Radiotherapy Protocol of Central Neurocytoma for Resource-limited Settings in the Absence of Official Guidelines: A Case Report and Review of the Literature
Bibliographic record
Abstract
BACKGROUND: Central neurocytoma (CN) is one of the rarest brain tumors which can cause considerable threats to the patient. Studies and trials regarding its treatment are scarce, and no official guidelines are dedicated to this disease. The main principle of treatment generally consists of surgery and radiotherapy. The choice of radiotherapy is divided into conventional fractionated radiotherapy and stereotactic radiosurgery (SRS). However, access to SRS in developing countries such as Indonesia is still limited. AIM: We report a case delineating the timeline and process of treatment in CN with a review of the literature. METHODS: We report the case of a 29-year-old woman with a solid inhomogeneous mass (AP 5.63 × CC 5.36 × LL 5.16 cm) in the right ventricle, attached to the septum pellucidum, as displayed on the magnetic resonance imaging (MRI). The patient had been vomiting for the past three weeks and presented with bidirectional horizontal nystagmus. RESULTS: Cognitive evaluation with Montreal Cognitive Assessment (MoCA-Ina) demonstrated a mild cognitive impairment. Biopsy was performed, and pathology analysis revealed some cells with fibrillary background and some with a honeycomb-like appearance. The immunohistochemistry staining showed positive results with synaptophysin and neuronal nuclear protein. According to the WHO classification of the central nervous system tumors, the profile favored CN Grade II. Subtotal resection (STR) was performed to reduce the tumor mass, which was measured with MRI 2-month post-surgery (AP 4.09 × CC 3.01 × LL 4.13 cm) and then followed by an external radiation program. Using intensity modulated radiation therapy (IMRT), a total dose of 54 Gy was given in 27 fractions, with the average planning target volume of 54.3 Gy. There was a minuscule reduction in tumor mass as seen in post-radiotherapy MRI (AP 4.00 × CC 3.86 × LL 3.63 cm). After the last session and at the 18-month follow-up, the patient did not have any complaints or abnormalities during clinical assessment. Reevaluation using MoCA-Ina showed an improved cognitive function. CONCLUSIONS: In line with recent evidence, we demonstrated that STR followed by IMRT with the dosage of 54 Gy in 27 fractions was a feasible treatment strategy for CN that resulted in cognitive improvement, with no side effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".