Within six months of the discovery of X-ray in 1895, the technology was used to scan the interior of the human body, paving the way for many innovations in the field of medicine, including an ultrasound device in 1950, a CT scanner in 1972, and MRI in 1980. More recent decades have witnessed developments such as digital imaging using a picture archiving and communication system, computer-aided detection/diagnosis, organ-specific workstations, and molecular, functional, and quantitative imaging. One of the latest technical breakthrough in the field of radiology has been imaging genomics and robotic interventions for biopsy and theragnosis. This review provides an engineering perspective on these developments and several other megatrends in radiology.
Biological Markers/analysis ; Biomedical Engineering ; Diagnosis, Computer-Assisted/*trends ; Diagnostic Imaging/*trends ; Equipment Design ; Genomics ; Humans ; Image Processing, Computer-Assisted/*trends ; Radiology Information Systems/*trends ; Robotics ; Systems Integration ; User-Computer Interface

Purpose: The purpose of this study is to build a prediction model for estimating graft weight about different graft volumetry methods combined with other variables. Methods: Donors who underwent living-donor right hepatectomy from March 2021 to March 2023 were included. Estimated graft volume measured by conventional method and 3-dimensional (3D) software were collected as well as the actual graft weight. Linear regression was used to build a prediction model. Donor groups were divided according to the 3D volumetry of <700 cm3 , 700–899 cm3 , and ≥900 cm3 to compare the performance of different models. Results: A total of 119 donors were included. Conventional volumetry showed R2 of 0.656 (P < 0.001) while 3D software showed R2 of 0.776 (P < 0.001). The R2 of the multivariable model was 0.842 (P < 0.001) including for 3D volume (β = 0.623, P < 0.001), body mass index (β = 7.648, P < 0.001), and amount of weight loss (β = –7.252, P < 0.001). The median errors between different models and actual graft weight did not differ in donor groups (<700 and 700–899 cm3 ), while the median error of univariable linear model using 3D software (122.5; interquartile range [IQR], 61.5–179.8) was significantly higher than multivariable-adjusted linear model (41.5; IQR, 24.8–69.8; P = 0.003) in donors with estimated graft weight ≥900 cm3 . Conclusion The univariable 3D volumetry model showed an acceptable outcome for donors with an estimated graft volume <900 cm3 . For donors with an estimated graft volume ≥900 cm3 , the multivariable-adjusted linear model showed higher accuracy.

Purpose: The purpose of this study is to build a prediction model for estimating graft weight about different graft volumetry methods combined with other variables. Methods: Donors who underwent living-donor right hepatectomy from March 2021 to March 2023 were included. Estimated graft volume measured by conventional method and 3-dimensional (3D) software were collected as well as the actual graft weight. Linear regression was used to build a prediction model. Donor groups were divided according to the 3D volumetry of <700 cm3 , 700–899 cm3 , and ≥900 cm3 to compare the performance of different models. Results: A total of 119 donors were included. Conventional volumetry showed R2 of 0.656 (P < 0.001) while 3D software showed R2 of 0.776 (P < 0.001). The R2 of the multivariable model was 0.842 (P < 0.001) including for 3D volume (β = 0.623, P < 0.001), body mass index (β = 7.648, P < 0.001), and amount of weight loss (β = –7.252, P < 0.001). The median errors between different models and actual graft weight did not differ in donor groups (<700 and 700–899 cm3 ), while the median error of univariable linear model using 3D software (122.5; interquartile range [IQR], 61.5–179.8) was significantly higher than multivariable-adjusted linear model (41.5; IQR, 24.8–69.8; P = 0.003) in donors with estimated graft weight ≥900 cm3 . Conclusion The univariable 3D volumetry model showed an acceptable outcome for donors with an estimated graft volume <900 cm3 . For donors with an estimated graft volume ≥900 cm3 , the multivariable-adjusted linear model showed higher accuracy.

Purpose: The purpose of this study is to build a prediction model for estimating graft weight about different graft volumetry methods combined with other variables. Methods: Donors who underwent living-donor right hepatectomy from March 2021 to March 2023 were included. Estimated graft volume measured by conventional method and 3-dimensional (3D) software were collected as well as the actual graft weight. Linear regression was used to build a prediction model. Donor groups were divided according to the 3D volumetry of <700 cm3 , 700–899 cm3 , and ≥900 cm3 to compare the performance of different models. Results: A total of 119 donors were included. Conventional volumetry showed R2 of 0.656 (P < 0.001) while 3D software showed R2 of 0.776 (P < 0.001). The R2 of the multivariable model was 0.842 (P < 0.001) including for 3D volume (β = 0.623, P < 0.001), body mass index (β = 7.648, P < 0.001), and amount of weight loss (β = –7.252, P < 0.001). The median errors between different models and actual graft weight did not differ in donor groups (<700 and 700–899 cm3 ), while the median error of univariable linear model using 3D software (122.5; interquartile range [IQR], 61.5–179.8) was significantly higher than multivariable-adjusted linear model (41.5; IQR, 24.8–69.8; P = 0.003) in donors with estimated graft weight ≥900 cm3 . Conclusion The univariable 3D volumetry model showed an acceptable outcome for donors with an estimated graft volume <900 cm3 . For donors with an estimated graft volume ≥900 cm3 , the multivariable-adjusted linear model showed higher accuracy.

Purpose: The purpose of this study is to build a prediction model for estimating graft weight about different graft volumetry methods combined with other variables. Methods: Donors who underwent living-donor right hepatectomy from March 2021 to March 2023 were included. Estimated graft volume measured by conventional method and 3-dimensional (3D) software were collected as well as the actual graft weight. Linear regression was used to build a prediction model. Donor groups were divided according to the 3D volumetry of <700 cm3 , 700–899 cm3 , and ≥900 cm3 to compare the performance of different models. Results: A total of 119 donors were included. Conventional volumetry showed R2 of 0.656 (P < 0.001) while 3D software showed R2 of 0.776 (P < 0.001). The R2 of the multivariable model was 0.842 (P < 0.001) including for 3D volume (β = 0.623, P < 0.001), body mass index (β = 7.648, P < 0.001), and amount of weight loss (β = –7.252, P < 0.001). The median errors between different models and actual graft weight did not differ in donor groups (<700 and 700–899 cm3 ), while the median error of univariable linear model using 3D software (122.5; interquartile range [IQR], 61.5–179.8) was significantly higher than multivariable-adjusted linear model (41.5; IQR, 24.8–69.8; P = 0.003) in donors with estimated graft weight ≥900 cm3 . Conclusion The univariable 3D volumetry model showed an acceptable outcome for donors with an estimated graft volume <900 cm3 . For donors with an estimated graft volume ≥900 cm3 , the multivariable-adjusted linear model showed higher accuracy.

PURPOSE: To evaluate the risk factors for overactive bladder (OAB) in a population aged 40 years and over in the community. MATERIALS AND METHODS: We conducted a community-based survey of OAB in a population aged 40 years and over in Guri City and Yangpyeong County, South Korea, by use of the overactive bladder symptom score (OABSS) questionnaire. A total of 926 subjects were included in the final analysis. The definition of OAB was more than 2 points for the urgency score and 3 points for the sum of scores. In addition, the subjects were asked about age, dwelling place, marital status, educational status, behavioral factors (smoking, drinking, etc), and medical history. Categorical variables were analyzed by using the logistic regression model and were adjusted for age by using the logistic regression model. RESULTS: Overall OAB prevalence was 14.1% (130/926), made up of 49/403 males (12.2%) and 81/523 females (15.5%). OAB prevalence increased with age (p<0.0001). Risk factors for OAB were educational status (age-adjusted p=0.0487), stroke (p=0.0414), osteoporosis (p=0.0208), asthma (p=0.0091), rhinitis (p=0.0008), and cataract. Other factors (dwelling place, marital status, smoking, drinking, hypertension, diabetes, hyperlipidemia, myocardial infarction, angina, tuberculosis, atopic dermatitis, hepatitis B, and depression) were not associated with OAB. CONCLUSIONS: The prevalence of OAB in our study was about 14.1% and the risk factors for OAB were educational status, stroke, osteoporosis, asthma, rhinitis, and cataract. Knowledge of these risk factors may help in the diagnosis and treatment of OAB.
Aged ; Asthma ; Cataract ; Dermatitis, Atopic ; Drinking ; Educational Status ; Female ; Hepatitis B ; Humans ; Hyperlipidemias ; Hypertension ; Hypogonadism ; Logistic Models ; Male ; Marital Status ; Mitochondrial Diseases ; Myocardial Infarction ; Ophthalmoplegia ; Osteoporosis ; Prevalence ; Republic of Korea ; Rhinitis ; Risk Factors ; Smoke ; Smoking ; Stroke ; Tuberculosis ; Urinary Bladder, Overactive

PURPOSE: For a single time-point hyperpolarized 13C magnetic resonance spectroscopy imaging (MRSI) of animal models, scan-time window after injecting substrates is critical in terms of signal-to-noise ratio (SNR) of downstream metabolites. Prescans of time-resolved magnetic resonance spectroscopy (MRS) can be performed to determine the scan-time window. In this study, based on two-site exchange model, protocol-specific simulation approaches were developed for 13C MRSI and the optimal scan-time window was determined to maximize the SNR of downstream metabolites. MATERIALS AND METHODS: The arterial input function and conversion rate constant from injected substrates (pyruvate) to downstream metabolite (lactate) were precalibrated, based on pre-scans of time-resolved MRS. MRSI was simulated using twosite exchange model with considerations of scan parameters of MRSI. Optimal scantime window for mapping lactate was chosen from simulated lactate intensity maps. The performance was validated by multiple in vivo experiments of BALB/C nude mice with MDA-MB-231 breast tumor cells. As a comparison, MRSI were performed with other scan-time windows simply chosen from the lactate signal intensities of prescan time-resolved MRS. RESULTS: The optimal scan timing for our animal models was determined by simulation, and was found to be 15 s after injection of the pyruvate. Compared to the simple approach, we observed that the lactate peak signal to noise ratio (PSNR) was increased by 230%. CONCLUSIONS: Optimal scan timing to measure downstream metabolites using hyperpolarized 13C MRSI can be determined by the proposed protocol-specific simulation approaches.
Animals ; Breast Neoplasms ; Lactic Acid ; Magnetic Resonance Spectroscopy ; Mice ; Mice, Nude ; Models, Animal ; Pyruvic Acid ; Signal-To-Noise Ratio

PURPOSE: To investigate the exchange and redistribution of hyperpolarized ¹³C metabolites between different pools by temporally analyzing the relative fraction of dual T₂* components of hyperpolarized ¹³C metabolites. MATERIALS AND METHODS: A dual exponential decay analysis of T₂* is performed for [1-¹³C] pyruvate and [1-¹³C] lactate using nonspatially resolved dynamic ¹³C MR spectroscopy from mice brains with tumors (n = 3) and without (n = 4) tumors. The values of shorter and longer T₂* components are explored when fitted from averaged spectrum and temporal variations of their fractions. RESULTS: The T₂* values were not significantly different between the tumor and control groups, but the fraction of longer T₂* [1-¹³C] lactate components was more than 10% in the tumor group over that of the controls (P < 0.1). The fraction of shorter T₂* components of [1-¹³C] pyruvate showed an increasing tendency while that of the [1-¹³C] lactate was decreasing over time. The slopes of the changing fraction were steeper for the tumor group than the controls, especially for lactate (P < 0.01). In both pyruvate and lactate, the fraction of the shorter T₂* component was always greater than the longer T₂* component over time. CONCLUSIONS: The exchange and redistribution of pyruvate and lactate between different pools was investigated by dual component analysis of the free induction decay signal from hyperpolarized ¹³C experiments. Tumor and control groups showed differences in their fractions rather than the values of longer and shorter T₂* components. Fraction changing dynamics may provide an aspect for extravasation and membrane transport of pyruvate and lactate, and will be useful to determine the appropriate time window for acquisition of hyperpolarized ¹³C images.
Animals ; Brain ; Lactic Acid ; Magnetic Resonance Spectroscopy ; Membranes ; Mice ; Pyruvic Acid

In liver transplantation, the primary concern is to ensure an adequate future liver remnant (FLR) volume for the donor, while selecting a graft of sufficient size for the recipient. The living donor–resection and partial liver segment 2−3 transplantation with delayed total hepatectomy (LD−RAPID) procedure offers a potential solution to expand the donor pool for living donor liver transplantation (LDLT).We report the first case involving a cirrhotic patient with autoimmune hepatitis and hepatocellular carcinoma, who underwent left lobe LDLT using the LD−RAPID procedure. The living liver donor (LLD) underwent a laparoscopic left hepatectomy, including middle hepatic vein. The resection on the recipient side was an extended left hepatectomy, including the middle hepatic vein orifice and caudate lobe. At postoperative day 7, a computed tomography scan showed hypertrophy of the left graft from 320 g to 465 mL (i.e., a 45.3% increase in graft volume body weight ratio from 0.60% to 0.77%). After a 7-day interval, the diseased right lobe was removed in the second stage surgery. The LD−RAPID procedure using left lobe graft allows for the use of a small liver graft or small FLR volume in LLD in LDLT, which expands the donor pool to minimize the risk to LLD by enabling the donation of a smaller liver portion.

In liver transplantation, the primary concern is to ensure an adequate future liver remnant (FLR) volume for the donor, while selecting a graft of sufficient size for the recipient. The living donor–resection and partial liver segment 2−3 transplantation with delayed total hepatectomy (LD−RAPID) procedure offers a potential solution to expand the donor pool for living donor liver transplantation (LDLT).We report the first case involving a cirrhotic patient with autoimmune hepatitis and hepatocellular carcinoma, who underwent left lobe LDLT using the LD−RAPID procedure. The living liver donor (LLD) underwent a laparoscopic left hepatectomy, including middle hepatic vein. The resection on the recipient side was an extended left hepatectomy, including the middle hepatic vein orifice and caudate lobe. At postoperative day 7, a computed tomography scan showed hypertrophy of the left graft from 320 g to 465 mL (i.e., a 45.3% increase in graft volume body weight ratio from 0.60% to 0.77%). After a 7-day interval, the diseased right lobe was removed in the second stage surgery. The LD−RAPID procedure using left lobe graft allows for the use of a small liver graft or small FLR volume in LLD in LDLT, which expands the donor pool to minimize the risk to LLD by enabling the donation of a smaller liver portion.