Non-colloid-cyst primary brain tumors: A systematic review of unexpected fatality

Atallah, Oday; Badary, Amr; Almealawy, Yasser F.; Sanker, Vivek; Andrew Awuah, Wireko; Abdul-Rahman, Toufik; Alrubaye, Sura N.; Chaurasia, Bipin

doi:10.1016/j.jocn.2023.11.022

Cited by 2 publications

(1 citation statement)

References 76 publications

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“…However, regrettably, their condition deteriorated over subsequent monitoring periods due to malignant like behavior of the tumor. [73][74][75] Due to the rarity of apoplexy cases, little is known about conservative treatment. Given the absence of hydrocephalus, absence of neoplasms and favorable clinical status, it is opted for observation over surgery.…”

Section: Treatment Modalities and Prognosismentioning

confidence: 99%

Pineal Apoplexy: Highlighting the Causes, Treatment, and Outcome

Atallah,

Chaurasia,

Badary

et al. 2024

J Neurol Surg A Cent Eur Neurosurg

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Background Pineal apoplexy, alternatively referred to as pineal hemorrhage or pineal gland hemorrhagic stroke, is an infrequent pathologic condition characterized by bleeding within the pineal gland. In this review, we encompass the primary factors contributing to this uncommon ailment. Methods The retrieval of pertinent research, including patients with pineal apoplexy, was conducted through PubMed, Google Scholar, and Scopus databases. This study exclusively incorporated comprehensive articles written in the English language. The search encompassed the MeSH terms “pineal apoplexy” and “pineal hemorrhage.” Results A total of 41 articles were identified, encompassing a collective sample size of 57 patients. The median age of the patients in the study was 30 years, with a range spanning from 1 to 73 years. There were 27 males, representing 47.4% of the participants. The study identified the most often reported symptoms as headache (49; 86%), nausea/vomiting (19; 33.3%), and Parinaud's syndrome (16; 28.1%). The treatment options encompass several approaches, including open resection, shunting, ventriculostomy, endoscopic aspiration, and conservative care. In the conducted study, a notable number of patients, amounting to 45 cases (78.9%), indicated an amelioration of their symptoms upon their discharge. Conclusion Data from a cohort of 57 cases provide insights into symptoms, lesions, treatments, and outcomes. Management approaches range from conservative measures to surgical interventions, with prognosis hinged on timely intervention. This investigation serves as a valuable resource for clinicians and researchers, underscoring the need for early diagnosis before permanent neurologic dysfunction happens and tailored treatments for optimal outcomes in pineal apoplexy cases.

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Section: Treatment Modalities and Prognosismentioning

confidence: 99%

Pineal Apoplexy: Highlighting the Causes, Treatment, and Outcome

Atallah,

Chaurasia,

Badary

et al. 2024

J Neurol Surg A Cent Eur Neurosurg

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Diagnosis and Classification of Brain Tumors from MRI Images Using the SVM Algorithm

Mehdipor Ghazvini,

Dehlaghi,

Papi

et al. 2024

J Clin Res Paramed Sci

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Background: A brain tumor is one of the most common and fatal neurological diseases that may require surgery. The correct diagnosis of the location and size of the tumor can be a diagnostic aid program for medical robots during surgery, and it also helps doctors formulate a suitable treatment plan for the patient. Objectives: To develop an algorithm based on support vector machine (SVM) for the detection and classification of tumors into benign and malignant types on MRI images. Methods: In this retrospective study, 160 MRI images were obtained from the KAGGLE website. The studied subjects included two groups: Benign tumors and malignant tumors. At first, preprocessing and noise removal were done by comparing four filters: Butterworth, wavelet, ideal, and median. Finally, the SVM algorithm was used to classify brain tumors into benign and malignant. Results: The performance evaluation of the filters showed that the median and wavelet filters had the best performance in removing noise from MRI images. Then, the discrete wavelet transform (DWT) extracted the required features from MRI images and was used as the input of the SVM algorithm. The accuracy, precision and specificity of the proposed algorithm in diagnosing benign and malignant brain tumors were 95%, 88% and 91%. Conclusions: The findings of recent studies show that this algorithm can be used to improve the accurate diagnosis of brain tumors and their types. Combining morphological features can also be a diagnostic tool to increase accuracy in robotic surgeries.

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Non-colloid-cyst primary brain tumors: A systematic review of unexpected fatality

Cited by 2 publications

References 76 publications

Pineal Apoplexy: Highlighting the Causes, Treatment, and Outcome

Pineal Apoplexy: Highlighting the Causes, Treatment, and Outcome

Diagnosis and Classification of Brain Tumors from MRI Images Using the SVM Algorithm

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