• 대한한방내과학회지
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• 제39권5호
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• pp.955-963
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• 2018

This case report documents one patient with acute cortical cisternal subarachnoid hemorrhage. The patient had a central pain in the right upper limb and was treated with traditional Korean medicine in the Oriental Hospital of Se-Myung University. The patient was treated with Yangkyuksanwha-tang and acupuncture and followed up with a symptoms checklist and brain computed tomography (CT) scan. Initially, the frequency of right upper extremity pain was 18 per day, but this disappeared after treatment. CT follow up showed that subarachnoid hemorrhage was resolved. There were no side effects associated with treatment. This case shows that traditional Korean medicine treatment is effective in treating acute cortical subarachnoid hemorrhage.

• Journal of Korean Neurosurgical Society
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• 제58권6호
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• pp.547-549
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• 2015

Acute subdural hematoma (SDH) of arterial origin is rare, especially SDH associated with an arteriovenous malformation (AVM) is extremely rare. The authors report a case of acute spontaneous SDH due to rupture of a tiny cortical AVM. A 51-year-old male presented with sudden onset headache and mentality deterioration without a history of trauma. Brain CT revealed a large volume acute SDH compressing the right cerebral hemisphere with subfalcine and tentorial herniation. Emergency decompressive craniectomy was performed to remove the hematoma and during surgery a small (5 mm sized) conglomerated aciniform mass with two surrounding enlarged vessels was identified on the parietal cortex. After warm saline irrigation of the mass, active bleeding developed from a one of the vessel. The bleeding was stopped by coagulation and the vessels were removed. Histopathological examination confirmed the lesion as an AVM. We concluded that a small cortical AVM existed at this area, and that the cortical AVM had caused the acute SDH. Follow up conventional angiography confirmed the absence of remnant AVM or any other vascular abnormality. This report demonstrates rupture of a cortical AVM is worth considering when a patient presents with non-traumatic SDH without intracerebral hemorrhage or subarachnoid hemorrhage.

• Journal of Korean Neurosurgical Society
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• 제46권2호
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• pp.93-98
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• 2009

Objective: Although prophylactic antiepileptic drug (AED) use in patients with aneurysmal subarachnoid hemorrhage (SAH) is a common practice, lack of uniform definitions and guidelines for seizures and AEDs rendered this prescription more habitual instead of evidence-based manner. We herein evaluated the incidence and predictive factors of seizure and complications about AED use. Methods: From July 1999 to June 2007, data of a total of 547 patients with aneurysmal SAH who underwent operative treatments were reviewed. For these, the incidence and risk factors of seizures and epilepsy were assessed, in addition to complications of AEDs. Results: Eighty-three patients (15.2%) had at least one seizure following SAH. Forty-three patients (79%) had onset seizures, 34 (6.2%) had perioperative seizures, and 17 (3.1%) had late epilepsy. Younger age (< 40 years), poor clinical grade, thick hemorrhage, acute hydrocephalus, and rebleeding were related to the occurrence of onset seizures. Cortical infarction and thick hemorrhage were independent risk factors for the occurrence of late epilepsy. Onset seizures were not predictive of late epilepsy. Moreover, adverse drug effects were identified in 128 patients (23.4%) with AEDs. Conclusion: Perioperative seizures are not significant predictors for late epilepsy. Instead, initial amount of SAH and surgery-induced cortical damage should be seriously considered as risk factors for late epilepsy. Because AEDs can not prevent early postoperative seizures (< 1 week) and potentially cause unexpected side effects, long-term use should be readjusted in high-risk patients.

• Journal of Korean Neurosurgical Society
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• 제46권3호
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• pp.215-220
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• 2009

Objective : Intraoperative ventriculostomy is widely adopted to make the slack brain. However, there are few reports about hemorrhagic or parenchymal injuries after ventriculostomy. We tried to analyze and investigate the incidence of these complications in a consecutive series of patients with aneurysmal subarachnoid hemorrhage (SAH). Methods : From September 2006 to June 2007, 43 patients underwent surgical clipping for aneurysmal SAH at our hospital. Among 43 patients, we investigated hemorrhagic or parenchymal injuries after intraoperative ventriculostomy using postoperative computed tomographic scan in 26 patients. After standard pterional craniotomy, ventriculostomy catheter was inserted perpendicular to the cortical surface along the bisectional imaginary line from Paine's point. Results : Hemorrhagic injuries were detected in 12 of 26 patients (46.2%). Mean systolic blood pressure during anesthesia was with in statistically significant parameter related to hemorrhage (p=0.006). On the other hand, parenchymal injuries were detected in 11 of 26 patients (42.3%). Female and the amount of infused mannitol during anesthesia showed statistically significant parameters related to parenchymal injury (p=0.005, 0.04, respectively). However, there were no ventriculostomy-related severe complications. Conclusion : In our series, hemorrhagic or parenchymal injuries after intraoperative ventriculostomy occurred more commonly than previously reported series in aneurysmal SAH patients. Although the clinical outcomes of complications are generally favorable, neurosurgeon must keep in mind the frequent occurrence of brain injury after intraoperative ventriculostomy in the acute stage of aneurysmal SAH.

• Journal of Korean Neurosurgical Society
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• 제29권1호
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• pp.108-112
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• 2000

Objective : Many authors suggest that patients with traumatic subarachnoid hemorrhage(tSAH) visible on first CT after heve injury had a significantly worse prognosis than patients who do not. The aim of this study is to identify patients with tSAH who present with a bad prognosis by reviewing their clinicoradiological features and plan appropriate treatments. Patients and Methods : We reviewed and analysed the factors that influenced discharge outcomes in 172 patients with tSAH for a 3-year period. The outcome was divided into good(good recovery and moderate disability of glasgow outcome scale) and good(severe disability, vegetative state and death). Results : A regression analysis of statistical significant factors(p<0.05) among the clinical and CT features ranked them by descending order of contribution to Glasgow Outcome Scale(GOS) scores at the time of discharge from acute hospitalization as follows 1) clinical : admission Glasgow Coma Scale(GCS), hypotension, CT grade, abnormal APTT, skull fracture, hyperglycemia(>160mg/dl), hypoxia, operation, 2) CT : basal cistern effacement(BCE), mass lesion, cortical sulcal effacement(CSE), midline shift. Conclusion : We have also experienced that the CT grading scale proposed by Green et al is a simple and useful prognostic factor. The authors believe that the patients with high CT grade need adjuvant therapies as of well surgery but it seems mandatory to consider early identification and correction of hypotension, hyperglycemia, and hypoxia in emergency setting.

• Investigative Magnetic Resonance Imaging
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• 제5권2호
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• pp.149-154
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• 2001

목적 : 급성 거미막하 출혈의 진단에 있어 CT와 비교하여 fluid-attenuated inversion-recovery (FLAIR) MR영상의 유용성을 평가하고자 하였다. 대상 및 방법 : 증상 발생 3일 이내에 비조영 CT와 FLAIR MR영상을 모두 얻었던 28명의 급성 지주막하 출혈 환자를 대상으로 하였다. 거미막하 공간을 피질구, 실비우스열구, 기저조, 후두와의 4부위로 나누어 각 부위 별로 CT와 FLAIR영상에서 출혈이 보이는 정도를 0(출혈 없음), 1(출혈 의심), 2(뚜렷한 출혈)의 점수로 구분하여 평가하였다. 또한 이들 28명 환자와 대조군 35명의 FLAIR영상을 비교하여 거미막하 공간의 고신호 강도를 기준으로 출혈의 유무를 판정할 경우, FLAIR영상의 민감도, 특이도 및 진단적 정확도를 평가하였다. 결과 : FLAIR영상에서 급성 거미막하 출혈은 모든 환자에서 뇌척수액이나 뇌 실질보다 고신호 강도를 보여 100%의 발견율을 보였다. CT와 비교하여 피질구($1.11{\pm}0.80$ vs $0.70{\pm}0.83$: p(0.05)와 후두와($1.41{\pm}0.74$ vs $0.78{\pm}0.80$: p(0.05)에서 FLAIR영상이 CT보다 통계적으로 유의하게 우수하였다 FLAIR영상에서 거미막하 공간의 고신호 강도를 기준으로 거미막하 출혈 유무를 평가한 결과에서 100%의 민감도, 특이도 및 진단적 정확도를 보였다. 결론 급성 거미막하 출혈의 진단에 FLAIR MR영상은 매우 유용하며, 특히 출혈의 양이 소량인 경우와 후두와의 출혈을 진단하는데 CT보다 우수하다.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.