ABSTRACT
BACKGROUND: Early detection of T790M mutation in exon 20 of epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) patients with brain metastasis is crucial for optimizing treatment strategies. In this study, we developed radiomics models to distinguish NSCLC patients with T790M-positive mutations from those with T790M-negative mutations using multisequence MR images of brain metastasis despite an imbalanced dataset. Various resampling techniques and classifiers were employed to identify the most effective strategy. METHODS: Radiomic analyses were conducted on a dataset comprising 125 patients, consisting of 18 with EGFR T790M-positive mutations and 107 with T790M-negative mutations. Seventeen first- and second-order statistical features were selected from CET1WI, T2WI, T2FLAIR, and DWI images. Four classifiers (logistic regression, support vector machine, random forest [RF], and extreme gradient boosting [XGBoost]) were evaluated under 13 different resampling conditions. RESULTS: The area under the curve (AUC) value achieved was 0.89, using the SVM-SMOTE oversampling method in combination with the XGBoost classifier. This performance was measured against the AUC reported in the literature, serving as an upper-bound reference. Additionally, comparable results were observed with other oversampling methods paired with RF or XGBoost classifiers. CONCLUSIONS: Our study demonstrates that, even when dealing with an imbalanced EGFR T790M dataset, reasonable predictive outcomes can be achieved by employing an appropriate combination of resampling techniques and classifiers. This approach has significant potential for enhancing T790M mutation detection in NSCLC patients with brain metastasis.
ABSTRACT
BACKGROUND: While magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of patients with brain tumors, it may still be challenging to differentiate glioblastoma multiforme (GBM) from solitary brain metastasis (SBM) due to their similar imaging features. This study aimed to evaluate the features extracted of dual-tree complex wavelet transform (DTCWT) from routine MRI protocol for preoperative differentiation of glioblastoma (GBM) and solitary brain metastasis (SBM). METHODS: A total of 51 patients were recruited, including 27 GBM and 24 SBM patients. Their contrast-enhanced T1-weighted images (CET1WIs), T2 fluid-attenuated inversion recovery (T2FLAIR) images, diffusion-weighted images (DWIs), and apparent diffusion coefficient (ADC) images were employed in this study. The statistical features of the pre-transformed images and the decomposed images of the wavelet transform and DTCWT were utilized to distinguish between GBM and SBM. RESULTS: The support vector machine (SVM) showed that DTCWT images have a better accuracy (82.35%), sensitivity (77.78%), specificity (87.50%), and the area under the curve of the receiver operating characteristic curve (AUC) (89.20%) than the pre-transformed and conventional wavelet transform images. By incorporating DTCWT and pre-transformed images, the accuracy (86.27%), sensitivity (81.48%), specificity (91.67%), and AUC (93.06%) were further improved. CONCLUSIONS: Our studies suggest that the features extracted from the DTCWT images can potentially improve the differentiation between GBM and SBM.
ABSTRACT
BACKGROUND: We hypothesized that patients with head and neck squamous cell carcinoma (HNSCC) with smoking cessation during curative chemoradiotherapy (CRT) had fewer complications and lower tumor progression risks. METHODS: Sixty-three patients with nonmetastatic HNSCC who were smokers at diagnosis (carbon monoxide [CO] breath concentrations ≥3 ppm) and underwent curative CRT were prospectively enrolled. Successful smoking cessation throughout CRT was confirmed by CO breath concentrations <3 ppm at CRT completion. RESULTS: Forty-one patients (65%) successfully discontinued smoking throughout CRT. With a median 33-month follow-up, patients with successful smoking cessation during CRT had significantly fewer, greater, and lower probabilities of grade ≥3 acute toxicities (P = .01), progression-free survival (P = .03), and permanent gastrostomy or tracheostomy (P = .04), respectively, than those continuing smoking throughout CRT. In multivariate analysis, successful smoking cessation during CRT significantly reduced tumor progression risks (hazard ratio: 0.4, P = .05). CONCLUSION: Smoking cessation during curative CRT reduced treatment-related toxicities and tumor progression risks in patients with HNSCC.
Subject(s)
Chemoradiotherapy , Head and Neck Neoplasms/therapy , Smoking Cessation , Squamous Cell Carcinoma of Head and Neck/therapy , Adult , Aged , Chemoradiotherapy/adverse effects , Disease Progression , Female , Humans , Male , Middle Aged , Multivariate Analysis , Prognosis , Prospective Studies , Survival Analysis , Treatment OutcomeABSTRACT
BACKGROUND: The main concerns with radiation therapy for head and neck cancer in human immunodeficiency virus (HIV)-infected patients include limited tumor response and profound mucosal or skin toxicities under severe immunocompromised status. METHODS: In this study, we describe the clinicopathological features, chronological changes in HIV viral loads and CD4 counts, and treatment outcomes of definitive radiotherapy for locally advanced head and neck cancer in an HIV-infected patient. RESULTS: Despite low CD4 counts (80 cells/µL), a combination of highly active antiretroviral therapy (HAART) and definitive concurrent chemoradiotherapy (70 Gy of simultaneously integrated boost intensity-modulated radiotherapy (IMRT), fluorouracil, and leucovorin) was well-tolerated. Grade 3 mucositis and dermatitis were resolved 2 weeks after treatment completion. The patient was alive and remained disease-free 31 months after treatment. CONCLUSION: For patients with HIV diagnosed with locally advanced head and neck cancer, good tolerance and outcome can be achieved with definitive radiotherapy while on HAART.