Kim Kwang-Hyun;Jung Eun-Jung;Hah Jeong-Hun;Kwon Seong-Keun;Sung Myung-Whun
Korean Journal of Head & Neck Oncology
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v.21
no.1
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pp.21-25
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2005
Background and Objectives: The popularity of complementary and alternative medicine(CAM) has grown at an astonishing rate in recent years. Because patients are interested in CAM and want to use it, physicians also should be concerned about CAM and know about the current situation of its usage. In this study, we tried to determine the prevalence of CAM use in the patients with head and neck cancer and correlate with demographics and tumor characteristics. Materials and Methods: A total of 87 patients with head and neck cancer previously treated with surgery at Seoul National University Hospital from March through June, 2004 were enrolled in this study. The patients were completed, questionnaire about the use of CAM and demographic information. Tumor characteristics were obtained from the patient's medical records. Results: Of the 87 patients, 33 patients(37.9%) use at least one CAM. There was no statistically significant correlation between patient's data and prevalence of CAM use. Of those patients using CAM, 16(48.5%) of 33 were using 2 or more therapies. The majority of agents used by patients in this study are mushrooms such as Phellinus and Reishi, followed by dietary therapy. A majority(60.6%) of patients were introduced to alternative medicine by friends or family members. Conclusion: Considerable cancer patients use CAM. Head and neck oncologists should inform themselves about CAM to counsel and educate the patients. Further scientific investigations on promising CAM agents may help advance cancer treatment.
Background: Breast cancer is the most common type of cancer amongst women throughout the world. Currently, there are various follow-up strategies implemented in Iran, which are usually dependent on clinic policies and agreement among the resident oncologists. Purpose: A cost-effectiveness analysis was performed to assess the cost-effectiveness of intensive follow-up versus standard models for early breast cancer patients in Iran. Materials and methods: This cross sectional study was performed with 382 patients each in the intensive and standard groups. Costs were identified and measured from a payer perspective, including direct medical outlay. To assess the effectiveness of the two follow-up models we used a decision tree along with indicators of detection of recurrence and metastasis, calculating expected costs and effectiveness for both cases; in addition, incremental cost-effectiveness ratios were determined. Results: The results of decision tree showed expected case detection rates of 0.137 and 0.018 and expected costs of US$24,494.62 and US$6,859.27, respectively, for the intensive and standard follow-up models. Tornado diagrams revealed the highest sensitivity to cost increases using the intensive follow-up model with an ICER=US$148,196.2. Conclusion: Overall, the results showed that the intensive follow-up method is not cost-effective when compared to the standard model.
This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.
The International Society for the Study of Vascular Anomalies classifies vascular anomalies into vascular tumors and vascular malformations. Vascular tumors are neoplasms of endothelial cells, among which infantile hemangiomas (IHs) are the most common, occurring in 5%-10% of infants. Glucose transporter-1 protein expression in IHs differs from that of other vascular tumors or vascular malformations. IHs are not present at birth but are usually diagnosed at 1 week to 1 month of age, rapidly proliferate between 1 and 3 months of age, mostly complete proliferation by 5 months of age, and then slowly involute to the adipose or fibrous tissue. Approximately 10% of IH cases require early treatment. The 2019 American Academy of Pediatrics clinical practice guideline for the management of IHs recommends that primary care clinicians frequently monitor infants with IHs, educate the parents about the clinical course, and refer infants with high-risk IH to IH specialists ideally at 1 month of age. High-risk IHs include those with life-threatening complications, functional impairment, ulceration, associated structural anomalies, or disfigurement. In Korea, IHs are usually treated by pediatric hematology-oncologists with the cooperation of pediatric cardiologists, radiologists, dermatologists, and plastic surgeons. Oral propranolol, a nonselective beta-adrenergic antagonist, is the first-line treatment for IHs at a dosage of 2-3 mg/kg/day divided into 2 daily doses maintained for at least 6 months and often continuing until 12 months of age. Topical timolol maleate solution, a topical nonselective beta-blocker, may be used for small superficial type IHs at a dosage of 1-2 drops of 0.5% gel-forming ophthalmic solution applied twice daily. Pulse-dye laser therapy or surgery is useful for the treatment of residual skin changes after IH involution.
Deep learning (DL) is a subset of machine learning and artificial intelligence that has a deep neural network with a structure similar to the human neural system and has been trained using big data. DL narrows the gap between data acquisition and meaningful interpretation without explicit programming. It has so far outperformed most classification and regression methods and can automatically learn data representations for specific tasks. The application areas of DL in radiation oncology include classification, semantic segmentation, object detection, image translation and generation, and image captioning. This article tries to understand what is the potential role of DL and what can be more achieved by utilizing it in radiation oncology. With the advances in DL, various studies contributing to the development of radiation oncology were investigated comprehensively. In this article, the radiation treatment process was divided into six consecutive stages as follows: patient assessment, simulation, target and organs-at-risk segmentation, treatment planning, quality assurance, and beam delivery in terms of workflow. Studies using DL were classified and organized according to each radiation treatment process. State-of-the-art studies were identified, and the clinical utilities of those researches were examined. The DL model could provide faster and more accurate solutions to problems faced by oncologists. While the effect of a data-driven approach on improving the quality of care for cancer patients is evidently clear, implementing these methods will require cultural changes at both the professional and institutional levels. We believe this paper will serve as a guide for both clinicians and medical physicists on issues that need to be addressed in time.
Kim Mi Sook;Yoo Seoung Yul;Cho Chul Koo;Yoo Hyung Jun;Yang Kwang Mo;Je Young Hoon;Lee Dong Hun;Lee Dong Han;Kim Do Jun
Radiation Oncology Journal
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v.17
no.2
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pp.172-178
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1999
Purpose : To measure the basic structural characteristics of radiation oncology facilities in Korea during 1997 and to compare personnel, equipments and patient loads between Korea and developed countries. Methods and Materials : Mail serveys we conducted in 1998 and data on treatment machines, personnel and peformed new patients were collected. Responses were obtained from the 100 percent of facilities. The consensus data of the whole country were summarized using Microsoft Excel program. Results: In Korea during 1997, 42 facilities delivered megavoltage radiation theraphy with 71 treatment machines, 100 radiation oncologists, 26 medical physicist, 205 technologists and 19,773 new patients. Eighty nine percent of facilities in Korea had linear accelators at least 6 MeV maximum photon energy. Ninety five percent of facilities had simulators while five percent of facilities had no simulator, Ninety one percent of facilities had computer planning systems and eighty three percent of facilities reported that they had a written quality assurance program. Thirty six percent of facilities had only one radiation oncologist and thirty eight percent of facilities had no medical physicists. The median of the distribution of annual patients load of a facility, patients load per a machine, patients load per a radiation oncologist, patients load per a therapist and therapists per a machine in Korea were 348 patients per a year, 263 patients per a machine, 171 patients per a radiation oncologist, 81 patients per a therapist, and 3 therapists per a machine respectively. Conclusions : The whole scale of the radiation oncology departments in Korea was smaller than Japan and USA in population ratio regard. In case of hardware level like linear accelerators, simulators and computer planning systems, there was no big differences between Korea and USA. The patients loads of radiation oncologists and therapists had no significant differences as compared with USA. However, it was desirable to consider the part time system in USA because there were a lot of hospitals which did not employ medical physicists.
$\underline{Purpose}$: An analysis of the infrastructure for radiotherapy in Korea was performed to establish a baseline plan in 2006 for future development. $\underline{Materials\;and\;Methods}$: The data were obtained from 61 radiotherapy centers. The survey covered the number of radiotherapy centers, major equipment and personnel. Centers were classified into technical level groups according to the IAEA criteria. $\underline{Results}$: 28,789 new patients were treated with radiation therapy in 2004. There were 104 megavoltage devices in 61 institutions, which included 96 linear accelerators, two Cobalt 60 units, three Tomotherapy units, two Cyberknife units and one proton accelerator in 2006. Thirty-five high dose rate remote after-loading systems and 20 CT-simulators were surveyed. Personnel included 132 radiation oncologists, 50 radiation oncology residents, 64 medical physicists, 130 nurses and 369 radiation therapy technologists. All of the facilities employed treatment-planning computers and simulators, among these thirty-two percent (20 facilities) used a CT-simulator. Sixty-six percent (40 facilities) used a PET/CT scanner, and 35% (22 facilities) had the capacity to implement intensity modulated radiation therapy. Twenty-five facilities (41%) were included in technical level 3 group (having one of intensity modulated radiotherapy, stereotactic radiotherapy or intra-operative radiotherapy system). $\underline{Conclusion}$: Radiation oncology in Korea evolved greatly in both quality and quantity recently and demand for radiotherapy in Korea is increasing steadily. The information in this analysis represents important data to develop the future planning of equipment and human resources.
Lee, Eonju;Park, Won;Ahn, Sung Hwan;Cho, Jae Ho;Kim, Jin Hee;Cho, Kwan Ho;Choi, Young Min;Kim, Jae-Sung;Kim, Jin Ho;Jang, Hong-Seok;Kim, Young-Seok;Nam, Taek-Keun
Radiation Oncology Journal
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v.36
no.1
/
pp.11-16
/
2018
Purpose: To investigate interobserver variation in target volume delineations for prostate cancer salvage radiotherapy using planning computed tomography (CT) versus combined planning CT and magnetic resonance imaging (MRI). Materials and Methods: Ten radiation oncologists independently delineated a target volume on the planning CT scans of five cases with different pathological status after radical prostatectomy. Two weeks later, this was repeated with the addition of planning MRI. The volumes obtained with CT only and combined CT and MRI were compared, and the effect of the addition of planning MRI on interobserver variability was assessed. Results: There were large differences in clinical target volume (CTV) delineated by each observer, regardless of the addition of planning MRI ($9.44-139.27cm^3$ in CT only and $7.77-122.83cm^3$ in CT plus MRI) and no significant differences in the mean and standard deviation of CTV. However, there were decreases in mean volume and standard deviation as a result of using the planning MRI. Conclusion: This study showed substantial interobserver variation in target volume delineation for salvage radiotherapy. The combination of planning MRI with CT tended to decrease the target volume and the variation.
Background: To investigate the impact of the breast size, shape, maximum heart depth (MDH), and chest wall hypotenuse (the distance connecting middle point of the sternum and the length of lung draw on the selected transverse CT slice) on the volumetric dose to heart with whole breast irradiation (WBI) of left-sided breast cancer patients. Materials and Methods: Fifty-three patients with left-sided breast cancer undergoing adjuvant intensity-modulated radiotherapy (IMRT) were enrolled in the study. The primary breast size and shape, MHD and DCWH (chest wall hypotenuse) were contoured on radiotherapy (RT) planning CT slices. The dose data of hearts were obtained from the dose-volume histograms (DVHs). Data were analyzed by one-way analysis of variance (ANOVA), Student's t-test and linear regression analysis. Results: Breast size was independent of heart dose, whereas breast shape, MHD and DCWH were correlated with heart dose. The shapes of breasts were divided into four types, as the flap type, hemisphere type, cone type and pendulous type with heart mean dose being $491.8{\pm}234.6cGy$, $752.7{\pm}219.0cGy$, $620.2{\pm}275.7cGy$, and $666.1{\pm}238.0cGy$, respectively. The flap type of breasts shows a strong statistically reduction in heart dose, compared to others (p=0.008 for V30 of heart). DCWH and MHD were found to be the most important parameters correlating with heart dose in WBI. Conclusions: More attention should be paid to the heart dose of non-flap type patients. The MHD was found to be the most important parameter to correlate with heart dose in tangential WBI, closely followed by the DCWH, which could help radiation oncologists and physicsts evaluate heart dose and design RT plan in advance.
Background: Soft tissue sarcomas (STS) must be managed with a team involving pathologists, radiologists, surgeons, radiation therapists and medical oncologists. Treatment modalities and demographic charasteristics of Turkish STS were analysed in the current study. Material-Methods: Primary adult STS followed between 1999-2010 in Cukurova University Medical Faculty Department of Medical Oncology were analzied retrospectively Results: Of the total of 498 patients, 238 were male and 260 female. The most seen adult sarcomas were leomyosarcoma (23%). Localization of disease was upper extremity (8.8%), lower extremity (24.7%), head-neck 8.2%, thoracic 8%, retroperitoneal 5.6%, uterine 12.4%, abdominal 10%, pelvic region 3.6 and other regions 10%. Some 13.1% were early stage, 10.2% locally advanced, 8.2% metastatic and 12.2% recurrent disease. Patients were treated with neoadjuvant/adjuvant (12%) or palliative chemotherapy (7.2%) and 11.4% patients did not receive chemotherapy. Surgery was performed as radical or conservative. The most preferred regimen was MAID combination chemotherapy in the rate of 17.6%. The most common metastatic site was lung (18.1%). The overall survival was 45 months (95%CI 30-59), 36 months in men and 55 months in women, with no statistically significant difference (p=0.5). The survival rates were not different between the group of adjuvant and palliative chemotherapy (respectively 28 versus 18 months) (p=0.06), but radical surgery at 37 months was better than 22 months for conservative surgery (p=0.0001). No differences were evident for localization (p=0.152). Locally advanced group had higher overall survival rates (72 months) than other stages (p=0.0001). Conclusion: STS can be treated successfully with surgery, chemotherapy and radiotherapy. The survival rates of Turkish people were higher in locally advanced group; these results show the importance of multimodality treatment approach and radical surgery.
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