Dataset Information

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

ABSTRACT: Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

SUBMITTER: Fedorov A

PROVIDER: S-EPMC4888317 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

Fedorov Andriy A Clunie David D Ulrich Ethan E Bauer Christian C Wahle Andreas A Brown Bartley B Onken Michael M Riesmeier Jörg J Pieper Steve S Kikinis Ron R Buatti John J Beichel Reinhard R RR

PeerJ 20160524

Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation ...[more]

PMID: 27257542

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Project description:To compare the interobserver agreement and degree of confidence in anatomical localisation of lesions using 2-[fluorine-18]fluoro-2-deoxy-D-glucose ((18)F-FDG) positron emission tomography (PET)/computed tomography (CT) and (18)F-FDG PET alone in patients with head and neck tumours. A prospective study of 24 patients (16 male, eight female, median age 59 years) with head and neck tumours was undertaken. (18)F-FDG PET/CT was performed for staging purposes. 2D images were acquired over the head and neck area using a GE Discovery LS PET/CT scanner. (18)F-FDG PET images were interpreted by three independent observers. The observers were asked to localise abnormal (18)F-FDG activity to an anatomical territory and score the degree of confidence in localisation on a scale from 1 to 3 (1=exact region unknown; 2=probable; 3=definite). For all (18)F-FDG-avid lesions, standardised uptake values (SUVs) were also calculated. After 3 weeks, the same exercise was carried out using (18)F-FDG PET/CT images, where CT and fused volume data were made available to observers. The degree of interobserver agreement was measured in both instances. A total of six primary lesions with abnormal (18)F-FDG uptake (SUV range 7.2-22) were identified on (18)F-FDG PET alone and on (18)F-FDG PET/CT. In all, 15 nonprimary tumour sites were identified with (18)F-FDG PET only (SUV range 4.5-11.7), while 17 were identified on (18)F-FDG PET/CT. Using (18)F-FDG PET only, correct localisation was documented in three of six primary lesions, while (18)F-FDG PET/CT correctly identified all primary sites. In nonprimary tumour sites, (18)F-FDG PET/CT improved the degree of confidence in anatomical localisation by 51%. Interobserver agreement in assigning primary and nonprimary lesions to anatomical territories was moderate using (18)F-FDG PET alone (kappa coefficients of 0.45 and 0.54, respectively), but almost perfect with (18)F-FDG PET/CT (kappa coefficients of 0.90 and 0.93, respectively). We conclude that (18)F-FDG PET/CT significantly increases interobserver agreement and confidence in disease localisation of (18)F-FDG-avid lesions in patients with head and neck cancers.

Project description:ImportanceThe mechanisms underlying the association between chronic stress and higher mortality among individuals with cancer remain incompletely understood.ObjectiveTo test the hypotheses that among individuals with active head and neck cancer, that higher stress-associated neural activity (ie. metabolic amygdalar activity [AmygA]) at cancer staging associates with survival.DesignRetrospective cohort study.SettingAcademic Medical Center (Massachusetts General Hospital, Boston).Participants240 patients with head and neck cancer (HNCA) who underwent 18F-FDG-PET/CT imaging as part of initial cancer staging.Measurements18F-FDG uptake in the amygdala was determined by placing circular regions of interest in the right and left amygdalae and measuring the mean tracer accumulation (i.e., standardized uptake value [SUV]) in each region of interest. Amygdalar uptake was corrected for background cerebral activity (mean temporal lobe SUV).ResultsAmong individuals with HNCA (age 59±13 years; 30% female), 67 died over a median follow-up period of 3 years (IQR: 1.7-5.1). AmygA associated with heightened bone marrow activity, leukocytosis, and C-reactive protein (P<0.05 each). In adjusted and unadjusted analyses, AmygA associated with subsequent mortality (HR [95% CI]: 1.35, [1.07-1.70], P = 0.009); the association persisted in stratified subset analyses restricted to patients with advanced cancer stage (P<0.001). Individuals within the highest tertile of AmygA experienced a 2-fold higher mortality rate compared to others (P = 0.01). The median progression-free survival was 25 months in patients with higher AmygA (upper tertile) as compared with 36.5 months in other individuals (HR for progression or death [95%CI], 1.83 [1.24-2.68], P = 0.001).Conclusions and relevanceAmygA, quantified on routine 18F-FDG-PET/CT images obtained at cancer staging, independently and robustly predicts mortality and cancer progression among patients with HNCA. Future studies should test whether strategies that attenuate AmygA (or its downstream biological consequences) may improve cancer survival.

Project description:Background Systemic inflammation is predictive of the overall survival in cancer patients and is related to the density of immune cells in the tumor microenvironment of cancer, which in turn correlates with 18F -fluorodeoxyglucose (FDG)-positron emission tomography/computed tomography (PET/CT) metabolic parameters (MPs). The density of tumor-infiltrating lymphocytes (TILs) in the microenvironment has the potential to be a biomarker that can be used clinically to optimize patient selection in oropharyngeal head and neck squamous cell carcinoma (HNSCC). There is little to no data regarding the association of systemic inflammation with PET/CT-MPs, especially in HNSCC. This study aimed to evaluate the correlation between markers of host inflammation, namely blood neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), with the PET/CT-MPs standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor, derived from FDG-PET/CT in patients with nonmetastatic (cM0) HNSCC before treatment. We hypothesized that NLR and PLR at baseline are positively correlated with PET/CT-MPs. Methods A retrospective review of consecutive patients with HNSCC with a pretreatment PET/CT was performed. NLR and PLR were computed using complete blood counts measured within 10 days before the start of any treatment. The correlation between NLR and PLR with PET/CT-MPs was evaluated with Spearman's rho test. Results Seventy-one patients were analyzed. Overall survival (OS) at 1, 2, and 3 years was 86%, 76%, and 68%. PLR was found to be correlated with MTV (rho = 0.26, P = .03) and TLG (rho = 0.28, P = .02) but not with maximum SUV or mean SUV. There was no correlation between NLR and the analyzed PET/CT-MPs. TLG was associated with worse survival in uni- and multivariable analysis, but no other PET/CT-MPs were associated with either OS or disease-specific survival (DSS). NLR and PLR were associated with OS and DSS on uni- and multivariable analysis. Conclusions In patients with HNSCC before any treatment such as definitive radio (chemo)therapy or oncologic surgery followed by adjuvant RT, baseline PLR correlated with MTV and TLG but not with SUV. NLR was not correlated with any PET/CT-MPs analyzed in our study. Confirmatory studies are needed, and a potential interaction between tumor microenvironment, host inflammation, and FDG-PET/CT measures warrants further investigation. Supplementary Information The online version contains supplementary material available at 10.1186/s13014-022-02112-4.

Project description:UNLABELLED:There has been no established qualitative system of interpretation for therapy response assessment using PET/CT for head and neck cancers. The objective of this study was to validate the Hopkins interpretation system to assess therapy response and survival outcome in head and neck squamous cell cancer patients (HNSCC). METHODS:The study included 214 biopsy-proven HNSCC patients who underwent a posttherapy PET/CT study, between 5 and 24 wk after completion of treatment. The median follow-up was 27 mo. PET/CT studies were interpreted by 3 nuclear medicine physicians, independently. The studies were scored using a qualitative 5-point scale, for the primary tumor, for the right and left neck, and for overall assessment. Scores 1, 2, and 3 were considered negative for tumors, and scores 4 and 5 were considered positive for tumors. The Cohen ? coefficient (?) was calculated to measure interreader agreement. Overall survival (OS) and progression-free survival (PFS) were analyzed by Kaplan-Meier plots with a Mantel-Cox log-rank test and Gehan Breslow Wilcoxon test for comparisons. RESULTS:Of the 214 patients, 175 were men and 39 were women. There was 85.98%, 95.33%, 93.46%, and 87.38% agreement between the readers for overall, left neck, right neck, and primary tumor site response scores, respectively. The corresponding ? coefficients for interreader agreement between readers were, 0.69-0.79, 0.68-0.83, 0.69-0.87, and 0.79-0.86 for overall, left neck, right neck, and primary tumor site response, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the therapy assessment were 68.1%, 92.2%, 71.1%, 91.1%, and 86.9%, respectively. Cox multivariate regression analysis showed human papillomavirus (HPV) status and PET/CT interpretation were the only factors associated with PFS and OS. Among the HPV-positive patients (n = 123), there was a significant difference in PFS (hazard ratio [HR], 0.14; 95% confidence interval, 0.03-0.57; P = 0.0063) and OS (HR, 0.01; 95% confidence interval, 0.00-0.13; P = 0.0006) between the patients who had a score negative for residual tumor versus positive for residual tumor. A similar significant difference was observed in PFS and OS for all patients. There was also a significant difference in the PFS of patients with PET-avid residual disease in one site versus multiple sites in the neck (HR, 0.23; log-rank P = 0.004). CONCLUSION:The Hopkins 5-point qualitative therapy response interpretation criteria for head and neck PET/CT has substantial interreader agreement and excellent negative predictive value and predicts OS and PFS in patients with HPV-positive HNSCC.

Project description:BACKGROUND:Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (18F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy. METHODS:Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent 18F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order 18F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with 18F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome. RESULTS:Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764). CONCLUSIONS:Combining HPV-status, first-order 18F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care. TRIAL REGISTRATION:Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.

Dataset Information

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

Publications

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

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