Incidence of radiation-induced hypothyroidism following head and neck irradiation: a single-center analysis

BackgroundThe purpose of this study was to investigate the incidence of primary hypothyroidism (HT), as well as any correlation between dosimetric parameters and thyroid dysfunctions after neck radiotherapy (RT) in head and neck cancer (HNC) patients.Materials and methodsThis study retrospectively reviewed HNC patients who finished neck RT for at least 12 months and who had available back-up treatment information. Eligible patients further received a single thyroid function test (TFT). Dosimetric parameters of the thyroid glands were retrospectively evaluated in order to detect any correlation between dose-volume parameters and primary HT.ResultsWe reviewed 1,102 HNC patients. Accordingly, 64 patients were deemed eligible and were included in this study. The median time interval between RT completion and TFT was 21 months (interquartile range, 14–34 months), while 26 patients (40.6%) were diagnosed with HT. The thyroid volume spared from a dose of 50 Gy (VS50_Gy) was found to be statistically significant and considered an associated factor for developing HT (p = 0.047). Furthermore, there was an observable trend indicating a reduction in the risk of HT when VS50_Gy was more than 5 cm³ (p = 0.052).ConclusionIn our study, VS50_Gy was determined to be a significant predictive parameter of radiation-induced HT.     

A study on conventional IMRT and RapidArc treatment planning techniques for head and neck cancers

AimTo evaluate the performance of volumetric arc modulation with RapidArc against conventional IMRT for head and neck cancers.BackgroundRapidArc is a novel technique that has recently been made available for clinical use. Planning study was done for volumetric arc modulation with RapidArc against conventional IMRT for head and neck cancers.Materials and methodsTen patients with advanced tumors of the nasopharynx, oropharynx, and hypopharynx were selected for the planning comparison study. PTV was delineated for two different dose levels and planning was done by means of simultaneously integrated boost technique. A total dose of 70 Gy was delivered to the boost volume (PTV boost) and 57.7 Gy to the elective PTV (PTV elective) in 35 equal treatment fractions. PTV boost consisted of the gross tumor volume and lymph nodes containing visible macroscopic tumor or biopsy-proven positive lymph nodes, whereas the PTV elective consisted of elective nodal regions. Planning was done for IMRT using 9 fields and RapidArc with single arc, double arc. Beam was equally placed for IMRT plans. Single arc RapidArc plan utilizes full 360° gantry rotation and double arc consists of 2 co-planar arcs of 360° in clockwise and counter clockwise direction. Collimator was rotated from 35 to 45° to cover the entire tumor, which reduced the tongue and groove effect during gantry rotation. All plans were generated with 6 MV X-rays for CLINAC 2100 Linear Accelerator. Calculations were done in the Eclipse treatment planning system (version 8.6) using the AAA algorithm.ResultsDouble arc plans show superior dose homogeneity in PTV compared to a single arc and IMRT 9 field technique. Target coverage was almost similar in all the techniques. The sparing of spinal cord in terms of the maximum dose was better in the double arc technique by 4.5% when compared to the IMRT 9 field and single arc techniques. For healthy tissue, no significant changes were observed between the plans in terms of the mean dose and integral dose. But RapidArc plans showed a reduction in the volume of the healthy tissue irradiated at V_15 Gy (5.81% for single arc and 4.69% for double arc) and V_20 Gy (7.55% for single arc and 5.89% for double arc) dose levels when compared to the 9-Field IMRT technique. For brain stem, maximum dose was similar in all the techniques. The average MU (±SD) needed to deliver the dose of 200 cGy per fraction was 474 ± 80 MU and 447 ± 45 MU for double arc and single arc as against 948 ± 162 MU for the 9-Field IMRT plan. A considerable reduction in maximum dose to the mandible by 6.05% was observed with double arc plan. Double arc shows a reduction in the parotid mean dose when compared with single arc and IMRT plans.ConclusionRapidArc using double arc provided a significant sparing of OARs and healthy tissue without compromising target coverage compared to IMRT. The main disadvantage with IMRT observed was higher monitor units and longer treatment time.     

Proton re-irradiation of unresectable recurrent head and neck cancers

BackgroundThis study presents a retrospective analysis (efficacy and toxicity) of outcomes in patients with unresectable recurrence of previously irradiated head and neck (H&N) cancers treated with proton therapy. Locoregional recurrence is the main pattern of failure in the treatment of H&N cancers. Proton re-irradiation in patients with relapse after prior radiotherapy might be valid as promising as a challenging treatment option.Materials and methodsFrom November 2015 to January 2020, 30 patients with in-field recurrence of head and neck cancer, who were not suitable for surgery due to medical contraindications, tumor localization, or extent, received re-irradiation with intensity-modulated proton therapy (IMPT). Sites of retreatment included the aerodigestive tract (60%) and the base of skull (40%). The median total dose of prior radiotherapy was 55.0 Gy. The median time to the second course was 38 months. The median re-irradiated tumor volume was 158.1 cm³. Patients were treated with 2.0, 2.4, and 3.0 GyRBE per fraction, with a median equivalent dose (EQD₂) of 57.6 Gy (α/β = 10). Radiation-induced toxicity was recorded according to the RTOG/EORTC criteria.ResultsThe 1- and 2-year local control (LC), progression-free survival (PFS), and overall survival (OS) were 52.6/21.0, 21.9/10.9, and 73.4/8.4%, respectively, with a median follow-up time of 21 months. The median overall survival was 16 months. Acute grade 3 toxicity was observed in one patient (3.3%). There were five late severe side effects (16.6%), with one death associated with re-irradiation.ConclusionRe-irradiation with a proton beam can be considered a safe and efficient treatment even for a group of patients with unresectable recurrent H&N cancers.     

机器学习在微生物组宿主表型预测中的应用

随着大数据时代的到来,如何将生物组学海量数据转化为易理解及可视化的知识是当前生物信息学面临的重要挑战之一.为了处理复杂、高维的微生物组数据,目前机器学习算法已被应用于人体微生物组研究,以揭示疾病背后的复杂机制.本文首先简述了微生物组数据处理方法及常用的机器学习算法,如支持向量机(SVM)、随机森林(RF)和人工神经网络...     

Expression scoring of a small-nucleolar-RNA signature identified by machine learning serves as a prognostic predictor for head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and poor prognosis due to a lack of predictive markers. Increasing evidence has demonstrated small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. The aim of this study was to identify a prognostic snoRNA signature of HNSCC. Survival-related snoRNAs were screened by Cox regression analysis (univariate, least absolute shrinkage and selection operator, and multivariate). The predictive value was validated in different subgroups. The biological functions were explored by coexpression analysis and gene set enrichment analysis (GSEA). One hundred and thirteen survival-related snoRNAs were identified, and a five-snoRNA signature predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different sexes, ages, stages, grades, and anatomic subdivisions. Coexpression analysis and GSEA revealed the five-snoRNA are involved in regulating malignant phenotype and DNA/RNA editing. This five-snoRNA signature is not only a promising predictor of prognosis and survival but also a potential biomarker for patient stratification management.     

Machine learning helps identifying volume-confounding effects in radiomics

PurposeHighlighting the risk of biases in radiomics-based models will help improve their quality and increase usage as decision support systems in the clinic. In this study we use machine learning-based methods to identify the presence of volume-confounding effects in radiomics features.Methods841 radiomics features were extracted from two retrospective publicly available datasets of lung and head neck cancers using open source software. Unsupervised hierarchical clustering and principal component analysis (PCA) identified relations between radiomics and clinical outcomes (overall survival). Bootstrapping techniques with logistic regression verified features’ prognostic power and robustness.ResultsOver 80% of the features had large pairwise correlations. Nearly 30% of the features presented strong correlations with tumor volume. Using volume-independent features for clustering and PCA did not allow risk stratification of patients. Clinical predictors outperformed radiomics features in bootstrapping and logistic regression.ConclusionsThe adoption of safeguards in radiomics is imperative to improve the quality of radiomics studies. We proposed machine learning (ML) – based methods for robust radiomics signatures development.     

Production of granulocyte colony-stimulating factor by head and neck carcinomas

Detectable levels of G-CSF by enzyme-linked immunosorbent assay (ELISA) were found in sera of 4 out of 15 patients with head and neck carcinomas. Also cells prepared from the tumors of these 4 patients secreted G-CSF. The supernatants of cells derived from all 15 patients did not contain granulocyte-monocyte CSF, monocyte CSF, tumor necrosis factor-, transforming growth factor- ₁, epidermal growth factor, interleukin (IL)-1 and IL-6. These findings suggest that leukocytosis in patients with carcinomas might be due to the production of G-CSF by tumor cells.Abbreviations CSF colony stimulating factor - EGF epidermal growth factor - ELISA Enzyme-linked immunosorbent assay - G granulocyte - GM granulocyte-monocyte - IL interluekin - M monocyte - TGF transforming growth factor - TNF tumor necrosis factor     

Good practice in head and neck fine needle aspiration cytology as assessed by CUSUM

Providing data as evidence of good practice is becoming imperative to meet the demands of professional revalidation and clinical governance. Sensitivity and specificity are common performance measures in fine needle aspiration (FNA) but are vulnerable to discordant analytical methods. We introduce a CUSUM technique and show how it may be used to show attainment and maintenance of proficiency in head and neck (H&N) FNA. In addition, we show how it can be used to compare practices and demonstrate different performance for FNAs from different tissues; a fact that must be recognized by anyone devising minimum performance values.     

DNA methylation biomarkers for head and neck squamous cell carcinoma

DNA methylation plays an important role in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). The current study aimed to identify aberrantly methylated-differentially expressed genes (DEGs) by a comprehensive bioinformatics analysis. In addition, we screened for DEGs affected by DNA methylation modification and further investigated their prognostic values for HNSCC. We included microarray data of DNA methylation (GSE25093 and GSE33202) and gene expression (GSE23036 and GSE58911) from Gene Expression Omnibus. Aberrantly methylated-DEGs were analyzed with R software. The Cancer Genome Atlas (TCGA) RNA sequencing and DNA methylation (Illumina HumanMethylation450) databases were utilized for validation. In total, 27 aberrantly methylated genes accompanied by altered expression were identified. After confirmation by The Cancer Genome Atlas (TCGA) database, 2 hypermethylated-low-expression genes (FAM135B and ZNF610) and 2 hypomethylated-high-expression genes (HOXA9 and DCC) were identified. A receiver operating characteristic (ROC) curve confirmed the diagnostic value of these four methylated genes for HNSCC. Multivariate Cox proportional hazards analysis showed that FAM135B methylation was a favorable independent prognostic biomarker for overall survival of HNSCC patients.     

Patient-specific IMRT QA verification using machine learning and gamma radiomics

Gamma function is the standard methodology for comparing dose distributions. It is calculated in dedicated software, and its results verification is not performed. Thus we developed an automatic tool for patient-specific QA results verification through high accuracy machine learning (ML) models based on the radiomics characteristics extraction from gamma images. We used 158 patient-specific QA tests and extracted 105 radiomics features from each gamma image. Three random forest models were developed (ML I, ML II, and ML III). ML I and ML II verified the gamma image approval using criteria of 2%/2mm/15% threshold and 3%/3mm/15% threshold, respectively. ML III verified if the gamma analyzes software recommended protocol was followed to detect if the TPS grid modification step was done. The models were based on the most important features selected using the mean decreased impurity, and their performances were evaluated. ML I included 25 features. Its accuracy was 0.85 using the test set and 0.84 using dataset B. ML II included 10 features, and its accuracy with the test set was 0.98; the same value was achieved using the never seen data (dataset B). The First-order 10th percentile feature was identified as a feature strongly related to the approved classification. ML III selected 23 features with an accuracy of 0.99 for test set and 0.98 for dataset B. An automatic workflow example for gamma analyses QA results verification could be proposed combining the models to detect grid inconsistencies on software evaluation, followed by the test approval classification.     

An overview of gene therapy in head and neck cancer

Gene therapy is a new treatment modality in which new gene is introduced or existing gene is manipulated to cause cancer cell death or slow the growth of the tumor. In this review, we have discussed the different treatment approaches for cancer gene therapy; gene addition therapy, immunotherapy, gene therapy using oncolytic viruses, antisense ribonucleic acid (RNA) and RNA interference-based gene therapy. Clinical trials to date in head and neck cancer have shown evidence of gene transduction and expression, mediation of apoptosis and clinical response including pathological complete responses. The objective of this article is to provide an overview of the current available gene therapies for head and neck cancer.     

The progress of multimodal imaging combination and subregion based radiomics research of cancers

In recent years, with the standardization of radiomics methods; development of tools; and popularization of the concept, radiomics has been widely used in all aspects of tumor diagnosis; treatment; and prognosis. As the study of radiomics in cancer has become more advanced, the currently used methods have revealed their shortcomings. The performance of cancer radiomics based on single-modality medical images, which based on their imaging principles, only partially reflects tumor information, has been necessarily compromised. Using the whole tumor as a region of interest to extract radiomic features inevitably leads to the loss of intra-tumoral heterogeneity of, which also affects the performance of radiomics. Radiomics of multimodal images extracts various aspects of information from images of each modality and then integrates them together for model construction; thus, avoiding missing information. Subregional segmentation based on multimodal medical image combinations allows radiomics features acquired from subregions to retain tumor heterogeneity, further improving the performance of radiomics. In this review, we provide a detailed summary of the current research on the radiomics of multimodal images of cancer and tumor subregion-based radiomics, and then raised some of the research problems and also provide a thorough discussion on these issues.     

Autologous tumor cell killing activity of tumor-associated lymphocytes in patients with head and neck carcinomas

In order to select the most cytotoxic effector cells for adoptive immunotherapy, lymphokine activated killer (LAK) cells, tumor infiltrating lymphocytes (TILs) and autologous mixed lymphocyte tumor cell culture (MLTC) cells derived from peripheral blood mononuclear cells (PBMC) in the same subject with head and neck carcinomas were prepared. The autologous tumor cell killing activity and cell surface phenotypes of each of the three effector cells were studied. MLTC cells cultured with interleukin-2 (IL-2) showed the strongest cytotoxic activity among these three different effector cells. Although TILs had suppressed killing activity immediately after isolation, after successive cultivations with IL-2, a cytotoxic activity against autologous tumor cells stronger than that of LAK cells appeared. Both IL-2 stimulated MLTC cells and TILs showed an enrichment of CD8 positive and CDU negative cells in a CD3 positive subpopulation.Abbreviations CD cluster differentiation - IL-2 interleukin-2 - LA lymphokine activated - LAK lymphokine activated killer - MLTC mixed lymphocyte tumor cell culture - NK natural killer - PBMC peripheral blood mononuclear cells - TILs tumor infiltrating lymphocytes     

Radiotherapy for locally advanced head and neck cancer in elderly patients: results and prognostic factors a single cohort

BackgroundThe objective of this study was to assess the treatment outcomes and prognostic factors of elderly patients with locally advanced head and neck cancer (LAHNC) undergoing radiotherapy (RT).Materials and methodsA retrospective cohort from a single institution, from 2000 to 2015, including patients older than 65 years old with LAHNC (stage III–IVa) treated by RT combined or not with chemotherapy (CRT). Univariate and multivariate analysis (MVA) were performed to identify prognostic factors associated with overall survival (OS), cancer-specific survival (CS), and locoregional control (LRC). A p-value < 0.05 was considered significant.Results220 patients with LAHNC and > 65 years of age were identified. The median follow-up was 3.8 years, the 3/5 years estimated OS, CS, and LRC rate was 40%/30%, 49%/34%, 76%/45%, respectively. In the univariate analysis, clinical stage (III vs. IVa/b, p = 0.01), tumor stage (T1/2 vs. T3/4, p = 0.035), Karnofsky performance status (KPS, 60–70, p = 0.03) and tumor site (other than vs. hypopharynx, p = 0.0001) were associated with lower OS. Patients with clinical stage (III vs. IVa/b, p = 0.01), tumor stage (T1/2 vs. T3/4, p = 0.015), N stage (N0/1 vs. N2/3, p = 0.04), (KPS 60–70, p = 0.04) and tumor site (other than vs. hypopharynx, p = 0.0001) had worst CS. For the LRC, clinical stage (III vs. IVa/b, p = 0.02), tumor stage (T1/2 vs. T3/4, p = 0.02), treatment type (CRT vs. RT, p = 0.02), RT technique (IMRT vs. 2DRT/3DRT, p = 0.0001), and tumor site (other than vs. hypopharynx, p = 0.02) were significant. In the MVA, KPS maintained significant for OS and CS. For LRC, clinical stage (Iva/b, p = 0.007), tumor stage (T3/4, p = 0.047) and radiotherapy technique other than IMRT (p = 0.0001) were significant.ConclusionThe OS, CS, and LRC were associated with several prognostic factors. The clinical performance was the main marker of OS and CS. Chemoradiation should be offered to selected elderly patients using IMRT to improve LRC.     

Effect of sizofiran on regional lymph nodes in patients with head and neck cancer

The immunomodulating effects of preoperative sizofiran (SPG) administration on regional lymph nodes were studied in patients with stage III or IV head and neck cancer, by comparing the immunofunction of peripheral blood. The regional lymph nodes were dissected surgically, and freshly obtained mononuclear cells were studied to investigate the interleukin-2 (IL-2) production, the LAK and NK activities, and the quantitative analysis of the surface phenotype of the mononuclear cells. The results indicated that SPG enhanced immunological activities in the regional lymph nodes, as shown by increased IL-2 production and cytotoxic activities of the effector cells (NK, LAK), and increased helper T lymphocytes (CD4⁺) in the tumor-uninvolved lymph nodes. The immunofunction following SPG administration was attenuated, but was still augmented in the regional lymph nodes with metastases. Therefore, SPG was found to be a biologic response modifier to enhance the immunofunctions of the regional lymph node in patients with head and neck cancer.     

Prediction of effluent quality in papermaking wastewater treatment processes using dynamic kernel-based extreme learning machine

Papermaking wastewater accounts for a large proportion of industrial wastewater, and it is essential to obtain accurate and reliable effluent indices in real-time. Considering the complexity, nonlinearity, and time variability of wastewater treatment processes, a dynamic kernel extreme learning machine (DKELM) method is proposed to predict the key quality indices of effluent chemical oxygen demand (COD). A time lag coefficient is introduced and a kernel function is embedded into the extreme learning machine (ELM) to extract dynamic information and obtain better prediction accuracy. A case study for modeling a wastewater treatment process is demonstrated to evaluate the performance of the proposed DKELM. The results illustrate that both training and prediction accuracy of the DKELM model is superior to other models. For the prediction of the quality indices of effluent COD, the determinate coefficient of the DKELM model is increased by 27.52 %, 21.36 %, 10.42 %, and 10.81 %, compared with partial least squares, ELM, dynamic ELM, and kernel ELM, respectively.