Breast MRI is the most sensitive imaging modality for detecting breast cancer. However, its widespread use is limited by factors such as extended examination times, need for contrast agents, and susceptibility to motion artifacts. Artificial intelligence (AI) has emerged as a promising solution for these challenges by enhancing the efficiency and accuracy of breast MRI in multiple domains. AI-driven image reconstruction techniques have significantly reduced scan times while preserving image quality. This method outperforms traditional parallel imaging and compressed sensing. AI has also shown great promise for lesion classification and segmentation, with convolutional neural networks and U-Net architectures improving the differentiation between benign and malignant lesions. AI-based segmentation methods enable accurate tumor detection and characterization, thereby aiding personalized treatment planning. An AI triaging system has demonstrated the potential to streamline workflow efficiency by identifying low-suspicion cases and reducing the workload of radiologists. Another promising application is synthetic breast MR image generation, which aims to generate contrast enhanced images from non-contrast sequences, thereby improving accessibility and patient safety. Further research is required to validate AI models across diverse populations and imaging protocols. As AI continues to evolve, it is expected to play an important role in the optimization of breast MRI.

Breast MRI is the most sensitive imaging modality for detecting breast cancer. However, its widespread use is limited by factors such as extended examination times, need for contrast agents, and susceptibility to motion artifacts. Artificial intelligence (AI) has emerged as a promising solution for these challenges by enhancing the efficiency and accuracy of breast MRI in multiple domains. AI-driven image reconstruction techniques have significantly reduced scan times while preserving image quality. This method outperforms traditional parallel imaging and compressed sensing. AI has also shown great promise for lesion classification and segmentation, with convolutional neural networks and U-Net architectures improving the differentiation between benign and malignant lesions. AI-based segmentation methods enable accurate tumor detection and characterization, thereby aiding personalized treatment planning. An AI triaging system has demonstrated the potential to streamline workflow efficiency by identifying low-suspicion cases and reducing the workload of radiologists. Another promising application is synthetic breast MR image generation, which aims to generate contrast enhanced images from non-contrast sequences, thereby improving accessibility and patient safety. Further research is required to validate AI models across diverse populations and imaging protocols. As AI continues to evolve, it is expected to play an important role in the optimization of breast MRI.

Breast MRI is the most sensitive imaging modality for detecting breast cancer. However, its widespread use is limited by factors such as extended examination times, need for contrast agents, and susceptibility to motion artifacts. Artificial intelligence (AI) has emerged as a promising solution for these challenges by enhancing the efficiency and accuracy of breast MRI in multiple domains. AI-driven image reconstruction techniques have significantly reduced scan times while preserving image quality. This method outperforms traditional parallel imaging and compressed sensing. AI has also shown great promise for lesion classification and segmentation, with convolutional neural networks and U-Net architectures improving the differentiation between benign and malignant lesions. AI-based segmentation methods enable accurate tumor detection and characterization, thereby aiding personalized treatment planning. An AI triaging system has demonstrated the potential to streamline workflow efficiency by identifying low-suspicion cases and reducing the workload of radiologists. Another promising application is synthetic breast MR image generation, which aims to generate contrast enhanced images from non-contrast sequences, thereby improving accessibility and patient safety. Further research is required to validate AI models across diverse populations and imaging protocols. As AI continues to evolve, it is expected to play an important role in the optimization of breast MRI.

Thyrotoxicosis (thyroid crisis) is a known cause of sudden death; however, only a few cases of death resulting from thyrotoxicosis have been reported. Histopathologic examination and postmortem thyroid function tests may be helpful in postmortem diagnosis, but their usefulness seems to be limited. We report three autopsy cases associated with thyrotoxicosis.
Autopsy ; Death, Sudden ; Thyroid Crisis ; Thyroid Function Tests ; Thyrotoxicosis

BACKGROUND: The EuroQol-5 Dimension (EQ-5D) is the most frequently used questionnaire in cost-utility studies such as the quality-adjusted life year measure. Nevertheless, little attention has been paid to the relationship between an individual's visual analogue scale (VAS) score and EQ-5D dimensions. The objective of this study was to assess the relationship between the EQ-5D and VAS quality of life measures after adjusting for socio-demographic factors in the Korean general population. METHODS: The Fourth Korea National Health and Nutrition Examination Survey, which is a national representative sample, was used to analyze the impact of the EQ-5D dimensions on the VAS. The known-group construct validity of the VAS was assessed by factors that included age, income and comorbidities. The ordinary linear regression models were applied to test for the effect of the EQ-5D dimensions after adjusting for socio-demographic and clinical factors. RESULTS: We found that the VAS showed good construct validity. The VAS significantly declined as age increased, and as education and income levels decreased. VAS scores decreased for all EQ-5D dimensions as the response level rose. The explanatory power of the VAS increased from 23.0% in the first model, which included only the EQ-5D dimensions and levels, to 25.0% in the full model, which included socio-demographic and clinical factors. CONCLUSIONS: While the EQ-5D dimensions were significant factors in determining the VAS, they did not, however, explain a sufficient amount of variance in the VAS. Further research is required on adding more dimensions to the EQ-5D preference-based instrument.
Comorbidity ; Korea ; Linear Models ; Nutrition Surveys ; Quality of Life ; Quality-Adjusted Life Years

No abstract available.
Female* ; Hepatitis* ; Humans ; Infant* ; Measles*

No abstract available.
Education* ; Humans ; Male*

The basic technique for total reconstruction of the microtia was established by Tanzer, who utilized autologous rib cartilages for constructing the auricular framework. In order to decrease the number of surgical stages and to achieve maximal convolution, we employed a surgical procedure with simultaneous three layered costal cartilage grafting for the high profiled auricle, concha formation and lobule rotation. However, we performed ear elevation as an additional procedure for some patients who had decreased helical height due to absorption of cartilage framework or postoperative trauma and who had wanted to wear the spectacles or to have more natural appearance of auriculocephalic sulcus. From August 1988 to October 1997 we had performed surgeries for the ear elevation of 58 patients in 177 patients with total ear reconstruction, using various elevation methods; skin graft, local flap, and local with costal cartilage block. When the ear elevation was performed with skin graft, postoperative contraction of the grafted skin was inevitable. In cases with two skin flaps, it was difficult to stabilize and maintain the correct projection of the constructed ear. So we elevated the reconstructed ear by utilizing a costal cartilage block, two skin flaps to cover the posterior region and skin graft. We conclude that the local flap with costal cartilage block is one of the most favorable methods in ear elevation which can maintain the adequate projection and make natural looking auriculocephalic sulcus.
Absorption ; Cartilage ; Ear* ; Eyeglasses ; Humans ; Ribs ; Skin ; Transplants

OBJECTIVE: To evaluate the effects of heel-opened ankle foot orthosis (HOAFO) on hemiparetic gait after stroke, especially on external foot rotation, and to compare the effects of HOAFO with conventional plastic-AFO (pAFO) and barefoot during gait. METHODS: This cross-over observational study involved 15 hemiparetic patients with external rotation of the affected foot. All subjects were able to walk independently, regardless of their usual use of a single cane, and had a less than fair-grade in ankle dorsiflexion power. Each patient was asked to walk in three conditions with randomized sequences: 1) barefoot, 2) with a pAFO, and 3) with an HOAFO. Their gait patterns were analyzed using a motion analysis system. RESULTS: Fifteen patients consisted of nine males and six females. On gait analysis, hip and foot external rotation were significantly greater in pAFO (-3.35degrees and -23.68degrees) than in barefoot and HOAFO conditions (p<0.05). Wearing an HOAFO resulted in significant decreases in hip (0.78degrees, p=0.04) and foot (-17.99degrees, p<0.01) external rotation compared with pAFO; although there was no significant difference between HOAFO and barefoot walking. Walking speed and percentage of single limb support were significantly greater for HOAFO than in barefoot walking. CONCLUSION: HOAFO was superior to pAFO in reducing hip and foot external rotation during the stance phase in patients with post-stroke hemiparesis. HOAFO may, therefore, be useful in patients with excessive external rotation of the foot during conventional pAFO.
Animals ; Ankle ; Canes ; Extremities ; Female ; Foot ; Foot Orthoses ; Foot Rot ; Gait ; Hip ; Humans ; Male ; Orthotic Devices ; Paresis ; Stroke ; Walking

No abstract available.
Rhinoplasty*