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    ํ•œ๊ตญ์˜ ๋นˆ๊ณค๋™ํƒœ, ์˜๋ฃŒ์ด์šฉ๊ณผ ์˜๋ฃŒ๋น„

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๋ณด๊ฑด๋Œ€ํ•™์› ๋ณด๊ฑดํ•™๊ณผ(๋ณด๊ฑด์ •์ฑ…๊ด€๋ฆฌํ•™์ „๊ณต),2019. 8. ๊ถŒ์ˆœ๋งŒ.๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์˜ ๋นˆ๊ณค๋™ํƒœ์™€ ์˜๋ฃŒ๊ธ‰์—ฌ์˜ ์ˆ˜๊ธ‰์ง€์œ„๋ณ€ํ™”๊ฐ€ ์˜๋ฃŒ์ด์šฉ, ์˜๋ฃŒ๋น„์™€ ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•ด ํ•œ๊ตญ์˜๋ฃŒํŒจ๋„ 2008-2014๋…„ ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ 2011-2013๋…„์— ๋Œ€ํ•œ ๋ถ„์„์„ ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ค‘์œ„์†Œ๋“ 50% ๋ฏธ๋งŒ์˜ ๋นˆ๊ณค์„  ์•„๋ž˜์˜ ๋นˆ๊ณค์ธต์—์„œ, ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„๊ฐ€ ์ฒซ ๋ฒˆ์งธ ๋นˆ๊ณค์ฃผ๊ธฐ์˜ ๊ธธ์ด์™€ ์ด ๋นˆ๊ณค๊ธฐ๊ฐ„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•ด์„œ ํ•œ๊ตญ๋ณต์ง€ํŒจ๋„ 2008-2016๋…„ ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ค‘์œ„์†Œ๋“ 40% ๋ฏธ๋งŒ์˜ ๋นˆ๊ณค์„  ์•„๋ž˜์˜ ๋นˆ๊ณค์ธต์—์„œ, ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„๊ฐ€ ๋นˆ๊ณคํƒˆ์ถœ (ํ˜น์€ ๋นˆ๊ณค์ง€์†)์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•ด์„œ ํ•œ๊ตญ๋ณต์ง€ํŒจ๋„ 2008-2016๋…„ ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ด์‚ฐ์‹œ๊ฐ„ ์‚ฌ๊ฑด์‚ฌ ๋ถ„์„์„ ํ†ตํ•ด ๋ถ„์„์„ ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋นˆ๊ณค๋™ํƒœ๊ฐ€ ์˜๋ฃŒ์ด์šฉ, ์˜๋ฃŒ๋น„์™€ ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํƒ์ƒ‰ํ•œ ์ฒซ ๋ฒˆ์งธ ์‹œ๋„๋ผ๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ, ์ง€์†์  ๋นˆ๊ณค์ธต(the persistent poor)์€ ์‘๊ธ‰์‹ค ๋ฐฉ๋ฌธ๊ณผ ์ž…์›ํšŸ์ˆ˜์— ์–ด๋ ค์›€์ด ์žˆ์—ˆ๊ณ , ์˜๋ฃŒ๋น„๋ฅผ ๋‚ฎ๊ฒŒ ์ง€์ถœํ•˜์˜€๊ณ , ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ๋ฅผ ๋” ๋งŽ์ด ๋ณด๊ณ ํ•˜์˜€๋‹ค. ๋ฐ˜๋ณต์  ๋นˆ๊ณค์ธต(the recurrent poor)์€ ์ž…์›ํšŸ์ˆ˜๊ฐ€ ๋” ์ ์—ˆ๊ณ , ์˜๋ฃŒ๋น„๋ฅผ ๋œ ์ง€์ถœํ•˜์˜€๊ณ , ๊ฐ€์žฅ ๋†’์€ ์ˆ˜์ค€์˜ ๊ฒฝ์ œ์  ์ด์œ ๋กœ ์ธํ•œ ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ๋ฅผ ํ˜ธ์†Œํ•˜์˜€๋‹ค. ๊ฑด๊ฐ•์œ ์ง€์™€ ๊ฐœ์ธ์˜ ์•ˆ๋…•์—์„œ ์งˆ๋ณ‘์ด ๋ฐœ์ƒํ•˜์˜€์„ ๋•Œ ์ ์ ˆํ•œ ๋•Œ์— ์ ์ ˆํ•œ ์˜๋ฃŒ์ด์šฉ์„ ํ•˜๋Š” ๊ฒƒ์˜ ์ค‘์š”์„ฑ์„ ์ƒ๊ฐํ•ด๋ณผ ๋•Œ, ์ง€์†์  ๋นˆ๊ณค์ธต๊ณผ ๋ฐ˜๋ณต์  ๋นˆ๊ณค์ธต์€ ๊ฑด๊ฐ•์ƒํƒœ์™€ ์•ˆ๋…•์ด ๋‚˜๋น ์งˆ ์œ„ํ—˜์— ์ฒ˜ํ•ด ์žˆ๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๊ฒ ๋‹ค. ๋˜ํ•œ ์˜๋ฃŒ๊ธ‰์—ฌ์˜ ์ˆ˜๊ธ‰์ง€์œ„์˜ ๋ณ€ํ™”๊ฐ€ ์˜๋ฃŒ์ด์šฉ, ์˜๋ฃŒ๋น„, ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์‚ดํŽด๋ณด๋ฉด, ์ง€์†์  ์˜๋ฃŒ๊ธ‰์—ฌ์ง‘๋‹จ์€ ๋” ๋งŽ์€ ์™ธ๋ž˜์ด์šฉ, ๋” ์ ์€ ๊ฑด๊ฐ•๊ฒ€์ง„์„œ๋น„์Šค ์ด์šฉ, ๋” ๋งŽ์€ ์‘๊ธ‰์˜๋ฃŒ ์ด์šฉ๊ณผ ์ž…์›์ด์šฉ์„ ํ•˜์˜€๊ณ , ์˜๋ฃŒ๋น„๋ฅผ ๋œ ์ง€์ถœํ•˜์˜€์œผ๋‚˜ ๋” ๋งŽ์€ ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ๋ฅผ ๋ณด๊ณ ํ•˜์˜€๋‹ค. ์‹ ๊ทœ ์˜๋ฃŒ๊ธ‰์—ฌ ์ง‘๋‹จ์€ ๋ณธ์ธ๋ถ€๋‹ด๊ธˆ์ด ๋‚ฎ์•„์ง€๋ฉด์„œ ๋” ๋งŽ์€ ๊ธ‰์—ฌํ˜œํƒ์„ ๋ฐ›๊ฒŒ ๋˜์–ด ๋” ๋งŽ์€ ์™ธ๋ž˜์ด์šฉ์„ ํ•˜๊ณ  ์žฌ์›์ผ์ˆ˜๊ฐ€ ๊ธธ์—ˆ๋‹ค. ์‹ ๊ทœ ๊ฑด๊ฐ•๋ณดํ—˜ ์ง‘๋‹จ์€ ๋ณธ์ธ๋ถ€๋‹ด๊ธˆ์ด ๋†’์•„์ง€๋ฉด์„œ ๊ธ‰์—ฌํ˜œํƒ์ด ์ค„์–ด๋“œ๋Š” ์ƒํ™ฉ์ด ๋˜๋Š”๋ฐ, ์ž…์›์ด์šฉ์„ ์ค„์ด๋Š” ์–‘์ƒ์„ ๋ณด์˜€๊ณ , ๋†’์€ ๋ฏธ์ถฉ์กฑ ์˜๋ฃŒ ์ˆ˜์ค€์„ ๋ณด๊ณ ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„๊ฐ€ ์ฒซ ๋ฒˆ์งธ ๋นˆ๊ณค์ฃผ๊ธฐ์˜ ๊ธธ์ด์™€ ์ด ๋นˆ๊ณค๊ธฐ๊ฐ„, ๊ทธ๋ฆฌ๊ณ  ๋นˆ๊ณคํƒˆ์ถœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ฒ˜์Œ์œผ๋กœ ๋ถ„์„ํ•œ ๊ฒƒ์— ์˜์˜๋ฅผ ๊ฐ€์ง„๋‹ค. ๋‹ค๋ฅธ ๋นˆ๊ณค๊ธฐ๊ฐ„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์š”์ธ๋“ค์„ ํ†ต์ œํ•œ ์ƒํƒœ์—์„œ๋„, ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„๊ฐ€ ๋ฐœ์ƒํ•œ ๊ฐ€๊ตฌ๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ์ฒซ ๋ฒˆ์งธ ๋นˆ๊ณค์ฃผ๊ธฐ(30-40%์˜ ์—ญ์น˜ ์ˆ˜์ค€)์™€ ์ด ๋นˆ๊ณค๊ธฐ๊ฐ„(30%์˜ ์—ญ์น˜ ์ˆ˜์ค€)์ด ๊ธธ์–ด์กŒ๋‹ค. ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„์˜ ์ด ๋นˆ๊ณค๊ธฐ๊ฐ„์— ๋Œ€ํ•œ ์˜ํ–ฅ์˜ ํฌ๊ธฐ๋Š” ์ฒซ ๋ฒˆ์งธ ๋นˆ๊ณค์ฃผ๊ธฐ์˜ ๊ธธ์ด์— ๋Œ€ํ•œ ์˜ํ–ฅ๋ณด๋‹ค ๋‹ค์†Œ ์ค„์–ด๋“ค์—ˆ๋Š”๋ฐ, ์ด๋Š” ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„์˜ ์˜ํ–ฅ์ด ์ฒซ ๋ฒˆ์งธ ๋นˆ๊ณค์ฃผ๊ธฐ์˜ ๊ธธ์ด์—์„œ ๋” ์ค‘์š”ํ•˜๊ฒŒ ์ž‘์šฉํ•จ์„ ์˜๋ฏธํ•œ๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„๊ฐ€ ๋นˆ๊ณคํƒˆ์ถœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์€ ๋นˆ๊ณคํƒˆ์ถœ ์œ ํ˜•๋ณ„๋กœ ๋‹ค๋ฅด๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ฐจ์ƒ์œ„ ๋นˆ๊ณค์ธต์œผ๋กœ ํƒˆ์ถœ๊ณผ ์™„์ „ ๋นˆ๊ณคํƒˆ์ถœ๋กœ ๋‚˜๋ˆ„์–ด ๋นˆ๊ณคํƒˆ์ถœ์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„์˜ ๋ฐœ์ƒ์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ์ฐจ์ƒ์œ„ ๋นˆ๊ณค์ธต์œผ๋กœ ํƒˆ์ถœ๊ณผ ๋ถ€์  ์ƒ๊ด€์ด ์žˆ์—ˆ์œผ๋‚˜, ์™„์ „ ๋นˆ๊ณคํƒˆ์ถœ์—์„œ๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค. ๋นˆ๊ณคํƒˆ์ถœ์˜ ๋Œ€๋ถ€๋ถ„(70%)์ด ์ฐจ์ƒ์œ„ ๋นˆ๊ณค์ธต์œผ๋กœ์˜ ์ด๋™์ž„์„ ๊ณ ๋ คํ•  ๋•Œ, ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„์˜ ๋ฐœ์ƒ์€ ์ด๋ฏธ ์ œํ•œ์ ์ธ ๋นˆ๊ณค์ธต์˜ ๊ฐ€๊ณ„์˜ˆ์‚ฐ์— ์œ„ํ˜‘์„ ์ฃผ๋ฉฐ, ๊ฐ€๊ณ„์˜ ์†Œ๋“๊ฐ์†Œ์™€ ๋”๋ถˆ์–ด ๋นˆ๊ณค์ง€์†์˜ ์š”์ธ์ž„์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์˜๋ฃŒ์ด์šฉ์˜ ์ ‘๊ทผ์„ฑ ํ–ฅ์ƒ๊ณผ ์˜๋ฃŒ๋น„๋กœ ์ธํ•œ ์žฌ์ •์  ์œ„ํ—˜์— ๋Œ€ํ•œ ๋ณดํ˜ธ๋ฅผ ์ด๋ฃจ๊ธฐ ์œ„ํ•œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์ ‘๊ทผ์€ ๊ธ‰์—ฌํ•ญ๋ชฉ์„ ํ™•๋Œ€ํ•˜๊ณ  ๋ณธ์ธ๋ถ€๋‹ด๊ธˆ์„ ๋‚ฎ์ถ”๋Š” ์„ ์ง€๋ถˆ์ฒด๊ณ„๋ฅผ ๋ฐœ์ „์‹œํ‚ค๋Š” ๊ฒƒ์ด๋‹ค. ๋‹ค๋ฅธ ๋ถ„์•ผ์˜ ๋นˆ๊ณค๊ฐ์†Œ ์ •์ฑ…๋“ค๊ณผ ๋”๋ถˆ์–ด, ๊ฑด๊ฐ•๋ณด์žฅ์ œ๋„๋ฅผ ๊ฐ•ํ™”ํ•˜์—ฌ ์žฌ๋‚œ์  ์˜๋ฃŒ๋น„ ๋ฐœ์ƒ์„ ์ค„์ด๋Š” ๊ฒƒ์€ ๋นˆ๊ณค์„ ๊ฐ์†Œ์‹œํ‚ค๊ณ  ๊ตญ๋ฏผ์˜ ์•ˆ๋…•์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ์‹คํ˜„๊ฐ€๋Šฅํ•˜๊ณ  ํ˜„์‹ค์ ์ธ ๋ฐฉ์•ˆ๋“ค ์ค‘ ํ•˜๋‚˜๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๊ฒ ๋‹ค.The aim of the study was to examine the effects of poverty dynamics and the Medical Aid (MA) status change on health care use, health expenditure (out-of-pocket payments), and unmet need, using data from the Korea Health Panel 2008-2014 for the years of 2011-2013. Then, the study aimed to analyze the effect of catastrophic health expenditure (CHE) on the first poverty spell length and the total poverty duration among the poor at the poverty line of less than 50% of the median income level (MIL), using the Korean Welfare Panel Study 2008-2016 through the panel generalized estimating equations population-averaged model. The study then examined the effect of CHE on exit from poverty among the poor at the poverty line of less than 40% of MIL, analyzing data from the Korean Welfare Panel Study 2008-2016 through a discrete time event history analysis. This study was the first attempt to explore the effect of poverty dynamics on health care use, health expenditure, and unmet need. The study showed that the persistent poor had difficulties in access to having emergency visits and hospitalization. The persistent poor spent less total health expenditure at all the poverty lines, and less outpatient health expenditures at some poverty lines and reported more unmet need for all reasons and for the economic reason. The recurrent poor had less inpatient care, spent less total health expenditure, and reported the largest unmet need for the economic reason. Considering how important receiving proper health care services timely to improve and sustain health and well-being is, the results raise some concerns that the persistent poor and potentially the recurrent poor would be at risk of having worse health status and well-being. As for the effects of the MA status change on health care use, health expenditure, and unmet need, the continuous MA had more outpatient visits, less medical check-ups, more emergency visits, more inpatient care, less health expenditure, and more unmet need; the new MA group who can have relatively high benefit coverage of services by reduction of co-payment compared to the continuous health insurance beneficiaries had more outpatient visits and stayed longer at a hospital; the new HI group who may have relatively low benefit coverage level decreased their inpatient care use, which may also affect the result of unmet need. The study was the first exploratory study to examine the effect of catastrophic health expenditure on the first poverty spell length and the total poverty duration, and on exit from poverty. Households with occurrence of CHE at the thresholds of 30-40% were more likely to be at risk of lengthening their first poverty spell, even after controlling other predictors of poverty duration. Households with occurrence of CHE at the threshold of 30% were likely to stay longer in the total poverty duration, with smaller effect sizes of CHE compared to those at the first poverty spell. This would suggest that effects of CHE were more critical for the first poverty spell. Effects of CHE on poverty exit were different between exit to near-poverty and exit to non-poverty. Households facing CHE were less likely to exit from poverty to near-poverty at the thresholds of 20-30%; however, effects of CHE were not associated with exiting from poverty to non-poverty. Considering the majority of types of exit from poverty were exit to near-poverty (about 70%), this result would raise concerns that occurrences of CHE may pose a big threat to their already limited household budget. Combined loss of income due to ill health, financial burden due to health care use may force the poor to be stuck at poverty. The key approach to achieving better access to care and financial protection should be to develop prepayment systems by extending benefit packages and reducing co-payments. Reduction of incidence of CHE by expanding coverage of the national health insurance may be one of more feasible ways of reducing poverty and improving well-being of the people in a society, along with other sectors policies for poverty reduction.Contents Introduction 1 1. Background 1 2. Research objectives of the study 6 Literature review 8 1. Health care use, health expenditure, and unmet need among the poor 9 2. Poverty dynamics 24 3. Catastrophic health expenditure and poverty persistence 37 Research frameworks and methods 42 1. Research frameworks 42 1.1. The effect of poverty dynamics and the Medical Aid status change on health care use, health expenditure, and unmet need in South Korea 42 1.2. The effect of catastrophic health expenditure on persistence of poverty in South Korea 43 2. Research methods 45 2.1. The effect of poverty dynamics and the Medical Aid status change on health care use, health expenditure, and unmet need in South Korea 45 2.2. The effect of catastrophic health expenditure on persistence of poverty in South Korea 50 The effect of poverty dynamics and the Medical Aid status change on health care use, health expenditure, and unmet need in South Korea 59 1. Results 59 2. Discussions 83 3. Limitations 92 The effect of catastrophic health expenditure on persistence of poverty in South Korea 94 1. The effect of catastrophic health expenditure on poverty duration among the poor 94 1.1. Results 94 2. The effect of catastrophic health expenditure on exit from poverty among the poor 110 2.1. Results 110 3. Discussions 116 4. Limitations 129 Policy implications and conclusion 132 References 141 Appendix 155Docto

    Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study

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    Background Mammography is the current standard for breast cancer screening. This study aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in mammography, and explore whether it could benefit radiologists by improving accuracy of diagnosis. Methods In this retrospective study, an AI algorithm was developed and validated with 170 230 mammography examinations collected from five institutions in South Korea, the USA, and the UK, including 36 468 cancer positive confirmed by biopsy, 59 544 benign confirmed by biopsy (8827 mammograms) or follow-up imaging (50 717 mammograms), and 74 218 normal. For the multicentre, observer-blinded, reader study, 320 mammograms (160 cancer positive, 64 benign, 96 normal) were independently obtained from two institutions. 14 radiologists participated as readers and assessed each mammogram in terms of likelihood of malignancy (LOM), location of malignancy, and necessity to recall the patient, first without and then with assistance of the AI algorithm. The performance of AI and radiologists was evaluated in terms of LOM-based area under the receiver operating characteristic curve (AUROC) and recall-based sensitivity and specificity. Findings The AI standalone performance was AUROC 0ยท959 (95% CI 0ยท952โ€“0ยท966) overall, and 0ยท970 (0ยท963โ€“0ยท978) in the South Korea dataset, 0ยท953 (0ยท938โ€“0ยท968) in the USA dataset, and 0ยท938 (0ยท918โ€“0ยท958) in the UK dataset. In the reader study, the performance level of AI was 0ยท940 (0ยท915โ€“0ยท965), significantly higher than that of the radiologists without AI assistance (0ยท810, 95% CI 0ยท770โ€“0ยท850; p<0ยท0001). With the assistance of AI, radiologistsโ€™ performance was improved to 0ยท881 (0ยท850โ€“0ยท911; p<0ยท0001). AI was more sensitive to detect cancers with mass (53 [90%] vs 46 [78%] of 59 cancers detected; p=0ยท044) or distortion or asymmetry (18 [90%] vs ten [50%] of 20 cancers detected; p=0ยท023) than radiologists. AI was better in detection of T1 cancers (73 [91%] vs 59 [74%] of 80; p=0ยท0039) or node-negative cancers (104 [87%] vs 88 [74%] of 119; p=0ยท0025) than radiologists. Interpretation The AI algorithm developed with large-scale mammography data showed better diagnostic performance in breast cancer detection compared with radiologists. The significant improvement in radiologistsโ€™ performance when aided by AI supports application of AI to mammograms as a diagnostic support tool.ope

    ๋‚จ์„ฑ์œ ๋ฐฉ์—์„œ ์œ ๋ฐฉ์•”๊ณผ ์œ ์‚ฌํ•˜๊ฒŒ ๋ณด์ด๋Š” ๊ณผ๋ฆฝ์„ธํฌ์ข…์–‘: ์ฆ๋ก€ ๋ณด๊ณ 

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    Granular cell tumor of the breast is a rare tumor arising from Schwann cells. Although it is usually a benign tumor, its characteristics can mimic those of breast carcinoma clinically, radiologically, and macroscopically. The tongue is the single most common anatomic site involved; however, a granular cell tumor may arise in virtually any site of the body. We report on a 67-year-old male patient with a palpable breast mass presenting as an irregular mass on mammography and ultrasound.ope

    ์ดˆ์ŒํŒŒ ์œ ๋„ํ•˜ ํ•ต์ƒ๊ฒ€์—์„œ ์ง„๋‹จ๋œ ์œ ๋ฐฉ์˜ ์—ฝ์ƒ์ข…์–‘ ํ˜น์€ ์„ธํฌ์ถฉ์‹ค์„ฑ์„ฌ์œ ์ƒํ”ผ๋ณ‘๋ณ€: ์ ˆ์ œ์ƒ๊ฒ€ ๊ฒฐ๊ณผ์™€ ์ดˆ์ŒํŒŒ ์†Œ๊ฒฌ๊ณผ์˜ ๋น„๊ต

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    PURPOSE: The purpose of this study was to analyze the histologic concordance of sonographically guided core needle biopsy for phyllodes tumors or fibroepithelial lesions with cellular stroma of the breast by comparing this with the outcomes of excision biopsy and to identify any sonographic features that are helpful to predict phyllodes tumors. MATERIALS AND METHODS: We retrospectively reviewed 60 breast masses that were diagnosed as phyllodes tumors (n = 43) or fibroepithelial lesions with cellular stroma (n = 17) on a sonographically guided core needle biopsy. The tumors were all subsequently excised by surgery. The sonographic features were compared between the phyllodes tumors and the non-phyllodes tumors according to the results of excision biopsy. RESULTS: By the results on excision biopsy, there were 48 (80%) phyllodes tumors and 12 (20%) non-phyllodes tumors. Phyllodes tumors were diagnosed at a rate of 90.7% (39/43) for the nodules with phyllodes tumors on the sonographically guided core needle biopsy, and at a rate of 52.9% (9/17) for the nodules with fibroepithelial lesions with cellular stroma on the sonographically guided core needle biopsy. On sonography, heterogeneous internal echotexture (58% vs. 17%, respectively, p = 0.0239), clefts (56% vs. 17%, respectively, p = 0.0331) and horizontal linear striations (71% vs. 33%, respectively, p = 0.0221) were significantly more frequent in the phyllodes tumors than that in the non-phyllodes tumors. CONCLUSION: Identification of a heterogeneous-internal echotexture, clefts and horizontal linear striations on sonography might help differentiate phyllodes tumors from non-phyllodes tumorsope

    Annual Trends in Ultrasonography-Guided 14-Gauge Core Needle Biopsy for Breast Lesions

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    OBJECTIVE: To examine time trends in ultrasonography (US)-guided 14-gauge core needle biopsy (CNB) for breast lesions based on the lesion size, Breast Imaging-Reporting and Data System (BI-RADS) category, and pathologic findings. MATERIALS AND METHODS: We retrospectively reviewed consecutive US-guided 14-gauge CNBs performed from January 2005 to December 2016 at our institution. A total of 22,297 breast lesions were included. The total number of biopsies, tumor size (โ‰ค 10 mm to > 40 mm), BI-RADS category (1 to 5), and pathologic findings (benign, high risk, ductal carcinoma in situ [DCIS], invasive cancer) were examined annually, and the malignancy rate was analyzed based on the BI-RADS category. RESULTS: Both the total number of US scans and US-guided CNBs increased while the proportion of US-guided CNBs to the total number of US scans decreased significantly. The number of biopsies classified based on the tumor size, BI-RADS category, and pathologic findings all increased over time, except for BI-RADS categories 1 or 2 and category 3 (odds ratio [OR] = 0.951 per year, 95% confidence interval [CI]: 0.902, 1.002 and odds ratio = 0.979, 95% CI: 0.970, 0.988, respectively). Both the unadjusted and adjusted total malignancy rates and the DCIS rate increased significantly over time. BI-RADS categories 4a, 4b, and 4c showed a significant increasing trend in the total malignancy rate and DCIS rate. CONCLUSION: The malignancy rate in the results of US-guided 14-gauge CNB for breast lesions increased as the total number of biopsies increased from 2005 to 2016. This trend persisted after adjusting for the BI-RADS category.ope

    Radiomics in predicting mutation status for thyroid cancer: A preliminary study using radiomics features for predicting BRAFV600E mutations in papillary thyroid carcinoma

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    PURPOSE: To evaluate whether if ultrasonography (US)-based radiomics enables prediction of the presence of BRAFV600E mutations among patients diagnosed as papillary thyroid carcninoma (PTC). METHODS: From December 2015 to May 2017, 527 patients who had been treated surgically for PTC were included (training: 387, validation: 140). All patients had BRAFV600E mutation analysis performed on surgical specimen. Feature extraction was performed using preoperative US images of the 527 patients (mean size of PTC: 16.4mmยฑ7.9, range, 10-85 mm). A Radiomics Score was generated by using the least absolute shrinkage and selection operator (LASSO) regression model. Univariable/multivariable logistic regression analysis was performed to evaluate the factors including Radiomics Score in predicting BRAFV600E mutation. Subgroup analysis including conventional PTC <20-mm (n = 389) was performed (training: 280, validation: 109). RESULTS: Of the 527 patients diagnosed with PTC, 428 (81.2%) were positive and 99 (18.8%) were negative for BRAFV600E mutation. In both total 527 cancers and 389 conventional PTC<20-mm, Radiomics Score was the single factor showing significant association to the presence of BRAFV600E mutation on multivariable analysis (all P<0.05). C-statistics for the validation set in the total cancers and the conventional PTCs<20-mm were lower than that of the training set: 0.629 (95% CI: 0.516-0.742) to 0.718 (95% CI: 0.650-0.786), and 0.567 (95% CI: 0.434-0.699) to 0.729 (95% CI: 0.632-0.826), respectively. CONCLUSION: Radiomics features extracted from US has limited value as a non-invasive biomarker for predicting the presence of BRAFV600E mutation status of PTC regardless of size.ope

    ๋ฐ˜์ง€์„ธํฌ ์œ„์•”์˜ ์œ ๋ฐฉ ์ „์ด: ์ฆ๋ก€ ๋ณด๊ณ 

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    Metastasis of signet ring cell gastric carcinoma to the breast is extremely rare. The common clinical findings are redness, edematous skin and pain, and these findings are similar to those of inflammatory breast cancer. We describe here a case of metastatic signet ring cell gastric carcinoma to the bilateral breasts, and this presented as bilateral palpable breast lumps after the patient had undergone radical total gastrectomy two years previouslyope

    ์ˆ˜์ˆ  ์ „ ํ•ญ์•”ํ™”ํ•™์š”๋ฒ•์„ ์‹œํ–‰๋ฐ›๋Š” ์œ ๋ฐฉ์•” ํ™˜์ž์—์„œ ์ดˆ์ŒํŒŒ์œ ๋„ํ•˜ ํด๋ฆฝ์‚ฝ์ž…์ˆ ์˜ ํƒ€๋‹น์„ฑ ์—ฐ๊ตฌ

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    Purpose: The purpose of our study was to investigate the feasibility of US-guided clip implantation in patients receiving neoadjuvant chemotherapy for treatment of breast cancer. Materials and Methods: From January to May 2012, marker clips were inserted with US guidance in or adjacent to 23 tumors in 20 female patients receiving neoadjuvant chemotherapy for treatment of breast cancer at our institution. One radiologist performed a retrospective review of the identification of tumors on US, mammography, and breast MRI, and MRI artifact caused by a marker clip. Clip migration was evaluated using the clip-to-nipple distance on mammography obtained immediately after clip insertion and within one week before breast surgery. Complication associated with clip insertion was also observed. Results: After completion of neoadjuvant chemotherapy, all tumors showed a decrease in size, and 13 of 23 (56.5%) tumors were no longer palpable and thus required preoperative localization. In addition, marker clips were the only remaining evidence of the original tumor site in three of 23 (13.0%) tumors at the time of preoperative localization. All signal voids caused by a marker clip on breast MRI were less than 1 cm, which did not have a significant effect on detection and evaluation of the extent of the breast cancer. The mean change of the clip-to-nipple distance was 2.11 mm on a craniocaudal, and 2.67 mm on a mediolateral mammogram. No complication associated with clip insertion was observed in any case. Conclusion: US-guided clip implantation in or adjacent to a breast cancer is safe and feasible for patients with anticipation of complete or near complete response to neoadjuvant chemotherapy.ope

    ๊ฐ‘์ƒ์„ ์•”์˜ 18F-Fluorodeoxyglucose PET ์„ญ์ทจ ์œ ๋ฌด์— ๋”ฐ๋ฅธ ์ž„์ƒ์†Œ๊ฒฌ, ๋ณ‘๋ฆฌ์†Œ๊ฒฌ ๋ฐ ์ดˆ์ŒํŒŒ ์†Œ๊ฒฌ์˜ ๋น„๊ต์— ๋Œ€ํ•œ ๊ณ ์ฐฐ

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    PURPOSE: We wanted to investigate the incidence and the clinicopathologic and sonographic characteristics of thyroid cancers that exhibit positive PET scans. MATERIALS AND METHODS: From January 2007 to February 2008, 156 patients with thyroid cancer underwent both sonography and FDG-PET for the purpose of staging the cancer. We conducted a retrospective review of their clinical, radiologic and pathologic records and we evaluated the incidence of PET-positive thyroid cancer, as well as the associated clinicopathologic aggressiveness and the sonographic features. RESULTS: The incidence of PET-positive thyroid carcinoma was 78.2% (122/156). On univariate analysis, PET-positive thyroid cancer was significantly associated with tumor size, extracapsular invasion and central lymph node metastasis, but there was no association between the sonographic features of the thyroid cancer or the sonographic features of the 2 groups of tumor (1. probably benign and 2. suspicious for malignancy) and the FDG uptake. Multivariate logistic regression analysis showed a significant association between PET positivity and both extrathyroidal extension and a higher cancer stage (III/IV) (p < 0.05). CONCLUSION: The incidence of PET positive thyroid carcinoma is high (78.2%) and PET positivity is significantly associated with tumor size, extracapsular extension and a higher stage. However, there is no significant association between PET positivity and the sonographic features of thyroid carcinomaope

    Sonographic predictors of aggressive behavior in medullary thyroid carcinomas

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    Objective: To identify the clinical and sonographic risk factors for aggressive behavior of Medullary Thyroid Carcinomas (MTCs). Material and methods: This is a retrospective analysis. The informed consents were waived. Totally, 127 patients were selected from the database. Two radiologists were invited to review the clinical records and ultrasonic images and scored all the cases according to ACR TI-RADS, retrospectively. Kappa test was used to evaluate the consistency between the two reviewers. Logistic regression analysis was carried to identify the risk factors for aggressive behaviors of MTCs. Comparison of survival proportions between different groups were calculated by Kaplan-Meier method and log-rank test. Results: Female patients with MTCs were more commonly seen than male (1.7:1), male sex was a risk factor for both metastasis (OR: 4.471, P = 0.001) and perithyroidal invasion (OR = 4.674, P = 0.004). Consistency between the two reviewers were quite high (K value, 0.797-0.988). On sonograms, typical MTCs manifest as hypoechoic (96.9%) solid nodules (94.5%). Sex of patients (P = 0.001), margin (P = 0.003) and focality (P = 0.01) of the nodule were independent risk factors for metastasis, whereas sex of the patients (P = 0.004) and margin (P = 0.000) were independent risk factors for perithyroidal invasion. By Kaplan-Meier analysis, survival proportions different between groups with/without perithyroidal extension (P = 0.000) but not between groups with/without metastasis (P = 0.473). Conclusion: High frequency ultrasound and TI-RADS were effective methods for preoperative diagnosis of MTC. Sex of the patients and margin of the nodule are common risk factors for both metastasis and perithyroidal invasion. Focality of the tumor is another independent risk factor for metastasis.ope
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