroid gland tiss...

/pdf/thyroid-gland-tumor-diagnosis-at-us-elastography-394vox75zp.pdf

Thyroid gland tumor diagnosis at US elastography

The value of 1.5-T magnetic resonance (MR) imaging in diagnosing endometrial cysts and differentiating them from other gynecologic masses was prospectively evaluated in 374 female patients with clinically suspected adnexal masses. A suggestive diagnosis of endometrial cyst was made when a cyst that was hyperintense on T1-weighted images exhibited homogeneous hyperintensity on T2-weighted images. A definitive diagnosis was made when a cyst that was hyperintense on T1-weighted images exhibited hypointense signal on T2-weighted images (shading) or when the lesion consisted of multiple hyperintense cysts on T1-weighted images (multiplicity) regardless of the signal intensity on T2-weighted images. Surgery was performed in 293 patients, and confirmation was obtained in 354 lesions. MR imaging enabled accurate diagnosis of 77 of 86 endometrial cysts and exclusion of the diagnosis of endometrial cyst in 263 of 268 other gynecologic masses with or without internal hemorrhage. The overall diagnostic sensitivity, specificity, and accuracy were 90%, 98%, 96%, respectively. MR imaging seems to be an acceptable diagnostic test on which clinical decisions can be based in selecting treatment.

Endometrial cysts: diagnosis with MR imaging.

Sarcoidosis is a systemic disorder of unknown cause with a wide variety of clinical and radiologic manifestations. The diagnosis is usually made on the basis of these manifestations supported by histologic findings. Systemic manifestations (eg, Lofgren syndrome, Heerfordt syndrome) are commonly seen at clinical examination. Bilateral hilar lymphadenopathy is the most common radiologic finding—frequently with associated pulmonary infiltrates—and typically has a characteristic perivascular distribution at high-resolution chest computed tomography. Radiologic findings in the short tubular bones of the hands and feet and magnetic resonance imaging findings of nodular involvement of muscle are often sufficient to raise suspicion for sarcoidosis. In the liver, spleen, kidneys, and scrotum, coalescing granulomas form nodules whose imaging features may occasionally be nonspecific, although familiarity with the relevant clinical settings will be helpful in recognizing the presence of sarcoidosis. Radiologic recogn...

Radiologic Manifestations of Sarcoidosis in Various Organs

Typical appearances of uterine leiomyoma at magnetic resonance (MR) imaging are well established, and diagnosis is usually easy. However, cases that are extremely difficult to differentiate from ot...

Kaori Togashi

Papers

Convolutional neural networks: an overview and application in radiology

Thyroid gland tumor diagnosis at US elastography

Endometrial cysts: diagnosis with MR imaging.

Radiologic Manifestations of Sarcoidosis in Various Organs

Unusual appearances of uterine leiomyomas: MR imaging findings and their histopathologic backgrounds.