• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2601-2611
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• 2015

Prostate cancer, with a lifetime prevalence of one in six men, is the second cause of malignancy-related death and the most prevalent cancer in men in many countries. Nowadays, prostate cancer diagnosis is often based on the use of biomarkers, especially prostate-specific antigen (PSA) which can result in enhanced detection at earlier stage and decreasing in the number of metastatic patients. However, because of the low specificity of PSA, unnecessary biopsies and mistaken diagnoses frequently occur. Prostate cancer has various features so prognosis following diagnosis is greatly variable. There is a requirement for new prognostic biomarkers, particularly to differentiate between inactive and aggressive forms of disease, to improve clinical management of prostate cancer. Research continues into finding additional markers that may allow this goal to be attained. We here selected a group of candidate biomarkers including PSA, PSA velocity, percentage free PSA, $TGF{\beta}1$, AMACR, chromogranin A, IL-6, IGFBPs, PSCA, biomarkers related to cell cycle regulation, apoptosis, PTEN, androgen receptor, cellular adhesion and angiogenesis, and also prognostic biomarkers with Genomic tests for discussion. This provides an outline of biomarkers that are presently of prognostic interest in prostate cancer investigation.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.31 no.3
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• pp.97-104
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• 2020

Deep learning (DL) is a kind of machine learning technique that uses artificial intelligence to identify the characteristics of given data and efficiently analyze large amounts of information to perform tasks such as classification and prediction. In the field of neuroimaging of neurodevelopmental disorders, various biomarkers for diagnosis, classification, prognosis prediction, and treatment response prediction have been examined; however, they have not been efficiently combined to produce meaningful results. DL can be applied to overcome these limitations and produce clinically helpful results. Here, we review studies that combine neurodevelopmental disorder neuroimaging and DL techniques to explore the strengths, limitations, and future directions of this research area.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.11-16
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• 2014

Accurate diagnosis and proper monitoring of cancer patients remain important obstacles for successful cancer treatment. The search for cancer biomarkers can aid in more accurate prediction of clinical outcome and may also reveal novel predictive factors and therapeutic targets. One such prognostic marker seems to be FOXA1. Many studies have shown that FOXA1 is strongly expressed in a vast majority of cancers, including breast cancer, in which high expression is associated with a good prognosis. In this review, we summarize the role of this transcription factor in the development and prognosis of breast cancer in the hope of providing insights into utility of FOXA1 as a novel biomarker.

• The Korean Journal of Nuclear Medicine
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• v.34 no.5
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• pp.426-432
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• 2000

After surgical operation in patients with arteriovenous malformation (AVM), normal pressure perfusion breakthrough (NPPB) is one of the major complications. Brain perfusion SPECT with acetazolamide stress was known to be useful to evaluate the vascular reserve in several neurological and neurosurgical conditions. The authors performed acetazolamide brain perfusion SPECT in patients with AVM and compared the brain perfusion in the post-operative clinical courses. The acetazolamide brain perfusion SPECT was helpful in defining the prognosis of the patients with AVM. We describe 4 patients with AVM who had acetazolamide brain perfusion SPECT to examine the prognosis.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.sup1
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• pp.101-109
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• 2008

Cervix cancer is one of common gynecological cancers in the world, and staged with FIGO or TNM system. However, these clinical staging systems lack information about lymph node or distant metastases, thus imaging modalities are considered to make an appropriate therapeutic plan and enhance overall survival rate. In this context, FDG PET is recommended to pre-treatment stating and prognosis prediction, for it could noninvasively evaluate the status of lymph nodes, especially abdominal paraaortic nodes which are closely related with prognosis. Moreover, the degree of FDG uptake is correlated with prognosis. Although there is no consistent method for surveillance of cervix cancer, FDG PET seems a very important tool in detecting tumor recurrence because it is much more advantageous than conventional imaging modalities such as MRI for discerning recurrent tumor from fibrosis caused by radiation or surgery. Furthermore, FDG PET could be used to evaluate treatment response. On the other hand, recently introduced PET/CT is expected to play an ancillary role to FIGO staging by adding anatomical information, and enhance diagnostic performance of PET by decreasing false positive findings.

• Smart Media Journal
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• v.9 no.4
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• pp.126-133
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• 2020

The treatment policy and prognosis are determined based on the final stage of lung cancer patients. The final stage of lung cancer patients is determined based on the T, N, and M stage classification table provided by the American Cancer Society (AJCC). However, the final stage of AJCC has limitations in its use for various fields such as patient treatment, prognosis and survival days prediction. In this paper, clustering algorithm which is one of non-supervised learning algorithms was assessed in order to check whether using only T, N, M stages with a data science method is effective for classifying the group of patients in the aspect of survival days. The final stage groups and T, N, M stage clustering groups of lung cancer patients were compared by using the cox proportional hazard model. It is confirmed that the accuracy of prediction of survival days with only T, N, M stages becomes higher than the accuracy with the final stages of patients. Especially, the accuracy of prediction of survival days with clustering of T, N, M stages improves when more or less clusters are analyzed than the seven clusters which is same to the number of final stage of AJCC.

• Journal of the korean academy of Pediatric Dentistry
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• v.23 no.3
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• pp.624-630
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• 1996

Anterior openbite is defined as the lack of contacts between the functional occluding teeth on vertical line at centric occlusion and classified into functional and skeletal anterior openbite based on its causes and characteristics. Anterior openbite causes masticatory, speech, and esthetic problems in the growing children and difficulties in diagnosis, treatment, and the prediction of its prognosis. We are reporting on the treatment of anterior openbite in the growing children and the results follow as : 1. In the growing children with anterior openbite, the overbite could be increased by the treatment according to its causes and characteristics. 2. The prognosis is not determined by the presence or severity of oral habit but the skeletal tendency of the patient.

• Korean Journal of Radiology
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• v.22 no.1
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• pp.23-40
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• 2021

In pancreatic cancer, imaging plays an essential role in surveillance, diagnosis, resectability evaluation, and treatment response evaluation. Pancreatic cancer surveillance in high-risk individuals has been attempted using endoscopic ultrasound (EUS) or magnetic resonance imaging (MRI). Imaging diagnosis and resectability evaluation are the most important factors influencing treatment decisions, where computed tomography (CT) is the preferred modality. EUS, MRI, and positron emission tomography play a complementary role to CT. Treatment response evaluation is of increasing clinical importance, especially in patients undergoing neoadjuvant therapy. This review aimed to comprehensively review the role of imaging in relation to the current treatment strategy for pancreatic cancer, including surveillance, diagnosis, evaluation of resectability and treatment response, and prediction of prognosis.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2034-2051
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• 2021

Metabolic encephalopathy is a critical condition that can be challenging to diagnose. Imaging provides early clues to confirm clinical suspicions and plays an important role in the diagnosis, assessment of the response to therapy, and prognosis prediction. Diffusion-weighted imaging is a sensitive technique used to evaluate metabolic encephalopathy at an early stage. Metabolic encephalopathies often involve the deep regions of the gray matter because they have high energy requirements and are susceptible to metabolic disturbances. Understanding the imaging patterns of various metabolic encephalopathies can help narrow the differential diagnosis and improve the prognosis of patients by initiating proper treatment regimen early.

• Clinical and Experimental Pediatrics
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• v.63 no.5
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• pp.164-170
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• 2020

The prognosis of patients who are comatose after resuscitation remains uncertain. The accurate prediction of neurological outcome is important for management decisions and counseling. A neurological examination is an important factor for prognostication, but widely used sedatives alter the neurological examination and delay the response recovery. Additional studies including electroencephalography, somatosensory-evoked potentials, brain imaging, and blood biomarkers are useful for evaluating the extent of brain injury. This review aimed to assess the usefulness of and provide practical prognostic strategy for pediatric postresuscitation patients. The principles of prognostication are that the assessment should be delayed until at least 72 hours after cardiac arrest and the assessment should be multimodal. Furthermore, multiple factors including unmeasured confounders in individual patients should be considered when applying the prognostication strategy.