A common [18F]-FDG PET radiomic signature to predict survival in patients with HPV-induced cancers.

Locally advanced cervical cancer (LACC) and anal and oropharyngeal squamous cell carcinoma (ASCC and OPSCC) are mostly caused by oncogenic human papillomaviruses (HPV). In this paper, we developed machine learning (ML) models based on clinical, biological, and radiomic features extracted from pre-treatment fluorine-18-fluorodeoxyglucose positron emission tomography ([18F]-FDG PET) images to predict the survival of patients with HPV-induced cancers. For this purpose, cohorts from five institutions were used: two cohorts of patients treated for LACC including 104 patients from Gustave Roussy Campus Cancer (Center 1) and 90 patients from Leeds Teaching Hospitals NHS Trust (Center 2), two datasets of patients treated for ASCC composed of 66 patients from Institut du Cancer de Montpellier (Center 3) and 67 patients from Oslo University Hospital (Center 4), and one dataset of 45 OPSCC patients from the University Hospital of Zurich (Center 5). Radiomic features were extracted from baseline [18F]-FDG PET images. The ComBat technique was applied to mitigate intra-scanner variability. A modified consensus nested cross-validation for feature selection and hyperparameter tuning was applied on four ML models to predict progression-free survival (PFS) and overall survival (OS) using harmonized imaging features and/or clinical and biological variables as inputs. Each model was trained and optimized on Center 1 and Center 3 cohorts and tested on Center 2, Center 4, and Center 5 cohorts. The radiomic-based CoxNet model achieved C-index values of 0.75 and 0.78 for PFS and 0.76, 0.74, and 0.75 for OS on the test sets. Radiomic feature-based models had superior performance compared to the bioclinical ones, and combining radiomic and bioclinical variables did not improve the performances. Metabolic tumor volume (MTV)-based models obtained lower C-index values for a majority of the tested configurations but quite equivalent performance in terms of time-dependent AUCs (td-AUC). The results demonstrate the possibility of identifying common PET-based image signatures for predicting the response of patients with induced HPV pathology, validated on multi-center multiconstructor data.

Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma.

Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.

Discovery of pre-therapy 2-deoxy-2-18F-fluoro-D-glucose positron emission tomography-based radiomics classifiers of survival outcome in non-small-cell lung cancer patients.

PURPOSE: The aim of this multi-center study was to discover and validate radiomics classifiers as image-derived biomarkers for risk stratification of non-small-cell lung cancer (NSCLC). PATIENTS AND METHODS: Pre-therapy PET scans from a total of 358 Stage I-III NSCLC patients scheduled for radiotherapy/chemo-radiotherapy acquired between October 2008 and December 2013 were included in this seven-institution study. A semi-automatic threshold method was used to segment the primary tumors. Radiomics predictive classifiers were derived from a training set of 133 scans using TexLAB v2. Least absolute shrinkage and selection operator (LASSO) regression analysis was used for data dimension reduction and radiomics feature vector (FV) discovery. Multivariable analysis was performed to establish the relationship between FV, stage and overall survival (OS). Performance of the optimal FV was tested in an independent validation set of 204 patients, and a further independent set of 21 (TESTI) patients. RESULTS: Of 358 patients, 249 died within the follow-up period [median 22 (range 0-85) months]. From each primary tumor, 665 three-dimensional radiomics features from each of seven gray levels were extracted. The most predictive feature vector discovered (FVX) was independent of known prognostic factors, such as stage and tumor volume, and of interest to multi-center studies, invariant to the type of PET/CT manufacturer. Using the median cut-off, FVX predicted a 14-month survival difference in the validation cohort (N = 204, p = 0.00465; HR = 1.61, 95% CI 1.16-2.24). In the TESTI cohort, a smaller cohort that presented with unusually poor survival of stage I cancers, FVX correctly indicated a lack of survival difference (N = 21, p = 0.501). In contrast to the radiomics classifier, clinically routine PET variables including SUVmax, SUVmean and SUVpeak lacked any prognostic information. CONCLUSION: PET-based radiomics classifiers derived from routine pre-treatment imaging possess intrinsic prognostic information for risk stratification of NSCLC patients to radiotherapy/chemo-radiotherapy.

Respiratory-gated PET/CT for pulmonary lesion characterisation-promises and problems.

2-deoxy-2-(18Fluorine)-fluoro-D-glucose (FDG) PET/CT is an integral part of lung carcinoma staging and frequently used in the assessment of solitary pulmonary nodules. However, a limitation of conventional three-dimensional PET/CT when imaging the thorax is its susceptibility to motion artefact, which blurs the signal from the lesion resulting in inaccurate representation of size and metabolic activity. Respiratory gated (four-dimensional) PET/CT aims to negate the effects of motion artefact and provide a more accurate interpretation of pulmonary nodules and lymphadenopathy. There have been recent advances in technology and a shift from traditional hardware to more streamlined software methods for respiratory gating which should allow more widespread use of respiratory-gating in the future. The purpose of this article is to review the evidence surrounding four-dimensional PET/CT in pulmonary lesion characterisation.

Respiratory-gated (4D) contrast-enhanced FDG PET-CT for radiotherapy planning of lower oesophageal carcinoma: feasibility and impact on planning target volume.

BACKGROUND: To assess the feasibility and potential impact on target delineation of respiratory-gated (4D) contrast-enhanced 18Fluorine fluorodeoxyglucose (FDG) positron emission tomography - computed tomography (PET-CT), in the treatment planning position, for a prospective cohort of patients with lower third oesophageal cancer. METHODS: Fifteen patients were recruited into the study. Imaging included 4D PET-CT, 3D PET-CT, endoscopic ultrasound and planning 4D CT. Target volume delineation was performed on 4D CT, 4D CT with co-registered 3D PET and 4D PET-CT. Planning target volumes (PTV) generated with 4D CT (PTV4DCT), 4D CT co-registered with 3D PET-CT (PTV3DPET4DCT) and 4D PET-CT (PTV4DPETCT) were compared with multiple positional metrics. RESULTS: Mean PTV4DCT, PTV3DPET4DCT and PTV4DPETCT were 582.4 ± 275.1 cm3, 472.5 ± 193.1 cm3 and 480.6 ± 236.9 cm3 respectively (no significant difference). Median DICE similarity coefficients comparing PTV4DCT with PTV3DPET4DCT, PTV4DCT with PTV4DPETCT and PTV3DPET4DCT with PTV4DPETCT were 0.85 (range 0.65-0.9), 0.85 (range 0.69-0.9) and 0.88 (range 0.79-0.9) respectively. The median sensitivity index for overlap comparing PTV4DCT with PTV3DPET4DCT, PTV4DCT with PTV4DPETCT and PTV3DPET4DCT with PTV4DPETCT were 0.78 (range 0.65-0.9), 0.79 (range 0.65-0.9) and 0.89 (range 0.68-0.94) respectively. CONCLUSIONS: Planning 4D PET-CT is feasible with careful patient selection. PTV generated using 4D CT, 3D PET-CT and 4D PET-CT were of similar volume, however, overlap analysis demonstrated that approximately 20% of PTV3DPETCT and PTV4DPETCT are not included in PTV4DCT, leading to under-coverage of target volume and a potential geometric miss. Additionally, differences between PTV3DPET4DCT and PTV4DPETCT suggest a potential benefit for 4D PET-CT. TRIAL REGISTRATION: ClinicalTrials.gov Identifier - NCT02285660 (Registered 21/10/2014).

Alterations in anatomic and functional imaging parameters with repeated FDG PET-CT and MRI during radiotherapy for head and neck cancer: a pilot study.

BACKGROUND: The use of imaging to implement on-treatment adaptation of radiotherapy is a promising paradigm but current data on imaging changes during radiotherapy is limited. This is a hypothesis-generating pilot study to examine the changes on multi-modality anatomic and functional imaging during (chemo)radiotherapy treatment for head and neck squamous cell carcinoma (HNSCC). METHODS: Eight patients with locally advanced HNSCC underwent imaging including computed tomography (CT), Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)-CT and magnetic resonance imaging (MRI) (including diffusion weighted (DW) and dynamic contrast enhanced (DCE)) at baseline and during (chemo)radiotherapy treatment (after fractions 11 and 21). Regions of interest (ROI) were drawn around the primary tumour at baseline and during treatment. Imaging parameters included gross tumour volume (GTV) assessment, SUVmax, mean ADC value and DCE-MRI parameters including Plasma Flow (PF). On treatment changes and correlations between these parameters were analysed using a Wilcoxon rank sum test and Pearson's linear correlation coefficient respectively. A p-value <0.05 was considered statistically significant. RESULTS: Statistically significant reductions in GTV-CT, GTV-MRI and GTV-DW were observed between all imaging timepoints during radiotherapy. Changes in GTV-PET during radiotherapy were heterogeneous and non-significant. Significant changes in SUVmax, mean ADC value, Plasma Flow and Plasma Volume were observed between the baseline and the fraction 11 timepoint, whilst only changes in SUVmax between baseline and the fraction 21 timepoint were statistically significant. Significant correlations were observed between multiple imaging parameters, both anatomical and functional; 20 correlations between baseline to the fraction 11 timepoint; 12 correlations between baseline and the fraction 21 timepoints; and 4 correlations between the fraction 11 and fraction 21 timepoints. CONCLUSIONS: Multi-modality imaging during radiotherapy treatment demonstrates early changes (by fraction 11) in both anatomic and functional imaging parameters. All functional imaging modalities are potentially complementary and should be considered in combination to provide multi-parametric tumour assessment, to guide potential treatment adaptation strategies. TRIAL REGISTRATION: ISRCTN Registry: ISRCTN34165059 . Registered 2nd February 2015.

Evaluation of noise equivalent count parameters as indicators of adult whole-body FDG-PET image quality.

OBJECTIVES: The aim of this study was to assess variation of qualitative and quantitative PET/CT image quality parameters with acquisition time, injection activity and body mass for a representative group of adults undergoing whole-body PET/CT imaging. METHODS: PET scan data from sixty patients were reconstructed with a scan time of 1, 2 and 3 min/bed position. These images were visually scored and three quantitative parameters were calculated: noise equivalent counts per axial length (NECpatient), noise equivalent count density (NECdensity) and liver signal to noise ratio (liver SNR). The ability of the three quantitative parameters to discriminate qualitative image quality was assessed using ROC analysis. RESULTS: The quantitative parameters were shown to discriminate images of good/excellent quality from those of poorer image quality with a high degree of accuracy (ROC area >0.9); further, NECpatient had significantly higher discrimination than either NECdensity or liver SNR (ROC area = 0.97). CONCLUSIONS: NECpatient, NECdensity and liver SNR all have high discrimination for qualitatively assessed PET image quality. NECpatient in particular is an effective objective indicator of patient image quality, which will help to assess and standardise scan protocols for purposes such as multi-centre research trials.

Monitoring linear accelerator output constancy using the PTW Linacheck.

The PTW-Linacheck was assessed for its ability to monitor linear accelerator radiation output constancy. The key issues that were considered were the setup for daily output measurements, e.g., requirements for build-up and backscatter material, and the reproducibility and linearity of the device with linear accelerator output. An appropriate measurement setup includes a 10 × 10 cm field at 100 cm FSD, 5 cm backscatter, and no added build-up for 4 MeV electron beams, 1 cm added build-up for 6-16 MeV electron beams and 5 cm added build-up for 6-15 MV photon beams. Using this measurement setup, the dose linearity and short-term reproducibility were acceptable; however, the Linacheck should be recalibrated on a monthly basis to ensure acceptable long-term reproducibility.

Monitoring primary breast cancer throughout chemotherapy using FDG-PET.

UNLABELLED: We have compared 2-deoxy-2-[(18)F]-fluoro-D-glucose positron emission tomography (FDG-PET) images of large or locally advanced breast cancers (LABC) acquired during Anthracycline-based chemotherapy. The purpose was to determine whether there is an optimal method for defining tumour volume and an optimal imaging time for predicting pathologic chemotherapy response. METHOD: PET data were acquired before the first and second cycles, at the midpoint and at the endpoint of neoadjuvant chemotherapy. FDG uptake was quantified using the mean and maximum standardized uptake values (SUV) and the coefficient of variation within a region of interest. Receiver-operator characteristic (ROC) analysis was used to determine the discrimination between tumours demonstrating a high pathological response (i.e. those with greater than 90% reduction in viable tumour cells) and low pathological response. RESULTS: Only tumours with an initial tumour to background ratio (TBR) of greater than five showed a difference between response categories. In terms of response discrimination, there was no statistically significant advantage of any of the methods used for image quantification or any of the time points. The best discrimination was measured for mean SUV at the midpoint of therapy, which identified 77% of low responding tumours whilst correctly identifying 100% of high responding tumours and had an ROC area of 0.93. CONCLUSION: FDG-PET is efficacious for predicting the pathologic response of most primary breast tumours throughout the duration of a neoadjuvant chemotherapy regimen. However, this technique is ineffective for tumours with low image contrast on pre-therapy PET scans.