Objective:To optimize the scan parameters for ultra-low dose computed tomography (ULDCT) of the chest using spectral purification technology, and assess the feasibility of maintaining image quality while reducing radiation dosage.Methods:An anthropomorphic chest phantom embedded with simulated pulmonary nodules was utilized for low-dose computed tomography(LDCT) and ULDCT scans. LDCT was conducted using a reference tube current of 25 mAs and a pitch of 1.0. ULDCT incorporating spectral purification technology was conducted using four reference tube currents, i. e., 50, 100, 150, and 200 mAs (labeled ULDCT1-4), and a pitch of 1.5. Other parameters were consistent. The volume CT dose index and the dose-length product were extracted from the dose reports, and then the effective doses were calculated. The objective image quality was assessed using metrics including image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The subjective image quality of ULDCT images was assessed on a four-point scale with LDCT images as reference.Results:The ULDCT4 at a reference tube current of 200 mAs showed a lower effective dose compared to LDCT ( t = -17.30, P < 0.001). The objective image quality assessments indicated that noise levels in four ULDCT groups were higher than those in LDCT ( t = 21.96, 10.56, 3.15, 3.14, P < 0.05). Notably, the SNR and CNR for the aortic arch were higher in ULDCT4 compared to LDCT ( t = 3.55, 71.96, P < 0.05). The SNR of pulmonary nodules in ULDCT4 was comparable to that in LDCT ( P > 0.05), but the CNR was higher ( t = 0.79, P < 0.001). Subjective image quality assessments reveal that the image quality of ULDCT4 was higher than that of LDCT, with scores of 3.80±0.46 for noise, 3.70±0.46 for contrast and sharpness, and 3.37±0.66 for pulmonary nodules. Conclusions:ULDCT (200 mAs) using spectral purification technology can yield higher image quality than LDCT while substantially reducing the radiation dose, thus demonstrating substantial clinical potential and the promise of replacing LDCT in early lung cancer screening.

Objective:To optimize the scan parameters for ultra-low dose computed tomography (ULDCT) of the chest using spectral purification technology, and assess the feasibility of maintaining image quality while reducing radiation dosage.Methods:An anthropomorphic chest phantom embedded with simulated pulmonary nodules was utilized for low-dose computed tomography(LDCT) and ULDCT scans. LDCT was conducted using a reference tube current of 25 mAs and a pitch of 1.0. ULDCT incorporating spectral purification technology was conducted using four reference tube currents, i. e., 50, 100, 150, and 200 mAs (labeled ULDCT1-4), and a pitch of 1.5. Other parameters were consistent. The volume CT dose index and the dose-length product were extracted from the dose reports, and then the effective doses were calculated. The objective image quality was assessed using metrics including image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The subjective image quality of ULDCT images was assessed on a four-point scale with LDCT images as reference.Results:The ULDCT4 at a reference tube current of 200 mAs showed a lower effective dose compared to LDCT ( t = -17.30, P < 0.001). The objective image quality assessments indicated that noise levels in four ULDCT groups were higher than those in LDCT ( t = 21.96, 10.56, 3.15, 3.14, P < 0.05). Notably, the SNR and CNR for the aortic arch were higher in ULDCT4 compared to LDCT ( t = 3.55, 71.96, P < 0.05). The SNR of pulmonary nodules in ULDCT4 was comparable to that in LDCT ( P > 0.05), but the CNR was higher ( t = 0.79, P < 0.001). Subjective image quality assessments reveal that the image quality of ULDCT4 was higher than that of LDCT, with scores of 3.80±0.46 for noise, 3.70±0.46 for contrast and sharpness, and 3.37±0.66 for pulmonary nodules. Conclusions:ULDCT (200 mAs) using spectral purification technology can yield higher image quality than LDCT while substantially reducing the radiation dose, thus demonstrating substantial clinical potential and the promise of replacing LDCT in early lung cancer screening.

Objective To investigate the prevalence and pattern of androgenetic alopecia (AGA) in Shanghai through a community-based survey. Methods A cluster sampling survey was done among the residents in Beixinjing Community, Changning District, Shanghai. All the subjects were asked to fill a questionnaire to provide their general information, including sex, age, native place, physical status, life habit, family history, etc. The diagnosis of AGA was made by dermatologists. To determine the pattern of hair loss,Norwood-Hamilton classification system and Ludwig classification system were used for male AGA and female AGA, respectively. All the data were statistically analyzed by EpiData and SPSS11.5 software. Results Totally, 7056 subjects completed the questionnaire, including 3519 males and 3537 females, and the response rate was 72.5%. AGA was diagnosed in 809 patients, consisting of 701 males aging from 19 to 91 years (mean 64.16±11.9 years) and 108 females aging from 35 to 91 years (mean 70.46±18.89 years). The standardized prevalence (SP) was 9.47% in total, 15.73% in males and 2.73% in females; the difference was significant between males and females (χ2=356.00, P<0.001). A family history of AGA was observed in 52.7% of all subjects including 391 (55.78%) males and 35 (32.41%) females. Type Ⅲ vertex involvement was the most common type in men aging from 20 to 70 years old, and type Ⅵ in those over 70 years old. Grade Ⅰ and Ⅱ predominated in female AGA. Conclusions The results of this survey indicate that the prevalence of AGA is remarkably higher in men than that in women. Furthermore, the prevalence is steadily increased with advancing age in Shanghai.