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Dundar Yolsal O, Esme P, Karahan S, Tasci I, Caliskan E. Clues for Facial Perceived Age: Exercise, Sun Protection, Photoaging, and Anthropometric Properties: An Observational Cross-Sectional Study. Dermatol Surg 2024:00042728-990000000-00854. [PMID: 38900103 DOI: 10.1097/dss.0000000000004276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
BACKGROUND AND OBJECTIVES The effect of environmental and genetic factors on the aging process is widely acknowledged. Yet, the extent to which each factor decisively contributes to the perception of looking younger or older remains a subject of debate. This study seeks to identify the factors linked to the perceived age among Turkish women. PATIENTS AND METHODS Ten assessors scored the perceived ages of 250 female patients based on facial photographs. The study aimed to assess the impact of environmental factors and anthropometric measurements on the perception of aging. A comprehensive analysis involved conducting 9 perioral and 6 periorbital anthropometric measurements on all study participants. RESULTS Exercise (p = .001), mild photodamage (stage 1-2) (p = .001), consistent sunscreen use (p = .001), the length of the palpebral fissure (p = .043), and the height of the upper vermilion (p = .019) demonstrated significant associations with a more youthful appearance. CONCLUSION Environmental factors, including exercise, photoprotection, sunscreen use, and anthropometric measurements such as palpebral fissure length and upper vermilion height, play a significant role in contributing to a more youthful appearance.
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Affiliation(s)
- Ozlem Dundar Yolsal
- Department of Dermatology and Venereology, University of Health Sciences, Gulhane Training and Research Hospital, Ankara, Turkey
| | - Pelin Esme
- Department of Dermatology and Venereology, University of Health Sciences, Gulhane Training and Research Hospital, Ankara, Turkey
| | - Sevilay Karahan
- Department of Biostatistics, University of Hacettepe, Ankara, Turkey
| | - Ilker Tasci
- Department of Internal Medicine, University of Health Sciences, Gulhane Training and Research Hospital, Ankara, Turkey
| | - Ercan Caliskan
- Department of Dermatology and Venereology, University of Health Sciences, Gulhane Training and Research Hospital, Ankara, Turkey
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2
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Kameyama M, Umeda-Kameyama Y. Applications of artificial intelligence in dementia. Geriatr Gerontol Int 2024; 24 Suppl 1:25-30. [PMID: 37916614 DOI: 10.1111/ggi.14709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/29/2023] [Accepted: 10/04/2023] [Indexed: 11/03/2023]
Abstract
The recent evolution of artificial intelligence (AI) can be considered life-changing. In particular, there is great interest in emerging hot topics in AI such as image classification and natural language processing. Our world has been revolutionized by convolutional neural networks and transformer for image classification and natural language processing, respectively. Moreover, these techniques can be used in the field of dementia. We introduce some applications of AI systems for treating and diagnosing dementia, including image-classification AI for recognizing facial features associated with dementia, image-classification AI for classifying leukoaraiosis in MRI images, object-detection AI for detecting microbleeding in MRI images, object-detection AI for support care, natural language-processing AI for detecting dementia within conversations, and natural language-processing AI for chatbots. Such AI technologies can significantly transform the future of dementia diagnosis and treatment. Geriatr Gerontol Int 2024; 24: 25-30.
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Affiliation(s)
- Masashi Kameyama
- AI and Theoretical Image Processing, Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Yumi Umeda-Kameyama
- Dementia Center, The University of Tokyo, Tokyo, Japan
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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3
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Mekić S, Pardo LM, Gunn DA, Jacobs LC, Hamer MA, Ikram MA, Vinke EJ, Vernooij MW, Haarman AEG, Thee EF, Vergroesen JE, Klaver CCW, Croll PH, Goedegebure A, Trajanoska K, Rivadeneira F, van Meurs JBJ, Arshi B, Kavousi M, de Roos EW, Brusselle GGO, Kayser M, Nijsten T. Younger facial looks are associate with a lower likelihood of several age-related morbidities in the middle-aged to elderly. Br J Dermatol 2023; 188:390-395. [PMID: 36763776 DOI: 10.1093/bjd/ljac100] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 12/06/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND Looking older for one's chronological age is associated with a higher mortality rate. Yet it remains unclear how perceived facial age relates to morbidity and the degree to which facial ageing reflects systemic ageing of the human body. OBJECTIVES To investigate the association between ΔPA and age-related morbidities of different organ systems, where ΔPA represents the difference between perceived age (PA) and chronological age. METHODS We performed a cross-sectional analysis on data from the Rotterdam Study, a population-based cohort study in the Netherlands. High-resolution facial photographs of 2679 men and women aged 51.5-87.8 years of European descent were used to assess PA. PA was estimated and scored in 5-year categories using these photographs by a panel of men and women who were blinded for chronological age and medical history. A linear mixed model was used to generate the mean PAs. The difference between the mean PA and chronological age was calculated (ΔPA), where a higher (positive) ΔPA means that the person looks younger for their age and a lower (negative) ΔPA that the person looks older. ΔPA was tested as a continuous variable for association with ageing-related morbidities including cardiovascular, pulmonary, ophthalmological, neurocognitive, renal, skeletal and auditory morbidities in separate regression analyses, adjusted for age and sex (model 1) and additionally for body mass index, smoking and sun exposure (model 2). RESULTS We observed 5-year higher ΔPA (i.e. looking younger by 5 years for one's age) to be associated with less osteoporosis [odds ratio (OR) 0.76, 95% confidence interval (CI) 0.62-0.93], less chronic obstructive pulmonary disease (OR 0.85, 95% CI 0.77-0.95), less age-related hearing loss (model 2; B = -0.76, 95% CI -1.35 to -0.17) and fewer cataracts (OR 0.84, 95% CI 0.73-0.97), but with better global cognitive functioning (g-factor; model 2; B = 0.07, 95% CI 0.04-0.10). CONCLUSIONS PA is associated with multiple morbidities and better cognitive function, suggesting that systemic ageing and cognitive ageing are, to an extent, externally visible in the human face.
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Affiliation(s)
- Selma Mekić
- Department of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Luba M Pardo
- Department of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - David A Gunn
- Unilever Research and Development, Colworth Science Park, Sharnbrook MK44 1LQ, UK
| | - Leonie C Jacobs
- Department of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Merel A Hamer
- Department of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Eline J Vinke
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Annet E G Haarman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Eric F Thee
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Joelle E Vergroesen
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Caroline C W Klaver
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Pauline H Croll
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Andre Goedegebure
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Katerina Trajanoska
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Banafsheh Arshi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Emmely W de Roos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Guy G O Brusselle
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Respiratory Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.,Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
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4
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Avila FR, Torres-Guzman RA, Maita KC, Garcia JP, Haider CR, Ho OA, Carter RE, McLeod CJ, Bruce CJ, Forte AJ. Perceived Age as a Mortality and Comorbidity Predictor: A Systematic Review. Aesthetic Plast Surg 2023; 47:442-454. [PMID: 35650301 DOI: 10.1007/s00266-022-02932-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/01/2022] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Perceived age is defined as how old a person looks to external evaluators. It reflects the underlying biological age, which is a measure based on physical and physiological parameters reflecting a person's aging process more accurately than chronological age. People with a higher biological age have shorter lives compared to those with a lower biological age with the same chronological age. Our review aims to find whether increased perceived age is a risk factor for overall mortality risk or comorbidities. METHODS A literature search of three databases was conducted following the PRISMA guidelines for studies analyzing perceived age or isolated facial characteristics of old age and their relationship to mortality risk or comorbidity outcomes. Data on the number of patients, type and characteristics of evaluation methods, evaluator characteristics, mean chronologic age, facial characteristics studied, measured outcomes, and study results were collected. RESULTS Out of 977 studies, 15 fulfilled the inclusion criteria. These studies found an increase in mortality risk of 6-51% in older-looking people compared to controls (HR 1.06-1.51, p < 0.05). In addition, perceived age and some facial characteristics of old age were also associated with cardiovascular risk and myocardial infarction, cognitive function, bone mineral density, and chronic obstructive pulmonary disease (COPD). CONCLUSION Perceived age promises to be a clinically useful predictor of overall mortality and cardiovascular, pulmonary, cognitive, and osseous comorbidities. LEVEL OF EVIDENCE III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Affiliation(s)
- Francisco R Avila
- Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA
| | | | - Karla C Maita
- Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA
| | - John P Garcia
- Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA
| | - Clifton R Haider
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Olivia A Ho
- Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA
| | - Rickey E Carter
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | | | - Charles J Bruce
- Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL, USA
| | - Antonio J Forte
- Division of Plastic Surgery, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA.
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5
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Ieki H, Ito K, Saji M, Kawakami R, Nagatomo Y, Takada K, Kariyasu T, Machida H, Koyama S, Yoshida H, Kurosawa R, Matsunaga H, Miyazawa K, Ozaki K, Onouchi Y, Katsushika S, Matsuoka R, Shinohara H, Yamaguchi T, Kodera S, Higashikuni Y, Fujiu K, Akazawa H, Iguchi N, Isobe M, Yoshikawa T, Komuro I. Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis. COMMUNICATIONS MEDICINE 2022; 2:159. [PMID: 36494479 PMCID: PMC9734197 DOI: 10.1038/s43856-022-00220-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 11/21/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND In recent years, there has been considerable research on the use of artificial intelligence to estimate age and disease status from medical images. However, age estimation from chest X-ray (CXR) images has not been well studied and the clinical significance of estimated age has not been fully determined. METHODS To address this, we trained a deep neural network (DNN) model using more than 100,000 CXRs to estimate the patients' age solely from CXRs. We applied our DNN to CXRs of 1562 consecutive hospitalized heart failure patients, and 3586 patients admitted to the intensive care unit with cardiovascular disease. RESULTS The DNN's estimated age (X-ray age) showed a strong significant correlation with chronological age on the hold-out test data and independent test data. Elevated X-ray age is associated with worse clinical outcomes (heart failure readmission and all-cause death) for heart failure. Additionally, elevated X-ray age was associated with a worse prognosis in 3586 patients admitted to the intensive care unit with cardiovascular disease. CONCLUSIONS Our results suggest that X-ray age can serve as a useful indicator of cardiovascular abnormalities, which will help clinicians to predict, prevent and manage cardiovascular diseases.
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Affiliation(s)
- Hirotaka Ieki
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Cardiology, Sakakibara Heart Institute, Tokyo, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
| | - Mike Saji
- Department of Cardiology, Sakakibara Heart Institute, Tokyo, Japan
| | - Rei Kawakami
- Department of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo, Japan
| | - Yuji Nagatomo
- Department of Cardiology, Sakakibara Heart Institute, Tokyo, Japan
- Department of Cardiology, National Defense Medical College, Tokorozawa, Japan
| | - Kaori Takada
- Department of Radiology, Sakakibara Heart Institute, Tokyo, Japan
| | - Toshiya Kariyasu
- Department of Radiology, Sakakibara Heart Institute, Tokyo, Japan
- Department of Radiology, Tokyo Women's Medical University, Medical Center East, Tokyo, Japan
| | - Haruhiko Machida
- Department of Radiology, Sakakibara Heart Institute, Tokyo, Japan
- Department of Radiology, Tokyo Women's Medical University, Medical Center East, Tokyo, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Hiroki Yoshida
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Ryo Kurosawa
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Hiroshi Matsunaga
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kazuo Miyazawa
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kouichi Ozaki
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Division for Genomic Medicine, Medical Genome Center, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yoshihiro Onouchi
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Public Health, Chiba University Graduate School of Medicine, Chiba, Japan
| | - Susumu Katsushika
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Ryo Matsuoka
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroki Shinohara
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Toshihiro Yamaguchi
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Center for Epidemiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan
| | - Satoshi Kodera
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yasutomi Higashikuni
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Katsuhito Fujiu
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroshi Akazawa
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Nobuo Iguchi
- Department of Cardiology, Sakakibara Heart Institute, Tokyo, Japan
| | | | | | - Issei Komuro
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
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6
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Żelaźniewicz A, Nowak-Kornicka J, Osochocka A, Pawłowski B. Perceived facial age and biochemical indicators of glycemia in adult men and women. Sci Rep 2022; 12:10149. [PMID: 35710822 PMCID: PMC9203806 DOI: 10.1038/s41598-022-14555-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 06/08/2022] [Indexed: 11/21/2022] Open
Abstract
Glycemia is linked with one of the key mechanisms underlying the aging process and inter-individual differences in biological age. Previous research showed that glucose level is linked with perceived age in elder individuals. This study aimed to verify if glycemia is related to perceived facial age in healthy adult individuals as interventions in younger and healthy cohorts are crucial for preventing the onset of age-related diseases. The study sample consisted of 116 healthy men of mean age 35.53 ± 3.54 years (29.95–44.29) and 163 healthy women of mean age 28.38 ± 2.40 (24.25–34.17) years. Glycemia was evaluated by fasting glucose, insulin, HOMA-IR, and glycated hemoglobin level. BMI, facial sexual dimorphism, estradiol, testosterone, and hsCRP levels were controlled. Perceived age was evaluated based on standardized facial photos in an online survey. Additionally perceived facial aging was calculated as a difference between perceived age and chronological age. No relationship between the levels of biochemical indicators of glycemia and perceived facial age or aging was found both in men and women, also when controlled for possible confounders. This study shows that perceived facial age in adult individuals is rather linked with body adiposity of sexual dimorphism but not with glycemic markers.
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Affiliation(s)
- Agnieszka Żelaźniewicz
- Department of Human Biology, University of Wrocław, Ul. Przybyszewskiego 63, 51-148, Wrocław, Poland.
| | - Judyta Nowak-Kornicka
- Department of Human Biology, University of Wrocław, Ul. Przybyszewskiego 63, 51-148, Wrocław, Poland
| | - Adriana Osochocka
- Department of Human Biology, University of Wrocław, Ul. Przybyszewskiego 63, 51-148, Wrocław, Poland
| | - Bogusław Pawłowski
- Department of Human Biology, University of Wrocław, Ul. Przybyszewskiego 63, 51-148, Wrocław, Poland
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Umeda-Kameyama Y, Kameyama M, Tanaka T, Son BK, Kojima T, Fukasawa M, Iizuka T, Ogawa S, Iijima K, Akishita M. Screening of Alzheimer's disease by facial complexion using artificial intelligence. Aging (Albany NY) 2021; 13:1765-1772. [PMID: 33495415 PMCID: PMC7880359 DOI: 10.18632/aging.202545] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 12/10/2020] [Indexed: 11/25/2022]
Abstract
Despite the increasing incidence and high morbidity associated with dementia, a simple, non-invasive, and inexpensive method of screening for dementia is yet to be discovered. This study aimed to examine whether artificial intelligence (AI) could distinguish between the faces of people with cognitive impairment and those without dementia.121 patients with cognitive impairment and 117 cognitively sound participants were recruited for the study. 5 deep learning models with 2 optimizers were tested. The binary differentiation of dementia / non-dementia facial image was expressed as a “Face AI score”. Xception with Adam was the model that showed the best performance. Overall sensitivity, specificity, and accuracy by the Xception AI system and AUC of the ROC curve were 87.31%, 94.57%, 92.56%, and 0.9717, respectively. Close and significant correlations were found between Face AI score and MMSE (r = −0.599, p < 0.0001). Significant correlation between Face AI score and chronological age was also found (r = 0.321, p < 0.0001). However, MMSE score showed significantly stronger correlation with Face AI score than chronological age (p < 0.0001). The study showed that deep learning programs such as Xception have the ability to differentiate the faces of patients with mild dementia from that of patients without dementia, paving the way for future studies into the development of a facial biomarker for dementia.
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Affiliation(s)
- Yumi Umeda-Kameyama
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Masashi Kameyama
- Department of Diagnostic Radiology, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
| | - Tomoki Tanaka
- Institute of Gerontology, The University of Tokyo, Tokyo, Japan
| | - Bo-Kyung Son
- Institute of Gerontology, The University of Tokyo, Tokyo, Japan.,Institute for Future Initiatives, The University of Tokyo, Tokyo, Japan
| | - Taro Kojima
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Makoto Fukasawa
- Department of Nuclear Medicine, Fukujuji Hospital, Japan Anti-Tuberculosis Association, Kiyose, Japan
| | - Tomomichi Iizuka
- Center for Dementia, Fukujuji Hospital, Japan Anti-Tuberculosis Association, Kiyose, Japan
| | - Sumito Ogawa
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Katsuya Iijima
- Institute of Gerontology, The University of Tokyo, Tokyo, Japan.,Institute for Future Initiatives, The University of Tokyo, Tokyo, Japan
| | - Masahiro Akishita
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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8
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Umeda-Kameyama Y, Kameyama M, Kojima T, Ishii M, Kidana K, Yakabe M, Ishii S, Urano T, Ogawa S, Akishita M. Cognitive function has a stronger correlation with perceived age than with chronological age. Geriatr Gerontol Int 2020; 20:779-784. [PMID: 32618098 PMCID: PMC7496800 DOI: 10.1111/ggi.13972] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 05/22/2020] [Accepted: 05/31/2020] [Indexed: 11/30/2022]
Abstract
Aim The perceived age of older adults, as measured by their facial appearance, has been shown to be a robust biomarker of aging predictive of survival, telomere length and DNA methylation, and reportedly correlates with carotid atherosclerosis and bone status. This study aimed to determine whether metrics of dementia, including general cognition, vitality, depressive state and self‐supportability, have stronger correlations with perceived age than with chronological age. Methods This study included 124 patients who were admitted to the Department of Geriatric Medicine, The University of Tokyo Hospital, on account of being suspected of cognitive decline. The Mini‐Mental State Examination, Vitality Index, Geriatric Depression Scale‐15, instrumental activities of daily living and Barthel Index were carried out. Five experienced geriatricians and five experienced clinical psychologists determined the perceived age of participants based on photographs. Results The average values of the 10 raters showed excellent reliability (intraclass correlation coefficient (3, 10) = 0.941). Steiger's test revealed that perceived age showed a significantly better correlation with the Mini‐Mental State Examination (female) and Vitality Index (total, female) than did chronological age, but not with Geriatric Depression Scale‐15, instrumental activities of daily living or the Barthel Index. Conclusions Perceived age was shown to be a reliable biomarker for cognitive assessment. Geriatr Gerontol Int 2020; 20: 779–784.
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Affiliation(s)
- Yumi Umeda-Kameyama
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Masashi Kameyama
- Department of Diagnostic Radiology, Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
| | - Taro Kojima
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Masaki Ishii
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kiwami Kidana
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Department of Home Care Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Mitsutaka Yakabe
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Shinya Ishii
- Department of Medicine for Integrated Approach to Social Inclusion, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Tomohiko Urano
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Department of Geriatric Medicine, School of Medicine, International University of Health and Welfare, Narita, Japan
| | - Sumito Ogawa
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Masahiro Akishita
- Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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9
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Li S, Zhan J, Wang Y, Wang Y, He J, Huang W, Sheng Z, Liu Y. Association between renal function and bone mineral density in healthy postmenopausal Chinese women. BMC Endocr Disord 2019; 19:146. [PMID: 31878912 PMCID: PMC6933739 DOI: 10.1186/s12902-019-0476-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Accepted: 12/16/2019] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The relationship between renal function and bone mineral density (BMD) is controversial. The aim of this study was to determine the relationship of renal function with BMD and osteoporosis risk in healthy postmenopausal Chinese women. METHODS A cross-sectional study was conducted in 776 healthy postmenopausal Chinese women. Dual-energy X-ray absorptiometry was used to measure BMDs. Clinical, demographic, and biochemical data were obtained at the time of image acquisition. Estimated glomerular filtration rate (eGFR) was calculated using a Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. RESULTS Women with eGFR levels of at least 90 ml/min/1.73m2 had a lower prevalence of osteoporosis compared with women with decreased eGFR levels (60 ml/min/1.73 m2 ≤ eGFR < 90.0 ml/min/1.73 m2). BMDs at femoral neck and total hip were significantly lower in the lower eGFR class than the higher class (0.717 ± 0.106 vs 0.744 ± 0.125 g/cm2, P < 0.01; 0.796 ± 0.116 vs 0.823 ± 0.129 g/cm2, P < 0.01, respectively). eGFR was positively correlated with BMDs at femoral neck and total hip in unadjusted analysis (P < 0.05). After controlling for age, menopausal duration and body mass index (BMI), decreased eGFR was not associated with osteoporosis risk. CONCLUSIONS After adjustments for age, menopausal duration and BMI, the decline in renal function was not independently associated with osteoporosis risk in healthy postmenopausal Chinese women.
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Affiliation(s)
- Shuang Li
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Junkun Zhan
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Yanjiao Wang
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Yi Wang
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Jieyu He
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Wu Huang
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China
| | - Zhifeng Sheng
- Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, People's Republic of China
| | - Youshuo Liu
- Department of Geriatrics, Institute of Aging and Geriatrics, The Second Xiangya Hospital, Central South University, 139 Renmin Road, Changsha, Hunan, 410011, People's Republic of China.
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A variety of processes that affect the perception of skin aging. CURRENT ISSUES IN PHARMACY AND MEDICAL SCIENCES 2019. [DOI: 10.2478/cipms-2019-0027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Abstract
The purpose of this paper is to discuss the most important factors affecting perceived age. Aging is an unavoidable and irreversible process, but perceived age is a modifiable psychosocial factor. Our exterior has become one of the determinants of our social position, the key to success in our professional and personal lives. Today, we see people through their appearance, we judge after the first impression. With the help of aesthetic medicine, we can change the perceived age, but we cannot stop aging. This article discusses factors affecting the perceived age, such as hair color, skin color, general appearance and environmental factors. Many cannot be avoided, but we can make changes in life to look younger and more well-groomed. Indeed, we can change our habits for the benefit of the whole body, not only for the skin.
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Debrabant B, Soerensen M, Christiansen L, Tan Q, McGue M, Christensen K, Hjelmborg J. DNA methylation age and perceived age in elderly Danish twins. Mech Ageing Dev 2018; 169:40-44. [PMID: 28965790 PMCID: PMC6190692 DOI: 10.1016/j.mad.2017.09.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 08/18/2017] [Accepted: 09/20/2017] [Indexed: 11/27/2022]
Abstract
Perceived age is an easily accessible biomarker of aging. Here, we studied its relation to DNA methylation age (DNAm age) as introduced in (Horvath, 2013) in 180 elderly Danish twins. We found perceived age and DNAm age to be associated with chronological age (P=0.04 resp. P=2.2e-10) when correcting for gender, but did not see an association between perceived age and DNAm age (P=0.44). Intrapair-analysis showed that the proportion of pairs where the twin with the highest perceived age also had the highest DNAm age was not different from 0.5 (P=1), and we did not see a trend when dividing pairs according to their difference in perceived age (P=0.36). Hence, intrapair analysis did not reveal links between perceived age and DNAm age. Moreover, none of the 353 CpGs underlying DNAm age was individually associated with perceived age after correction for multiple-testing (P>6e-4, FDR>0.21). Finally, when constructing an epigenetic signature based on these CpGs to predict perceived age, we only found a correlation of 0.18 (95%CI: -0.06 to 0.40) and a mean square error of 13.6 years2 between observed and predicted values in the test dataset, indicating poor predictive strength. Altogether, our results suggest that perceived age and DNAm age capture different aging aspects.
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Affiliation(s)
- Birgit Debrabant
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark.
| | - Mette Soerensen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark; The Danish Twin Registry and the Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Lene Christiansen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark; The Danish Twin Registry and the Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Qihua Tan
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark; Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA; Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Kaare Christensen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark; The Danish Twin Registry and the Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jacob Hjelmborg
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark; The Danish Twin Registry and the Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark
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Boyanov M. WHOLE BODY AND REGIONAL BONE MINERAL CONTENT AND DENSITY IN WOMEN AGED 20-75 YEARS. ACTA ENDOCRINOLOGICA (BUCHAREST, ROMANIA : 2005) 2016; 12:191-196. [PMID: 31149086 PMCID: PMC6535291 DOI: 10.4183/aeb.2016.191] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Dual-energy X-ray absorptiometry (DXA) allows measurement of whole body (WB) and regional bone mineral content (BMC) and density (BMD). OBJECTIVE To measure WB and regional bone area, BMC and BMD (arms, legs, ribs and pelvis) in women of different ages. SUBJECTS AND METHODS 140 women participated (age range 20-75 yrs). Three subgroups were built: 20-44 yr (30 premenopausal women), 45-59 (80 women), and 60-75 (30 women). WB DXA was performed on a Hologic QDR 4500 A bone densitometer (Hologic Inc., Bedford MA). WB BMD T-scores were calculated by using the manufacturer-provided and the NHANES 1999-2004 reference databases, while the WB BMC Z-scores - based on the latter. Statistical analysis was performed on an IBM SPSS Statistics 19.0 for Windows platform (Chicago, IL). RESULTS WB BMC and BMD Z-scores were consistently lower than the reference databases showing a difference of about 0.4 - 0.5 SD. The arms, legs and ribs lost more BMC after the age of 50-55, while the pelvis - much earlier. The total decreases in BMC were highest in the pelvis (26.36 %), followed by the arms (16.81 %) and whole body (15.91 %), while the bone area decreased mostly in the pelvis (13.23 %). CONCLUSION The age-related declines in regional BMC, bone areas and BMD follow different patterns in appendicular and axial bones.
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Affiliation(s)
- M.A. Boyanov
- University Hospital Alexandrovska, Clinic of Endocrinology and Metabolic Diseases, Medical University of Sofia, Faculty of Medicine, Department of Internal Medicine, Sofia, Bulgaria
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