Dataset Information

Differentiating head and neck carcinoma from lung carcinoma with an electronic nose: a proof of concept study.

ABSTRACT: Disease specific patterns of volatile organic compounds can be detected in exhaled breath using an electronic nose (e-nose). The aim of this study is to explore whether an e-nose can differentiate between head and neck, and lung carcinoma. Eighty-seven patients received an e-nose measurement before any oncologic treatment. We used PARAFAC/TUCKER3 tensor decomposition for data reduction and an artificial neural network for analysis to obtain binary results; either diagnosed as head and neck or lung carcinoma. Via a leave-one-out method, cross-validation of the data was performed. In differentiating head and neck from lung carcinoma patients, a diagnostic accuracy of 93 % was found. After cross-validation of the data, this resulted in a diagnostic accuracy of 85 %. There seems to be a potential for e-nose as a diagnostic tool in HNC and lung carcinoma. With a fair diagnostic accuracy, an e-nose can differentiate between the two tumor entities.

SUBMITTER: van Hooren MR

PROVIDER: S-EPMC5052311 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Differentiating head and neck carcinoma from lung carcinoma with an electronic nose: a proof of concept study.

van Hooren Michel R A MR Leunis Nicoline N Brandsma Dirk S DS Dingemans Anne-Marie C AC Kremer Bernd B Kross Kenneth W KW

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery 20160416 11

Disease specific patterns of volatile organic compounds can be detected in exhaled breath using an electronic nose (e-nose). The aim of this study is to explore whether an e-nose can differentiate between head and neck, and lung carcinoma. Eighty-seven patients received an e-nose measurement before any oncologic treatment. We used PARAFAC/TUCKER3 tensor decomposition for data reduction and an artificial neural network for analysis to obtain binary results; either diagnosed as head and neck or lu ...[more]

PMID: 27083159

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Project description:PurposeProgrammed cell death-1 (PD-1) receptor inhibitors have shown efficacy in head and neck squamous cell carcinoma (HNSCC), but treatment failure or secondary resistance occurs in most patients. In preclinical murine carcinoma models, inhibition of Bruton's tyrosine kinase (BTK) induces myeloid cell reprogramming that subsequently bolsters CD8+ T cell responses, resulting in enhanced antitumor activity. This phase 2, multicenter, open-label, randomized study evaluated pembrolizumab (anti-PD-1 monoclonal antibody) plus acalabrutinib (BTK inhibitor) in recurrent or metastatic HNSCC.Patients and methodsPatients received pembrolizumab 200 mg intravenously every 3 weeks, alone or in combination with acalabrutinib 100 mg orally twice daily. Safety and overall response rate (ORR) were co-primary objectives. The secondary objectives were progression-free survival (PFS) and overall survival.ResultsSeventy-six patients were evaluated (pembrolizumab, n = 39; pembrolizumab + acalabrutinib, n = 37). Higher frequencies of grade 3-4 treatment-emergent adverse events (AE; 65% vs. 39%) and serious AEs (68% vs. 31%) were observed with combination therapy versus monotherapy. ORR was 18% with monotherapy versus 14% with combination therapy. Median PFS was 2.7 [95% confidence interval (CI), 1.4-6.8] months in the combination arm and 1.7 (95% CI, 1.4-4.0) months in the monotherapy arm. The study was terminated due to lack of clinical benefit with combination treatment. To assess how tumor immune contexture was affected by therapy in patients with pre- and post-treatment biopsies, spatial proteomic analyses were conducted that revealed a trend toward increased CD45+ leukocyte infiltration of tumors from baseline at day 43 with pembrolizumab (monotherapy, n = 5; combination, n = 2), which appeared to be higher in combination-treated patients; however, definitive conclusions could not be drawn due to limited sample size.ConclusionsDespite lack of clinical efficacy, immune subset analyses suggest that there are additive effects of this combination; however, the associated toxicity limits the feasibility of combination treatment with pembrolizumab and acalabrutinib in patients with recurrent or metastatic HNSCC.

Project description:PurposeRadiomics has already been proposed as a prognostic biomarker in head and neck cancer (HNSCC). However, its predictive power in radiotherapy has not yet been studied. Here, we investigated a local radiomics approach to distinguish between tumor sub-volumes with different levels of radiosensitivity as a possible target for radiation dose intensification.Materials and methodsOf 40 patients (n=28 training and n=12 validation) with biopsy confirmed locally recurrent HNSCC, pretreatment contrast-enhanced CT images were registered with follow-up PET/CT imaging allowing identification of controlled (GTVcontrol) vs non-controlled (GTVrec) tumor sub-volumes on pretreatment imaging. A bi-regional model was built using radiomic features extracted from pretreatment CT in the GTVrec and GTVcontrol to differentiate between those regions. Additionally, concept of local radiomics was implemented to perform detection task. The original tumor volume was divided into sub-volumes with no prior information on the location of recurrence. Radiomic features from those sub-volumes were then used to detect recurrent sub-volumes using multivariable logistic regression.ResultsRadiomic features extracted from non-controlled regions differed significantly from those in controlled regions (training AUC = 0.79 CI 95% 0.66 - 0.91 and validation AUC = 0.88 CI 95% 0.72 - 1.00). Local radiomics analysis allowed efficient detection of non-controlled sub-volumes both in the training AUC = 0.66 (CI 95% 0.56 - 0.75) and validation cohort 0.70 (CI 95% 0.53 - 0.86), however performance of this model was inferior to bi-regional model. Both models indicated that sub-volumes characterized by higher heterogeneity were linked to tumor recurrence.ConclusionLocal radiomics is able to detect sub-volumes with decreased radiosensitivity, associated with location of tumor recurrence in HNSCC in the pre-treatment CT imaging. This proof of concept study, indicates that local CT radiomics can be used as predictive biomarker in radiotherapy and potential target for dose intensification.

Dataset Information

Differentiating head and neck carcinoma from lung carcinoma with an electronic nose: a proof of concept study.

Publications

Differentiating head and neck carcinoma from lung carcinoma with an electronic nose: a proof of concept study.

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