• Journal of Chest Surgery
• /
• v.40 no.6 s.275
• /
• pp.420-427
• /
• 2007

Background: Postpneumonectomy empyema (PPE) due to bronchopleural fistula (BPF) can be a surgical challenge for surgeons. We analyzed the follow-up outcomes after performing omentopexy and thoracoplasty for the treatment of PPE with BPF after pneumonectomy. Material and Mehod: Between December 1991 and January 2006, 9 patients underwent BPF closure using an omental pedicled flap for the treatment of PPE with BPF after pneumonectomy. There were 7 males and 2 females (mean age: $45.9{\pm}9$ years). The patients were followed up for a mean of 58 months (median: 28 months, range: $6{\sim}169$). When we performed omentopexy, the surgical procedures for empyema were thoracoplasy for 8 patients and the Clagett procedure for 1 patient. Thoracoplasty was performed for the latter patient due to recurrence of empyema, Result: For the 8 patients who were treated by omentopexy and thoracoplasty, there was 1 operation-related death due to sepsis. During follow up, 1 patient, who was treated by omentopexy and a Clagett procedure, died of acute hepatitis 40 months postoperatively. The early mortality was 11.1% (8/9). Of the 8 patients, including the 1 late death patient, successful closure of the BPF were achieved in all patients (8/9) and the empyema was cured in 7 patients (7/8). Conclusion: The BPF closure using an omental pedicled flap was an effective method for treating PPE with BPF due to 75-destroyed lung, and thoracoplasty with simultaneous omentopexy was effective and safe for removing dead space if the patient was young and in a good general condition.

• The Korean Journal of Nuclear Medicine
• /
• v.39 no.1
• /
• pp.49-56
• /
• 2005

Purpose: Dedicated animal PET is useful equipment for the study of new PET tracer. recently, microPET R4 was installed in the Korea institute of radiology and medical science. In this study, we measured the characteristics of scanner. Materials and methods: Resolution was measured using a line source (F-18:65 ${\mu}Ci$, inner diameter: 0.5 mm). The line source was put in the axial direction and was moved from the center of field of view to outside with 1 mm interval. PET images were reconstructed using a filtered back-protection and ordered subset expectation maximization. line source (16.5 ${\mu}Ci$, 78 mm) was put on the tenter of axial direction to measure the sensitivity when the deadtime was under 1%. Images were acquired during 4 minutes respectively from center to 39 mm outward. Delayed count was subtracted from total count and then decay was corrected for the calculation of sensitivity. Noise equivalent count ratio and scatter fraction were calculated using cylindrical phantom. Results: Spatial resolution of reconstructed image using filtered back-projection was 1.86 mm(radial), 1.95 mm(tangential), 1.95 mm(axial) in the tenter of field of view, and 2.54 mm, 2.8 mm, 1.61 mm in 2 cm away from the center respectively. Sensitivity was 2.36% at the center of transaxial field of view. Scatter fraction was 20%. Maximal noise equivalent count ratio was 66.4 kcps at 242 kBq/mL. Small animal images were acquired for confirmation of performance. Conclusion: Performance characteristics of microPET R4 were similar with reported value. So this will be a useful tool for small animal imaging.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.34 no.1
• /
• pp.74-84
• /
• 1998

A doubly resonant ultrasonic transducer has been designed as an attempt to increase the bandwidth of underwater transducers. The dual resonance conditions were accomplished by attaching a single acoustic matching layer on the front face of a Tonpilz transducer consisted of an aluminum head, a piezoelectric ring, a brass tail and a prestress bolt. A modified Mason's model was used for the performance analysis and the design of transducers, and the constructed transducers were tested experimentally and numerically by changing the impedances and thicknesses of the head, tail and matching layers in the water tank. Two distinct resonance peaks in the transmitting voltage response(TVR) of a developed transducer were observed at 34.3 and 40.4 kHz, respectively, with the difference frequency of 6.1kHz and the center frequency of 37.2kHz. The values of TVR at these frequencies were 136.5 dB re $1\;\muPa/V$ at 34.3 kHz and 136.8 dB re $1\;\muPa/V$ at 40.4 kHz, respectively. Reasonable agreement between the experimental results and the numerical results was achieved. From this result, it is expected that the generation of the distinct resonances at any two desired frequencies can be achieved through the proper choice of the matching layer to provide the impedance transformation between the transducer and the medium.

• The Korean Society of Law and Medicine
• /
• v.24 no.4
• /
• pp.67-101
• /
• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.