Stereotactic Radiosurgery as Treatment for Brain Metastases: An Update

Pena-Pino, Isabela; Chen, Clark C.

doi:10.1055/s-0043-1769754

Cited by 5 publications

(5 citation statements)

References 113 publications

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Section: Discussionmentioning

confidence: 99%

“…The decision to perform a biopsy on brain lesions in lung cancer patients is not standardized and relies on various factors, such as lesion characteristics, neurological symptoms, overall health status, and treatment planning [7]. Brain lesions devoid of atypical features or neurological symptoms may forego a biopsy, and treatment determinations are predominantly based on imaging characteristics [6,7]. However, in this specific case, the patient's persistent headache coupled with the detection of a growing lesion prompted the decision to conduct a biopsy, ultimately disclosing a diagnosis of neurocysticercosis.…”

Section: Discussionmentioning

confidence: 99%

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Coexistence of Lung Cancer and Neurocysticercosis: A Rare Case

Nguyen,

Puthillath

2024

Cureus

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Lung cancer with brain metastasis has a high morbidity and mortality worldwide. Neurocysticercosis is a parasitic infection commonly found in regions with poor sanitation. We present a case with the coexistence of lung cancer and neurocysticercosis. A 57-year-old Caucasian female, with a history of secondhand smoke exposure, presented with a cough. Further evaluation revealed a lesion in the right upper lobe of the lung on a CT scan, a frontal lobe lesion on brain MRI, and hypermetabolic lymph nodes on a PET scan. Biopsies confirmed invasive moderately differentiated adenocarcinoma, indicating stage 4 lung cancer with a solitary brain metastasis. The patient underwent stereotactic radiosurgery for the brain lesion and subsequently received chemoradiation therapy. Upon completion of therapy, the patient showed improvement in both lung and brain lesions. Durvalumab maintenance therapy was initiated. However, a follow-up MRI of the brain revealed a new lesion in the right lateral ventricle. Stereotactic radiosurgery was performed to target this lesion. Five months later, a repeat MRI showed growth of the brain lesion. Given the atypical image finding, a biopsy of the right lateral ventricle lesion was performed, revealing an unexpected diagnosis of calcified parenchymal neurocysticercosis. The patient was referred to an infectious disease specialist who started the patient on dexamethasone without antiparasitic treatment. The co-occurrence of metastatic lung cancer to the brain and neurocysticercosis presents significant diagnostic and therapeutic complexities. Despite stereotactic radiosurgery, the patient's neurologic symptoms failed to improve, and subsequent radiographic assessments yielded inconclusive results. Consequently, a brain biopsy was performed, deviating from the usual practice in cancer management, revealing the unexpected presence of neurocysticercosis. This unforeseen diagnosis underscores the critical significance of contemplating alternative etiologies in patients exhibiting atypical clinical manifestations, particularly in regions devoid of prevalent parasitic infections. This case highlights the challenges in identifying and managing complex cases involving lung cancer and neurocysticercosis, where treatment decisions must balance the need for oncologic control and the management of parasitic infection.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Coexistence of Lung Cancer and Neurocysticercosis: A Rare Case

Nguyen,

Puthillath

2024

Cureus

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“…Shorter intervals between diagnosis and SRS may be associated with more favorable outcomes, suggesting that prompt initiation of SRS after diagnosis could contribute to improved survival rates. Smaller tumor volumes may correlate with greater OS and PFS outcomes, highlighting the importance of accurately defining and targeting tumor boundaries during SRS [ 26 ]. Optimal margin doses play a crucial role in improving OS and PFS, with deviations potentially impacting outcomes [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

“…The study cohort comprised eight (80%) pediatric patients (ages 3-18) and two (20%) adult patients (ages . The median age at the time of SRS was 13 years, with the pediatric group having a median age of 12 years (range: 9-16) and the adult group with a median age of 27 years (range: [25][26][27][28][29]. Nine (90%) patients underwent surgical resection prior to SRS, with histological confirmation of WHO grade IV tumors.…”

Section: Patient Selection and Characteristicsmentioning

confidence: 99%

The Role of CyberKnife Stereotactic Radiosurgery in Recurrent Cranial Medulloblastomas across Pediatric and Adult Populations

Yoo,

Marianayagam,

Park

et al. 2024

JCM

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Background/Objectives: Medulloblastoma is the most common malignant brain tumor in children. In recent decades, the therapeutic landscape has undergone significant changes, with stereotactic radiosurgery (SRS) emerging as a promising treatment for recurrent cases. Our study provides a comprehensive analysis of the long-term efficacy and safety of SRS in recurrent medulloblastomas across both pediatric and adult patients at a single institution. Methods: We retrospectively reviewed the clinical and radiological records of patients who underwent CyberKnife SRS for recurrent cranial medulloblastomas at our institution between 1998 and 2023. Follow-up data were available for 15 medulloblastomas in 10 patients. The cohort comprised eight pediatric patients (ages 3–18) and two adult patients (ages 19–75). The median age at the time of SRS was 13 years, the median tumor volume accounted for 1.9 cc, the median biologically equivalent dose (BED) was 126 Gy, and the single-fraction equivalent dose (SFED) was 18 Gy. The SRS was administered at 75% of the median isodose line. Results: Following a median follow-up of 39 months (range: 6–78), 53.3% of the medulloblastomas progressed, 13.3% regressed, and 33.3% remained stable. The 3-year local tumor control (LTC) rate for all medulloblastomas was 65%, with lower rates observed in the adult cohort (50%) and higher rates in pediatric patients (67%). The 3-year overall survival (OS) rate was 70%, with significantly higher rates in pediatric patients (75%) compared to adult patients (50%). The 3-year progression-free survival (PFS) rate was 58.3%, with higher rates in pediatric patients (60%) compared to adult patients (50%). Two pediatric patients developed radiation-induced edema, while two adult patients experienced radiation necrosis at the latest follow-up, with both adult patients passing away. Conclusions: Our study provides a complex perspective on the efficacy and safety of CyberKnife SRS in treating recurrent cranial medulloblastomas across pediatric and adult populations. The rarity of adverse radiation events (AREs) underscores the safety profile of SRS, reinforcing its role in enhancing treatment outcomes. The intricacies of symptomatic outcomes, intertwined with factors such as age, tumor location, and prior surgeries, emphasize the need for personalized treatment approaches. Our findings underscore the imperative for ongoing research and the development of more refined treatment strategies for recurrent medulloblastomas. Given the observed disparities in treatment outcomes, a more meticulous tailoring of treatment approaches becomes crucial.

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“…In SRS and SRT, the delivered radiation is confined to the lesion and there is a rapid dose fall-off at the edge of the treatment volume. Since the radiation dose is not delivered to the healthy brain tissue, there is a reduced likelihood of posttreatment neurocognitive decline compared to WBRT [9].…”

Section: Introductionmentioning

confidence: 99%

Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features

Kanakarajan,

Baene,

Hanssens

et al. 2024

Preprint

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Background and purpose: Timely identification of Local Failure (LF) after stereotactic radiosurgery offers the opportunity for appropriate treatment modifications that may result in improved treatment outcomes, patient survival, and quality of life. Previous studies showed that the addition of either radiomics or deep learning features to clinical features increased the accuracy of the models in predicting Local Control (LC) of brain metastases after stereotactic radiosurgery. To date, however, no study combined both radiomics and deep learning features together with clinical features to develop machine learning algorithms to predict LC of brain metastases. In this study, we examined whether a model trained with a combination of all these features could predict LC better than models trained with only a subset of these features. Materials and methods: Pre-treatment brain MRIs and clinical data were collected retrospectively for 129 patients at the Gamma Knife Center of Elisabeth-TweeSteden Hospital (ETZ), Tilburg, The Netherlands. The patients were split into 103 patients for training and 26 patients for testing. The segment-based radiomics features were extracted using the radiomics feature extractor of the python radiomics package. The deep learning features were extracted using a fine-tuned 3D ResNet model and then combined with the clinical and radiomics features. A Random Forest classifier was trained with the training data set and then tested with the test data set. The performance was compared across 4 different models trained with clinical features only, clinical and radiomics features, clinical and deep learning features, and clinical, radiomics and deep learning features. Results: The prediction model with only clinical variables provided an Area Under the receiver operating characteristic Curve (AUC) of 0.82 and an accuracy of 75.6%. The prediction model with the combination of clinical and radiomics features demonstrated an AUC of 0.880 and an accuracy of 83.3% whereas the prediction model with the combination of clinical and deep learning features demonstrated an AUC of 0.863 and an accuracy of 78.3%. The best prediction performance was associated with the model that combined the clinical, radiomics and deep learning features with an AUC of 0.886 and 87% accuracy. Conclusion: Machine learning models trained on radiomics features and deep learning features combined with patient characteristics show good potential to predict LC after stereotactic radiosurgery with high accuracy. The promising findings from this study demonstrate the potential for early prediction of stereotactic radiosurgery outcome for brain metastasis prior to treatment initiation and might offer the opportunity for appropriate treatment modifications that may result in improved treatment outcomes, patient survival, and quality of life.

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Stereotactic Radiosurgery as Treatment for Brain Metastases: An Update

Cited by 5 publications

References 113 publications

Coexistence of Lung Cancer and Neurocysticercosis: A Rare Case

Coexistence of Lung Cancer and Neurocysticercosis: A Rare Case

The Role of CyberKnife Stereotactic Radiosurgery in Recurrent Cranial Medulloblastomas across Pediatric and Adult Populations

Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features

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