The purpose of this study is to classify breast types and to inquire about characteristics depending on breast types of women subjects in their twenties. We researched size items affecting breast volume and regression equations for the prediction of breast volume, and thereby, we will be able to provide some basic data, useful to the development of the brassiere depending on breast types. As a result of categorizing the types of three breast types, "type 1" was characterized by big and greatest protrusion of the breast with large breast volume and a large bust, while "type 2" was characterized by flat breasts with the least breast volume and least bust, and "type 3" was characterized by breast location apart from the center front line. Breast volume is significant in establishment of the brassiere cup depending on breast type. Five items such as, the circumference of the breast, the length of the upper breast, the depth of the breast point, the length of the shoulder point-breast point, and the length of the inferior breast were extracted through regression equations for breast volume.
Journal of the Korean Society of Clothing and Textiles
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v.37
no.3
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pp.280-291
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2013
This paper analyzes desirable breast types using measurements from 31 selected female subjects based on the ratio of breast in works of art and to design a brassiere cup design according to the breast type of 182 female subjects in their 20s. The subjects selected for this paper are somewhat larger than a previous study on aesthetically perfect breasts of foreigners according to chest breadth, center neck point to breast point, breast circumference, and breast volume. However, the aesthetic breasts of foreigners are larger than the subjects selected for this study according to chest depth, under-bust circumference, and bust point to bust point. Comparing various breasts types and aesthetic breasts, padding is necessary to complement the form of flat breasts to increase the volume and diameter. Brassiere cups for cone-shaped breasts should be designed to increase breast volume through an increase in nipple height. Hemisphere breasts should be designed to increase the overall volume-leaving diameter. Protrusion breasts should enhance the functions of aggregating and supporting without any increase or decrease of the breast volume. Drooping breasts require the ability to support a large volume to stabilize the breast. Subjects were selected depending on the ratio of breast silhouette as works of art and who have large breasts in disproportional to a slender trunk. Three items, the circumferential length of breast, height of the nipple, and the depth of inner breast using the anthropomorphic measurements of 182 subjects were measured through regression equations for breast volume. Breast volume = -394.86 + 27.52 ${\times}$ (the circumferential length of breast) + 18.73 ${\times}$ (height of the nipple) + 12.85 ${\times}$ (the depth of inner breast). Regression equations to extract the aesthetic breast volume in measurements irrelevant to breasts using the anthropomorphic measurements of 31 subjects were as follows. Aesthetic breast volume = -611.30 + 17.67 ${\times}$ (bust circumference) -24.29 ${\times}$ (under-bust circumference) + 16.31 ${\times}$ (neck point to breast point to waistline) + 22.83 ${\times}$ (bust breadth) + 12.22 ${\times}$ (waist depth) -8.34 ${\times}$ (interscye- front). This prediction equation is useful to develop a breast type brassiere pattern, complement breast enhancement surgery, or minimize the effect a mastectomy.
Tectona grandis (teak) is one of the most important timber species worldwide and India is one of the major teak growing countries. Though some volume equations were developed for teak in India but the models developed were neither evaluated using robust statistical criteria nor validated. Hence, the objective of this study was to develop statistically tested appropriate volume equation to predict total wood volume (over- and under-bark) for teak trees in Gujarat. A total of 41 trees with age varying from 15 to 33 years and diameter at breast height (dbh) from 7.3 to 30.8 cm were felled for the purpose. Linear and non-linear equations were used to model the relationship of the total wood volume with respect to dbh and total height. The equations tested mostly fitted well to the data. Model evaluation and validation indicated that models should be calibrated with local data for greater accuracy in the prediction.
Utilization of high energy photons (>10MV) with an optimal weight using a mixed energy technique is a practical way to generate a homogenous dose distribution while maintaining adequate target coverage in intact breast radiotherapy. This study represents a model for estimation of this optimal weight for day to day clinical usage. For this purpose, treatment planning computed tomography scans of thirty-three consecutive early stage breast cancer patients following breast conservation surgery were analyzed. After delineation of the breast clinical target volume (CTV) and placing opposed wedge paired isocenteric tangential portals, dosimeteric calculations were conducted and dose volume histograms (DVHs) were generated, first with pure 6MV photons and then these calculations were repeated ten times with incorporating 18MV photons (ten percent increase in weight per step) in each individual patient. For each calculation two indexes including maximum dose in the breast CTV ($D_{max}$) and the volume of CTV which covered with 95% Isodose line ($V_{CTV,95%IDL}$) were measured according to the DVH data and then normalized values were plotted in a graph. The optimal weight of 18MV photons was defined as the intersection point of $D_{max}$ and $V_{CTV,95%IDL}$ graphs. For creating a model to predict this optimal weight multiple linear regression analysis was used based on some of the breast and tangential field parameters. The best fitting model for prediction of 18MV photons optimal weight in breast radiotherapy using mixed energy technique, incorporated chest wall separation plus central lung distance (Adjusted R2=0.776). In conclusion, this study represents a model for the estimation of optimal beam weighting in breast radiotherapy using mixed photon energy technique for routine day to day clinical usage.
Kim, Il-Kug;Lee, Jun-Ho;Kim, Yong-Ha;Kim, Tae-Gon;Lee, Soo-Jung;Kang, Soo-Hwan
Archives of Plastic Surgery
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v.38
no.6
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pp.808-814
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2011
Purpose: Despite wide clinical use of breast implants, there is continued concern about the lifespan of these devices. The causes of explantation were infection, deflation of implant and patient's want. The deflation of saline-filled breast implant was related to strength and durability of implant shell. The purpose of this study is to evaluate the clinical durability of saline-filled breast implant through the analysis of duration until deflation occurred, causes, incidence and influencing factors. Methods: Retrospective analyses were conducted on clinical records for 19 cases of deflation of saline-filled breast implant from 201 cases of breast reconstruction with saline-filled implant between May 1995 and June 2011. The authors had been analyzed the causes of deflation, survival duration, symptom, sign, nipple excision, volume of implant, saline filling, method of reoperation, breast cancer stage and combined capsular contracture. Results: The causes of deflation were attributed to the cases that cannot be evaluated the causes in 15 cases, fall down in 1 case, mammography in 2 cases, accidental needle injury in 1 case. Mean survival duration was 4 years and 5 months. The duration of survival was less than 1 year for 5 cases, 1 year to 10 years for 10 cases, more than 10 years for 4 cases. The volume between 201 and 250 cc of deflated breast implant was rated as high by 14.0 percent. The deflation rate of underfilled implants was 11.4 percent, adequate filled implants was 9.3 percent. None of overfilled implant was deflated. The deflation of smooth surface implant was 5 of 152 cases. Textured implant was 14 of 49 cases. The capsular contracture of non-deflated breast implant was 28 of 182 cases and that of deflated breast implant was 6 of 19 cases. Conclusion: The patients who underwent saline-filled breast implant implantation should be informed that their implant could deflate. The analysis of clinical durability and causes of deflation in breast implant was important for the prediction and prevention of reopeation. The authors could suppose the causes of deflation of saline-filled breast implant through history, duration of survival, inspection of the shell of implant.
Objective: As a source of information, medical data can feature hidden relationships. However, the high volume of datasets and complexity of decision-making in medicine introduce difficulties for analysis and interpretation and processing steps may be needed before the data can be used by clinicians in their work. This study focused on the use of Bayesian models with different numbers of nodes to aid clinicians in breast cancer risk estimation. Methods: Bayesian networks (BNs) with a retrospectively collected dataset including mammographic details, risk factor exposure, and clinical findings was assessed for prediction of the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: A network incorporating selected features performed better (AUC = 0.94) than that incorporating all the features (AUC = 0.93). The results revealed no significant difference among 3 models regarding performance indices at the 5% significance level. Conclusion: BNs could effectively discriminate malignant from benign abnormalities and accurately predict the risk of breast cancer in individuals. Moreover, the overall performance of the 9-node BN was better, and due to the lower number of nodes it might be more readily be applied in clinical settings.
Seongyeop Jeong;Jongsu Yim;Sunjung Lee;Jungeun Song;Hyokeun Park;JungBin Lee;Kyujin Yeom;Yeongmo Son
Journal of Korean Society of Forest Science
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v.112
no.1
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pp.83-92
/
2023
This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R2) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.
Min Young Kim;Heera Yoen;Hye Ji;Sang Joon Park;Sun Mi Kim;Wonshik Han;Nariya Cho
Korean Journal of Radiology
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v.24
no.12
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pp.1190-1199
/
2023
Objective: This study aimed to investigate the feasibility of ultrafast magnetic resonance imaging (MRI) and radiomic features derived from breast MRI for predicting the upstaging of ductal carcinoma in situ (DCIS) diagnosed using percutaneous needle biopsy. Materials and Methods: Between August 2018 and June 2020, 95 patients with 98 DCIS lesions who underwent preoperative breast MRI, including an ultrafast sequence, and subsequent surgery were included. Four ultrafast MRI parameters were analyzed: time-to-enhancement, maximum slope (MS), area under the curve for 60 s after enhancement, and time-to-peak enhancement. One hundred and seven radiomic features were extracted for the whole tumor on the first post-contrast T1WI and T2WI using PyRadiomics. Clinicopathological characteristics, ultrafast MRI findings, and radiomic features were compared between the pure DCIS and DCIS with invasion groups. Prediction models, incorporating clinicopathological, ultrafast MRI, and radiomic features, were developed. Receiver operating characteristic curve analysis and area under the curve (AUC) were used to evaluate model performance in distinguishing between the two groups using leave-one-out cross-validation. Results: Thirty-six of the 98 lesions (36.7%) were confirmed to have invasive components after surgery. Compared to the pure DCIS group, the DCIS with invasion group had a higher nuclear grade (P < 0.001), larger mean lesion size (P = 0.038), larger mean MS (P = 0.002), and different radiomic-related characteristics, including a more extensive tumor volume; higher maximum gray-level intensity; coarser, more complex, and heterogeneous texture; and a greater concentration of high gray-level intensity. No significant differences in AUCs were found between the model incorporating nuclear grade and lesion size (0.687) and the models integrating additional ultrafast MRI and radiomic features (0.680-0.732). Conclusion: High nuclear grade, larger lesion size, larger MS, and multiple radiomic features were associated with DCIS upstaging. However, the addition of MS and radiomic features to the prediction model did not significantly improve the prediction performance.
Biomass determination of species-specific in forest ecosystem by semi-destructive measures requires the development of allometric equations; predict aboveground biomass observable independent variables such as, Diameter at Breast Height, Height, and Volume are crucial role. There has not been equation of this type in mountain Chuqala natural forest. In this study two species namely, Hypericum revolutum Vahl. & Maesa lanceoleta Forssk. with tree diameter classes (15-20, 20.5-25, and 25.5-35 cm), with the purpose of conducting allometric equations were characterized. Each species assumed considered individually. For the linear model fit the two observed variable DBH, H and V were preferred for the prediction of above ground biomass. The best fitted model choose among the two formed model were identified using Akaike Information Criterion (AIC), and $R^2$ and adjacent $R^2$. Based on this the best fit model for Hypericum revolutum Vahl. was AGB=-681.015+4,494.06 (DBH), and for Maesa lanceoleta Forrsk. was. AGB=-936.96+5,268.92 (DBH).
Sora Kim;Jongsu Yim;Sunjung Lee;Jungeun Song;Hyelim Lee;Yeongmo Son
Journal of Korean Society of Forest Science
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v.112
no.2
/
pp.209-216
/
2023
This study aimed to use national forest inventory data to develop a forest productivity index and yield prediction model of a Tilia amurensis stand. The site index displaying the forest productivity of the Tilia amurensis stand was developed as a Schumacher model, and the site index classification curve was generated from the model results; its distribution growth in Korea ranged from 8-16. The growth model using age as an independent variable for breast height and height diameter estimation was derived from the Chapman-Richards and Weibull model. The Fitness Indices of the estimation models were 0.32 and 0.11, respectively, which were generally low values, but the estimation-equation residuals were evenly distributed around 0, so we judged that there would be no issue in applying the equation. The stand basal area and site index of the Tilia amurensis stand had the greatest effect on the stand-volume change. These two factors were used to derive the Tilia amurensis stand yield model, and the model's determination coefficient was approximately 94%. After verifying the residual normality of the equation and autocorrelation of the growth factors in the yield model, no particular problems were observed. Finally, the growth and yield models of the Tilia amurensis stand were used to produce the makeshift stand yield table. According to this table, when the Tilia amurensis stand is 70 years old, the estimated stand-volume per hectare would be approximately 208 m3 . It is expected that these study results will be helpful for decision-making of Tilia amurensis stands management, which have high value as a forest resource for honey and timber.
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