Stability of radiomic features in CT perfusion maps

This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate  >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size, image discretization, HU threshold and temporal resolution have to be standardized to build a reliable predictive model based on CTP radiomics analysis.

Volumetric stratification of cT4 stage head and neck cancer

BACKGROUND

Locoregionally advanced stage head and neck cancer (HNC) is known for unfavorable outcome with only ~ 40-50% 3-year overall survival (OS). Clinical T4 stage includes a wide range of tumor burden. The lack of further nonsurgical subgrouping of cT4 stage makes intercenter outcome of irradiated cohorts difficult. Aim of this analysis was to further stratify cT4 stage HNC using volumetric staging.

MATERIAL AND METHODS

Between January 2002 and January 2013, a total of 201 cT4 stage squamous cell cancer (SCC) HNC patients referred to our center for curative definitive radiation were consecutively irradiated. Radiation was performed using modulated techniques. Total gross tumor volumes (tGTV: primary+nodal tumor volume) of all patients have retrospectively been stratified using a prospectively evaluated volumetric staging system which bases on 3 cut-offs (15/70/130 ml), translating into 4 prognostic subgroups [V1: 1-15 ml (n=15), V2: 16-70 ml (108), V3: 71-130 ml (62), V4: >130 ml (16)]. OS, disease-free survival (DFS), locoregional control (LRC), and distant metastasis-free survival (DMFS) rates were calculated.

RESULTS

The mean/median follow-up was 31/23 months (range 1-116 months). The 3-year OS, DFS, LRC, and DMFS rates of the entire cohort were 63, 44, 48, and 77%, respectively. Volumetric staging revealed its potential to prognostically statistically significantly divide the cT4 cohort into 4 volume subgroups (V1/2/3/4): OS: 90%/72%/58%/18%; DFS: 83%/50%/39%/10%; LRC: 81%/53%/47%/15%; DMFS: 93%/90%/70%/41%, all p<0.0001.

CONCLUSION

Volumetric staging allowed a highly statistically significant stratification of cT4 HNC stages into prognostic subgroups, which offers the chance of better intercenter comparability of irradiated advanced stage HNC cohorts.

OpenStructure: an integrated software framework for computational structural biology

Research projects in structural biology increasingly rely on combinations of heterogeneous sources of information, e.g. evolutionary information from multiple sequence alignments, experimental evidence in the form of density maps and proximity constraints from proteomics experiments. The OpenStructure software framework, which allows the seamless integration of information of different origin, has previously been introduced. The software consists of C++ libraries which are fully accessible from the Python programming language. Additionally, the framework provides a sophisticated graphics module that interactively displays molecular structures and density maps in three dimensions. In this work, the latest developments in the OpenStructure framework are outlined. The extensive capabilities of the framework will be illustrated using short code examples that show how information from molecular-structure coordinates can be combined with sequence data and/or density maps. The framework has been released under the LGPL version 3 license and is available for download from http://www.openstructure.org.

Treatment concepts of oral cancer

The mortality of oral cancer (OC) has shown only moderate improvement over recent decades. Treatment of OC remains mainly surgical with increasing contributions from radio- and chemotherapy. Early diagnosis and adequate management improves patient prognosis whilst lymphatic spread worsens the prognosis significantly. Copious extirpation of the tumour achieving tumour-free margins, as well as the effective removal of affected or suspect lymph nodes are vital steps to ensure long-term survival. Reconstructive ablities have improved to such an extent that many patients can be fully integrated in society after treatment. New modalities such as intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) ensures selective radiation and significantly contributes to improved quality of life. Photodynamic therapy and other targeted therapy options will play an increasingly important role in the future.

Volumetric staging (VS) is superior to TNM and AJCC staging in predicting outcome of head and neck cancer treated with IMRT

The UICC classification (TNM) represents the validated standard tool to describe tumor extent and includes prognostic information on the probability of disease control. The American Joint Committee on Cancer (AJCC) stage grouping is based on the evaluation of treatment and outcome. Gross tumor volume (GTV) might be more relevant than pure description (TNM) or stage grouping as prognostic factor for local control in head and neck cancer (HNC). Based on the observation of GTV-correlated outcome in our initial HNC patient cohort treated with IMRT, we tested the hypothesis that the GTV is the most reliable predictive tool in HNC outcome. A GTV based volumetric staging system (VS) was introduced, using two volumetric cut-off values (15 and 70 cm3). VS, TNM, and AJCC stages were assessed and correlated with outcome following primary radiation in 172 HNC patients. Analyses were based on Kaplan-Meier survival curves. VS proved to be superior to the TNM/AJCC in predicting outcome. In addition, VS enabled to stratify high- and low-risk patients in advanced TN stages. GTV represented the most important prognostic indicator in HNC treated with IMRT and is recommended to be considered for therapeutic decisions and estimation of outcome.

IMRT using simultaneously integrated boost (SIB) in head and neck cancer patients

Background

Preliminary very encouraging clinical results of intensity modulated radiation therapy (IMRT) in Head Neck Cancer (HNC) are available from several large centers. Tumor control rates seem to be kept at least at the level of conventional three-dimensional radiation therapy; the benefit of normal tissue preservation with IMRT is proven for salivary function. There is still only limited experience with IMRT using simultaneously integrated boost (SIB-IMRT) in the head and neck region in terms of normal tissue response.

The aim of this work was (1) to establish tumor response in HNC patients treated with SIB-IMRT, and (2) to assess tissue tolerance following different SIB-IMRT schedules.

Results

Between 1/2002 and 12/2004, 115 HNC patients have been curatively treated with IMRT. 70% received definitive IMRT (dIMRT), 30% were postoperatively irradiated. In 78% concomitant chemotherapy was given.

SIB radiation schedules with 5–6 × 2 Gy/week to 60–70 Gy, 5 × 2.2 Gy/week to 66–68.2 Gy (according to the RTOG protocol H-0022), or 5 × 2.11 Gy/week to 69.6 Gy were used.

After mean 18 months (10–44), 77% of patients were alive with no disease. Actuarial 2-year local, nodal, and distant disease free survival was 77%, 87%, and 78%, respectively. 10% were alive with disease, 10% died of disease. 20/21 locoregional failures occurred inside the high dose area. Mean tumor volume was significantly larger in locally failed (63 cc) vs controlled tumors (32 cc, p <0.01), and in definitive (43 cc) vs postoperative IMRT (25 cc, p <0.05); the locoregional failure rate was twofold higher in definitively irradiated patients.

Acute reactions were mild to moderate and limited to the boost area, the persisting grade 3/4 late toxicity rate was low with 6%. The two grade 4 reactions (dysphagia, laryngeal fibrosis) were observed following the SIB schedule with 2.2 Gy per session.

Conclusion

SIB-IMRT in HNC using 2.0, 2.11 or 2.2 Gy per session is highly effective and safe with respect to tumor response and tolerance. SIB with 2.2 Gy is not recommended for large tumors involving laryngeal structures.