Purpose
To investigate whether imaging features from pretreatment planning CT scans are associated with overall survival (OS), recurrence‐free survival (RFS), and loco‐regional recurrence‐free ...survival (LR‐RFS) after stereotactic body radiotherapy (SBRT) among nonsmall‐cell lung cancer (NSCLC) patients.
Patients and methods
A total of 92 patients (median age: 73 yr) with stage I or IIA NSCLC were qualified for this study. A total dose of 50 Gy in five fractions was the standard treatment. Besides clinical characteristics, 24 “semantic” image features were manually scored based on a point scale (up to 5) and 219 computer‐derived “radiomic” features were extracted based on whole tumor segmentation. Statistical analysis was performed using Cox proportional hazards model and Harrell's C‐index, and the robustness of final prognostic model was assessed using tenfold cross validation by dichotomizing patients according to the survival or recurrence status at 24 months.
Results
Two‐year OS, RFS and LR‐RFS were 69.95%, 41.3%, and 51.85%, respectively. There was an improvement of Harrell's C‐index when adding imaging features to a clinical model. The model for OS contained the Eastern Cooperative Oncology Group (ECOG) performance status Hazard Ratio (HR) = 2.78, 95% Confidence Interval (CI): 1.37–5.65, pleural retraction (HR = 0.27, 95% CI: 0.08–0.92), F2 (short axis × longest diameter, HR = 1.72, 95% CI: 1.21–2.44) and F186 (Hist‐Energy‐L1, HR = 1.27, 95% CI: 1.00–1.61); The prognostic model for RFS contained vessel attachment (HR = 2.13, 95% CI: 1.24–3.64) and F2 (HR = 1.69, 95% CI: 1.33–2.15); and the model for LR‐RFS contained the ECOG performance status (HR = 2.01, 95% CI: 1.12–3.60) and F2 (HR = 1.67, 95% CI: 1.29–2.18).
Conclusions
Imaging features derived from planning CT demonstrate prognostic value for recurrence following SBRT treatment, and might be helpful in patient stratification.
Introduction Background: Recurrence after initial resection of advanced gastroinstestinal stromal tumors (GIST) is common despite tyrosine kinase inhibitor (TKI) therapy. Appropriate management of ...patients with recurrent GIST is not well defined. Our aim was to identify predictive factors associated with outcome in this population. Methods We identified patients (pts) with advanced/recurrent GIST who underwent resection from our institutional database from 1999-2009. Significant variables for recurrence and survival were analyzed. Results Of the 193 pts with GIST, 78 pts (46.4%) underwent treatment for recurrent/advanced GIST with a median follow up of 38 months (0.3-61). Final margin after initial primary resection was R0/R1 in 60 pts (77%) and R2 in 18 pts (23%). Thirty-eight pts (49%) received adjuvant TKI therapy. Age, gender, tumor size, mitotic rate or adjuvant TKI therapy were not associated with survival on univariate analysis, whereas stage at initial diagnosis (p=0.0015), initial resection margin (p<0.0001), presence of multifocal disease (p=0.002), >2 procedures for recurrence (p=0.04), and TKI resistance (p<0.0001) were significant. Resistance to TKI therapy (p=0.04, 95% CI 1.0-5.6) and incomplete resection at the time of initial primary GIST resection (p=0.002, 95% CI 1.6-9.6) were independently associated with reduced survival on multivariate analysis. Conclusions Incomplete initial resection and development of resistance are independent predictors of survival in patients with advanced or recurrent GIST. Selection of patients for resection versus continuing TKI therapy in the setting of recurrence requires a multidisciplinary approach. Reoperation should be reserved for TKI response and for those which complete resection of the recurrence is possible.
The objective of this research focuses on the development of a statistical methodology able to answer the question of whether variation in the intake of sulfur amino acids (SAA) affects the metabolic ...process. Traditional approaches, which evaluate specific biomarkers after a series of preprocessing procedures, have been criticized as not being fully informative, as well as inappropriate for translation of methodology. Rather than focusing on particular biomarkers, our proposed methodology involves the multifractal analysis that measures the inhomogeneity of regularity of the proton nuclear magnetic resonance (1H-NMR) spectrum by wavelet-based multifractal spectrum. With two different statistical models (Model-I and Model-II), three different geometric features of the multifractal spectrum of each 1H-NMR spectrum (spectral mode, left slope, and broadness) are employed to evaluate the effect of SAA and discriminate 1H-NMR spectra associated with different treatments. The investigated effects of SAA include group effect (high and low doses of SAA), depletion/repletion effect, and time over data effect. The 1H-NMR spectra analysis outcomes show that group effect is significant for both models. The hourly variation in time and depletion/repletion effects does not show noticeable differences for the three features in Model-I. However, these two effects are significant for the spectral mode feature in Model-II. The 1H-NMR spectra of the SAA low groups exhibit highly regular patterns with more variability than that of the SAA high groups for both models. Moreover, the discriminatory analysis conducted using the support vector machine and the principal components analysis shows that the 1H-NMR spectra of SAA high and low groups can be easily discriminatory for both models, while the spectra of depletion and repletion within these groups are discriminatory for Model-I and Model-II. Therefore, the study outcomes imply that the amount of SAA is important and that SAA intake affects mostly the hourly variation of the metabolic process and the difference between depletion and repletion each day. In conclusion, the proposed multifractal analysis of 1H-NMR spectra provides a novel tool to investigate metabolic processes.
To describe the characteristics of the wheelchairs, the users, and their wheelchair use among persons newly prescribed a manual wheelchair.
Cohort study.
Veterans Affairs teaching hospital.
...Ninety-nine consecutive, cognitively intact veterans prescribed a manual wheelchair.
Not applicable.
Self-reported difficulty transferring into and propelling the wheelchair; and bathroom mobility method.
Study patients had a mean age of 66 and a mean of 10 comorbid medical conditions. Parkinsonism, osteoporosis, joint replacement, and amputation were uncommon (<30% of patients), but had a high impact on need for a wheelchair (when present were reported by >50% of patients as causing need for a wheelchair). Falls and arthritis were common (>50% of patients) and highly impacted need for a wheelchair. At 1 month, over 30% of patients had wheelchairs that did not meet common criteria for wheelchair fit; 36% and 61%, respectively, reported difficulty transferring and propelling the wheelchair. The wheelchairs were used for bathroom mobility by 38% of the patients.
The typical manual wheelchair recipient in this study sample was old with multiple medical problems. Despite provision of manual wheelchairs by trained professionals and availability of diverse wheelchair types, new wheelchair users commonly reported difficulty using the wheelchair.
Quantitative size, shape, and texture features derived from computed tomographic (CT) images may be useful as predictive, prognostic, or response biomarkers in non-small cell lung cancer (NSCLC). ...However, to be useful, such features must be reproducible, non-redundant, and have a large dynamic range. We developed a set of quantitative three-dimensional (3D) features to describe segmented tumors and evaluated their reproducibility to select features with high potential to have prognostic utility. Thirty-two patients with NSCLC were subjected to unenhanced thoracic CT scans acquired within 15 min of each other under an approved protocol. Primary lung cancer lesions were segmented using semi-automatic 3D region growing algorithms. Following segmentation, 219 quantitative 3D features were extracted from each lesion, corresponding to size, shape, and texture, including features in transformed spaces (laws, wavelets). The most informative features were selected using the concordance correlation coefficient across test–retest, the biological range and a feature independence measure. There were 66 (30.14 %) features with concordance correlation coefficient ≥ 0.90 across test–retest and acceptable dynamic range. Of these, 42 features were non-redundant after grouping features with
R
2
Bet
≥ 0.95. These reproducible features were found to be predictive of radiological prognosis. The area under the curve (AUC) was 91 % for a size-based feature and 92 % for the texture features (runlength, laws). We tested the ability of image features to predict a radiological prognostic score on an independent NSCLC (39 adenocarcinoma) samples, the AUC for texture features (runlength emphasis, energy) was 0.84 while the conventional size-based features (volume, longest diameter) was 0.80. Test–retest and correlation analyses have identified non-redundant CT image features with both high intra-patient reproducibility and inter-patient biological range. Thus making the case that quantitative image features are informative and prognostic biomarkers for NSCLC.
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