Frontiers in oncology
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Frontiers in oncology · Jan 2020
Stereotactic Cavity Irradiation or Whole-Brain Radiotherapy Following Brain Metastases Resection-Outcome, Prognostic Factors, and Recurrence Patterns.
Introduction: Following the resection of brain metastases (BM), whole-brain radiotherapy (WBRT) is a long-established standard of care. Its position was recently challenged by the less toxic single-session radiosurgery (SRS) or fractionated stereotactic radiotherapy (FSRT) of the resection cavity, reducing dose exposure of the healthy brain. Patients and Methods: We analyzed 101 patients treated with either SRS/FSRT (n = 50) or WBRT (n = 51) following BM resection over a 5-year period. ⋯ Conclusion: This is the first propensity score-adjusted direct comparison of SRS/FSRT and WBRT following the resection of BM. Patients receiving SRS/FSRT showed longer OS and LC compared to WBRT. Future analyses will address the optimal choice of safety margin, dose and fractionation for postoperative stereotactic RT of the resection cavity.
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Frontiers in oncology · Jan 2020
Development of a Novel, Multi-Parametric, MRI-Based Radiomic Nomogram for Differentiating Between Clinically Significant and Insignificant Prostate Cancer.
Objectives: To develop and validate a predictive model for discriminating clinically significant prostate cancer (csPCa) from clinically insignificant prostate cancer (ciPCa). Methods: This retrospective study was performed with 159 consecutively enrolled pathologically confirmed PCa patients from two medical centers. The dataset was allocated to a training group (n = 54) and an internal validation group (n = 22) from one center along with an external independent validation group (n = 83) from another center. ⋯ Then, the combination nomogram incorporating the radiomic signature and ADC value demonstrated a favorable classification capability with the AUC of 0.95 (training group), 0.93 (internal validation group), and 0.84 (external validation group). Appreciable clinical utility of this model was illustrated using the decision curve analysis for the nomogram. Conclusions: The nomogram, incorporating radiomic signature and ADC value, provided an individualized, potential approach for discriminating csPCa from ciPCa.
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Frontiers in oncology · Jan 2020
Radiomics Nomogram of DCE-MRI for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer.
This study aimed to establish and validate a radiomics nomogram based on dynamic contrast-enhanced (DCE)-MRI for predicting axillary lymph node (ALN) metastasis in breast cancer. ⋯ The MRI-based radiomics nomogram model could be used to preoperatively predict the ALN metastasis of breast cancer.
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Frontiers in oncology · Jan 2020
A Novel Nomogram Model Based on Cone-Beam CT Radiomics Analysis Technology for Predicting Radiation Pneumonitis in Esophageal Cancer Patients Undergoing Radiotherapy.
We quantitatively analyzed the characteristics of cone-beam computed tomography (CBCT) radiomics in different periods during radiotherapy (RT) and then built a novel nomogram model integrating clinical features and dosimetric parameters for predicting radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC). ⋯ The radiomics model based on early lung CBCT is a potentially valuable tool for predicting RP. V5, MLD, and tumor stage have certain predictive effects for RP. The developed nomogram model has a better prediction ability than any of the other predictors and can be used as a quantitative model to predict RP.
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Frontiers in oncology · Jan 2020
Machine Learning-Based Radiomics Nomogram Using Magnetic Resonance Images for Prediction of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Patients.
Purpose: The construction and validation of a radiomics nomogram based on machine learning using magnetic resonance image (MRI) for predicting the efficacy of neoadjuvant chemotherapy (NACT) in patients with breast cancer (BCa). Methods: This retrospective investigation consisted of 158 patients who were diagnosed with BCa and underwent MRI before NACT, of which 33 patients experienced pathological complete response (pCR) by the postoperative pathological examination. The patients with BCa were divided into the training set (n = 110) and test set (n = 48) randomly. ⋯ The decision curve indicated the clinical usefulness of our nomogram. Conclusion: Our radiomics nomogram showed good discrimination in patients with BCa who experience pCR after NACT. The model may aid physicians in predicting how specific patients may respond to BCa treatments in the future.