Notes

Aftereffect of perioperative ache neuroscience schooling in patients with post-mastectomy continual pain: a retrospective, inclination score-matched review.
lternative to IL in reducing pain during thoracentesis and abdominocentesis, but it seemed to increase unsuccessful medical procedure attempts.
To assist doctors to diagnose mild cognitive impairment (MCI) and Alzheimer's disease (AD) early and accurately, convolutional neural networks based on structural magnetic resonance imaging (sMRI) images have been developed and shown excellent performance. However, they are still limited in their capacity in extracting discriminative features because of large sMRI image volumes yet small lesion regions and the small number of sMRI images.

We proposed a task-driven hierarchical attention network (THAN) taking advantage of the merits of patch-based and attention-based convolutional neural networks for MCI and AD diagnosis. THAN consists of an information sub-network and a hierarchical attention sub-network. In the information sub-network, an information map extractor, a patch-assistant module, and a mutual-boosting loss function are designed to generate a task-driven information map, which automatically highlights disease-related regions and their importance for final classification. In the hierarchical atth the two sub-networks, THAN fully exploits the visual and semantic features of disease-related regions and meanwhile considers global features of sMRI images, which finally facilitate the diagnosis of MCI and AD.
The information sub-network can automatically highlight the disease-related regions. The hierarchical attention sub-network can extract discriminative visual and semantic features. Through the two sub-networks, THAN fully exploits the visual and semantic features of disease-related regions and meanwhile considers global features of sMRI images, which finally facilitate the diagnosis of MCI and AD.
We aimed to investigate the relationship between baseline clinical characteristics and postprocedural myocardial perfusion as determined by dynamic computed tomography myocardial perfusion imaging (CT-MPI).

We retrospectively included consecutive symptomatic post percutaneous coronary intervention (PCI) patients, who underwent dynamic CT-MPI + coronary CT angiography (CCTA) and who were revealed to have patent stents on previously revascularized lesions. Myocardial blood flow (MBF) was measured for stented territories and reference territories. Various baseline clinical and angiographic parameters were tested for the association with reduced MBF of stented territories.

A total of 81 patients with 96 stented vessels were included in the analysis. The mean effective doses of radiation for the whole integrated CT protocol (calcium score + dynamic CT-MPI + CCTA) was 4.89±1.14 (2.58-6.93) mSv. Overall, 49 stented vessels had reduced MBF (75.3±17.2 mL/100 mL/min) within related territories, whereas 47 stentedrevascularization, followed by AMI, stenotic extent, and NT-pro-BNP.
Whether to prophylactically irradiate the ipsilateral internal mammary chain (IMC) in post-mastectomy radiotherapy (PMRT) remains controversial because of equivocal clinical benefits against the added toxicities. Our previous study revealed that the cardiac dose was decreased during left-sided breast radiotherapy with abdominal deep inspiration breath-hold (aDIBH) as compared with free-breathing (FB) and thoracic deep inspiration breath-hold (tDIBH). find more Here we present the dosimetric advantage of aDIBH for patients undergoing PMRT with IMC coverage.

We prospectively analyzed 19 patients with left-sided breast cancer who underwent PMRT. Patients underwent computed tomography (CT) simulation under both free-breathing (FB) and aDIBH. The heart, left anterior descending coronary artery (LAD), lungs, and the contralateral breast was defined as organs at risk (OARs). Three-dimensional conformal radiation therapy (3D-CRT), inverse planning intensity-modulated radiation therapy (IMRT), and volumetric modulated arc tIBH technique be routinely applied in suitable patients if the IMC is irradiated.
Using an immobilization-assisted aDIBH technique, radiation doses to the heart can be kept at reasonably low levels even if IMC is included in the clinical target volume (CTV). Among 3D-CRT, IMRT, and VMAT plans, IMRT plus aDIBH results in the best heart-sparing effect. We recommend that the aDIBH technique be routinely applied in suitable patients if the IMC is irradiated.
Biplanar X-ray system providing anteroposterior and sagittal plane with an ultra-low radiation dose and in weight-bearing position is increasingly used for spine imaging. The original three-dimensional (3D) reconstruction method from biplanar X-rays has been widely used for clinical parameters, however, the main issue is that manual adjustments of the 3D model was quite time-consuming and limited to thoracolumbar spine. A quasi-automated 3D reconstruction method of the spine from cervical vertebra to pelvis was proposed, which proved fast and accurate in 57 patients with adolescent idiopathic scoliosis. The aim of this study was to compare the newly developed technique of quasi-automatic 3D measurement with classical 2D measurements in a large cohort.

A total of 494 adults with biplanar EOS X-ray scanning were included in this study and divided into health and deformity group according to the presence of spinal deformity. The proposed method of quasi-automatic 3D measurement was applied to all these subjeorrelation analysis showed r2 for all clinical parameters ranged from 0.667 to 0.923. On average, the new method takes 5 minutes to compute all the parameters for one case.

In conclusion, this ergonomic and efficient quasi-automatic method for full spine proved fast and accurate measurement in a large population, which showed great potential in extensive clinical application.
In conclusion, this ergonomic and efficient quasi-automatic method for full spine proved fast and accurate measurement in a large population, which showed great potential in extensive clinical application.
Accurate segmentation of pulmonary nodules on computed tomography (CT) scans plays a crucial role in the evaluation and management of patients with suspicion of lung cancer (LC). When performed manually, not only the process requires highly skilled operators, but is also tiresome and time-consuming. To assist the physician in this task several automated and semi-automated methods have been proposed in the literature. In recent years, in particular, the appearance of deep learning has brought about major advances in the field.

Twenty-four (12 conventional and 12 based on deep learning) semi-automated-'one-click'-methods for segmenting pulmonary nodules on CT were evaluated in this study. The experiments were carried out on two datasets a proprietary one (383 images from a cohort of 111 patients) and a public one (259 images from a cohort of 100). All the patients had a positive transcript for suspect pulmonary nodules.

The methods based on deep learning clearly outperformed the conventional ones. The best performance [Sørensen-Dice coefficient (DSC)] in the two datasets was, respectively, 0.
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