[Environmental risks to housing and living arrangements among older survivors of the Great East Japan Earthquake and their relationships with housing type: The RIAS Study].

Objective　Over the course of their lives, people spend most of their time in the home environment. The Community-based Integrated Care System 2018 by the Ministry of Health, Labour and Welfare in Japan declared the importance of "housing" and "living arrangements" as essential elements to enable older adults to live independently and to protect their privacy and dignity in their communities. The present study aims to clarify the relationship between current housing type and "housing" and "living arrangements" among older survivors of the Great East Japan Earthquake (GEJE).Methods　We used data obtained from 3,856 participants, aged 65 years or older, in the Research project for prospective Investigation of health problems Among Survivors of the GEJE (RIAS). Housing types were categorized as follows: "same housing," "temporary housing," "disaster public housing," "new housing" (in a different area), and "others." Healthy housing scores were calculated using a housing health checklist from the Nationwide Smart Wellness Housing Survey in Japan. "Living arrangements" were assessed based on residential status, social network, and social capital. To determine the risks associated with each "housing" and "living arrangement" category, we used multivariate logistic and linear regression models.Results　The number of participants in each housing type was as follows: 2,531 in "same housing," 146 in "temporary housing," 234 in "disaster public housing," 844 in "new housing," and 101 in "others." Compared with those living in "same housing," those living in "disaster public housing," "new housing," and "others" had a significantly higher healthy housing score, whereas those living in "temporary housing" had a lower score. However, with regards to "living arrangements," the number of residents who were living alone was significantly higher among those in "disaster public housing," and those living in "disaster public housing" as well as "new housing" had low social capital compared with those living in "same housing." The likelihood of having a poor social network was substantially higher for those living in "disaster public housing." Sub-scale analyses indicated that "disaster public housing" was associated with less family support, whereas "new housing" was associated with less support from friends.Conclusion　The present results indicate that older survivors-regardless of whether they live in the existing community-find it challenging to establish new social capital and social networks in a new location without the presence of "someone" they knew before the disaster.

A new metal artifact reduction algorithm based on a deteriorated CT image.

BACKGROUND: Computed tomography (CT) is an established imaging technology primarily used as a non-invasive diagnostic tool that reconstructs axial images. However, significant problems with metal artifacts remain. A metal artifact is a strong radial noise in an image, which makes it difficult to diagnose patients and inspect products containing metal implants. Historically, studies related to metal artifact reduction used projection data, though the data is not typically saved after processing. OBJECTIVE: This study proposes a new metal artifact reduction algorithm that does not require projection data, for new applications and for accurate diagnostic techniques. METHODS: The algorithm utilizes reconstructed images and is based on iterative reconstruction. By reproducing an accurate forward projection on simulation and combining it with an iterative calculation, discrepancies causing metal artifacts are eliminated. RESULTS: Validation was completed with numerical phantom models. Our results indicate that the proposed algorithm effectively reduces metal artifacts, even if numerous complex-shaped metal pieces were embedded in the cross-section. CONCLUSIONS: We developed a novel reconstruction algorithm for metal artifact reduction in CT imaging that only requires reconstructed images and projection conditions. Any historical CT data containing metal artifacts could be improved with this method.