Search

BackgroundMost MRI radiomics studies to date, even multi-centre ones, have used “pure” datasets deliberately accrued from single-vendor, single-field-strength scanners. This does not reflect aspirations for the ultimate generalisability of AI models. We therefore investigated the development of a radiomics signature from heterogeneous data originating on six different imaging platforms, for a breast cancer exemplar, in order to provide input into future discussions of the viability of radiomics in “real-world” scenarios where image data are not controlled by specific trial protocols but reflective of routine clinical practice.MethodsOne hundred fifty-six patients with pathologically proven breast cancer underwent multi-contrast MRI prior to neoadjuvant chemotherapy and/or surgery. From these, 92 patients were identified for whom T2-weighted, diffusion-weighted and contrast-enhanced T1-weighted sequences were available, as well as key clinicopathological variables. Regions-of-interest were drawn on the above image types and, from these, semantic and calculated radiomics features were derived. Classification models using a variety of methods, both with and without recursive feature elimination, were developed to predict pathological nodal status. Separately, we applied the same methods to analyse the information carried by the radiomic features regarding the originating scanner type and field strength. Repeated, ten-fold cross-validation was employed to verify the results. In parallel work, survival modelling was performed using random survival forests.ResultsPrediction of nodal status yielded mean cross-validated AUC values of 0.735 ± 0.15 (SD) for clinical variables alone, 0.673 ± 0.16 (SD) for radiomic features only, and 0.764 ± 0.16 (SD) for radiomics and clinical features together. Prediction of scanner platform from the radiomics features yielded extremely high values of AUC between 0.91 and 1 for the different classes examined indicating the presence of confounding features for the nodal status classification task. Survival analysis, gave out-of-bag prediction errors of 19.3% (clinical features only), 36.9–51.8% (radiomic features from different combinations of image contrasts), and 26.7–35.6% (clinical plus radiomics features).ConclusionsRadiomic classification models whose predictive ability was consistent with previous single-vendor, single-field strength studies have been obtained from multi-vendor, multi-field-strength data, despite clear confounding information being present. However, our sample size was too small to obtain useful survival modelling results.

Recurrence occurs in up to 36% of patients treated with curative-intent radiotherapy for NSCLC. Identifying patients at higher risk of recurrence for more intensive surveillance may facilitate the earlier introduction of the next line of treatment. We aimed to use radiotherapy planning CT scans to develop radiomic classification models that predict overall survival (OS), recurrence-free survival (RFS) and recurrence two years post-treatment for risk-stratification. A retrospective multi-centre study of >900 patients receiving curative-intent radiotherapy for stage I-III NSCLC was undertaken. Models using radiomic and/or clinical features were developed, compared with 10-fold cross-validation and an external test set, and benchmarked against TNM-stage. Respective validation and test set AUCs (with 95% confidence intervals) for the radiomic-only models were: (1) OS: 0.712 (0.592–0.832) and 0.685 (0.585–0.784), (2) RFS: 0.825 (0.733–0.916) and 0.750 (0.665–0.835), (3) Recurrence: 0.678 (0.554–0.801) and 0.673 (0.577–0.77). For the combined models: (1) OS: 0.702 (0.583–0.822) and 0.683 (0.586–0.78), (2) RFS: 0.805 (0.707–0.903) and 0·755 (0.672–0.838), (3) Recurrence: 0·637 (0.51–0.·765) and 0·738 (0.649–0.826). Kaplan-Meier analyses demonstrate OS and RFS difference of >300 and >400 days respectively between low and high-risk groups. We have developed validated and externally tested radiomic-based prediction models. Such models could be integrated into the routine radiotherapy workflow, thus informing a personalised surveillance strategy at the point of treatment. Our work lays the foundations for future prospective clinical trials for quantitative personalised risk-stratification for surveillance following curative-intent radiotherapy for NSCLC.

Impact of curing conditions on basic dosimetric properties of silicone-based radiochromic dosimeters for photon and proton irradiation

SummaryThe National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for accelerated translation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools and ongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification using multicentre clinical studies.

Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, and clinical decision support, with the goal of delivering precision medicine. The authors provide a practical approach for successfully implementing a radiomic workflow from planning and conceptualization through manuscript writing. Applications in oncology typically are either classification tasks that involve computing the probability of a sample belonging to a category, such as benign versus malignant, or prediction of clinical events with a time-to-event analysis, such as overall survival. The radiomic workflow is multidisciplinary, involving radiologists and data and imaging scientists, and follows a stepwise process involving tumor segmentation, image preprocessing, feature extraction, model development, and validation. Images are curated and processed before segmentation, which can be performed on tumors, tumor subregions, or peritumoral zones. Extracted features typically describe the distribution of signal intensities and spatial relationship of pixels within a region of interest. To improve model performance and reduce overfitting, redundant and nonreproducible features are removed. Validation is essential to estimate model performance in new data and can be performed iteratively on samples of the dataset (cross-validation) or on a separate hold-out dataset by using internal or external data. A variety of noncommercial and commercial radiomic software applications can be used. Guidelines and artificial intelligence checklists are useful when planning and writing up radiomic studies. Although interest in the field continues to grow, radiologists should be familiar with potential pitfalls to ensure that meaningful conclusions can be drawn.

Background Textural features extracted from MRI potentially provide prognostic information additional to volume for influencing surgical management of cervical cancer. Purpose To identify textural features that differ between cervical tumors above and below the volume threshold of eligibility for trachelectomy and determine their value in predicting recurrence in patients with low-volume tumors. Methods Of 378 patients with Stage1–2 cervical cancer imaged prospectively (3T, endovaginal coil), 125 had well-defined, histologically-confirmed squamous or adenocarcinomas with >100 voxels (>0.07 cm3) suitable for radiomic analysis. Regions-of-interest outlined the whole tumor on T2-W images and apparent diffusion coefficient (ADC) maps. Textural features based on grey-level co-occurrence matrices were compared (Mann-Whitney test with Bonferroni correction) between tumors greater (n = 46) or less (n = 79) than 4.19 cm3. Clustering eliminated correlated variables. Significantly different features were used to predict recurrence (regression modelling) in surgically-treated patients with low-volume tumors and compared with a model using clinico-pathological features. Results Textural features (Dissimilarity, Energy, ClusterProminence, ClusterShade, InverseVariance, Autocorrelation) in 6 of 10 clusters from T2-W and ADC data differed between high-volume (mean ± SD 15.3 ± 11.7 cm3) and low-volume (mean ± SD 1.3 ± 1.2 cm3) tumors. (p, Highlights • Texture features differed significantly between high-compared to low-volume cervical tumors (p

Intra-tumour genetic heterogeneity (ITH) fuels cancer evolution. The role of clonal diversity and genetic complexity in the progression of clear-cell renal cell carcinomas (ccRCCs) has been characterised, but the ability to predict clinically relevant evolutionary trajectories remains limited. Here, towards enhancing this ability, we investigated spatial features of clonal diversification through a combined computational modelling and experimental analysis in the TRACERx Renal study. We observe through modelling that spatial patterns of tumour growth impact the extent and trajectory of subclonal diversification. Moreover, subpopulations with high clonal diversity, and parallel evolution events, are frequently observed near the tumour margin. In-silico time-course studies further showed that budding structures on the tumour surface could indicate future steps of subclonal evolution. Such structures were evident radiologically in 15 early-stage ccRCCs, raising the possibility that spatially resolved sampling of these regions, when combined with sequencing, may enable identification of evolutionary potential in early-stage tumours.

Previous work has shown that PRESAGE® can be used successfully to perform 3D dosimetric measurements of complex radiotherapy treatments. However, measurements near the sample edges are known to be difficult to achieve. This is an issue when the doses at air-material interfaces are of interest, for example when investigating the electron return effect (ERE) present in treatments delivered by magnetic resonance (MR)-linac systems. To study this effect, a set of 3.5 cm-diameter cylindrical PRESAGE® samples was uniformly irradiated with multiple dose fractions, using either a conventional linac or an MR-linac. The samples were imaged between fractions using an optical-CT, to read out the corresponding accumulated doses. A calibration between TPS-predicted dose and optical-CT pixel value was determined for individual dosimeters as a function of radial distance from the axis of rotation. This data was used to develop a correction that was applied to four additional samples of PRESAGE® of the same formulation, irradiated with 3D-CRT and IMRT treatment plans, to recover significantly improved 3D measurements of dose. An alternative strategy was also tested, in which the outer surface of the sample was physically removed prior to irradiation. Results show that for the formulation studied here, PRESAGE® samples have a central region that responds uniformly and an edge region of 6-7 mm where there is gradual increase in dosimeter response, rising to an over-response of 24%-36% at the outer boundary. This non-uniform dose response increases in both extent and magnitude over time. Both mitigation strategies investigated were successful. In our four exemplar studies, we show how discrepancies at edges are reduced from 13%-37% of the maximum dose to between 2 and 8%. Quantitative analysis shows that the 3D gamma passing rates rise from 90.4, 69.3, 63.7 and 43.6% to 97.3, 99.9, 96.7 and 98.9% respectively.

Background: Endogenous hormones are associated with breast cancer risk, but little is known about their role on breast tissue composition, a strong risk predictor. This study aims to investigate the relationship between growth and sex hormone levels and breast tissue composition in young nulliparous women. Methods: A cross-sectional study of 415 young (age ∼21.5 years) nulliparous women from an English prebirth cohort underwent a MRI examination of their breasts to estimate percent-water (a proxy for mammographic percent density) and provided a blood sample to measure plasma levels of growth factors (insulin-like growth factor-I, insulin-like growth factor-II, insulin growth factor-binding protein-3, growth hormone) and, if not on hormonal contraception (n = 117) sex hormones (dehydroepiandrosterone, androstenedione, testosterone, estrone, estadiol, sex hormone–binding globulin, prolactin). Testosterone (n = 330) and sex hormone–binding globulin (n = 318) were also measured at age 15.5 years. Regression models were used to estimate the relative difference (RD) in percent-water associated with one SD increment in hormone levels. Results: Estradiol at age 21.5 and sex hormone–binding globulin at age 21.5 were positively associated with body mass index (BMI)-adjusted percent-water [RD (95% confidence interval (CI)): 3% (0%–7%) and 3% (1%–5%), respectively]. There was a positive nonlinear association between androstenedione at age 21.5 and percent-water. Insulin-like growth factor-I and growth hormone at age 21.5 were also positively associated with BMI-adjusted percent-water [RD (95% CI): 2% (0%–4%) and 4% (1%–7%), respectively]. Conclusions: The findings suggest that endogenous hormones affect breast tissue composition in young nulliparous women. Impact: The well-established associations of childhood growth and development with breast cancer risk may be partly mediated by the role of endogenous hormones on breast tissue composition.

With the increasing complexity of radiotherapy treatments typical 1D and 2D quality assurance (QA) detectors may fail to detect out-of-plane dose discrepancies, in particular in the presence of motion. In this work, small samples of the PRESAGE® 3D radiochromic dosimeter were used in combination with a motion phantom to measure real-time multileaf collimator (MLC)-tracked radiotherapy treatments. A different sample of PRESAGE® was irradiated for each of three different irradiation scenarios: (1) static: static sample, without tracking (2) motion: moving sample, without tracking and (3) tracking: moving sample, with tracking. Our in-house software DynaTrack dynamically moves the linac's MLC leafs based on the target position. The doses delivered to the samples were reconstructed based on the recorded positions of the MLC and phantom during the beam delivery. PRESAGE® samples were imaged with an in-house optical-CT scanner. Comparison between simulated and measured 3D dose showed good agreement for all three irradiation scenarios (static: 99.2%; motion: 99.7%; tracking: 99.3% with a 3%, 2 mm and a 10% threshold local gamma criterion), failing only at the edges of the PRESAGE® samples (~ 6 mm). Given that the dose distributions deposited using the DynaTrack system have been independently verified, this experiment demonstrates the ability of PRESAGE to measure 3D doses correctly in a tracking context. We conclude that this methodology could be used in the future to validate the delivery of dynamic MLC-tracked radiotherapy.

Density assessment and lesion localization in breast MRI require accurate segmentation of breast tissues. A fast, computerized algorithm for volumetric breast segmentation, suitable for multi-centre data, has been developed, employing 3D bias-corrected fuzzy c-means clustering and morphological operations. The full breast extent is determined on T1-weighted images without prior information concerning breast anatomy. Left and right breasts are identified separately using automatic detection of the midsternum. Statistical analysis of breast volumes from eighty-two women scanned in a UK multi-centre study of MRI screening shows that the segmentation algorithm performs well when compared with manually corrected segmentation, with high relative overlap (RO), high true-positive volume fraction (TPVF) and low false-positive volume fraction (FPVF), and has an overall performance of RO 0.94 ± 0.05, TPVF 0.97 ± 0.03 and FPVF 0.04 ± 0.06, respectively (training: 0.93 ± 0.05, 0.97 ± 0.03 and 0.04 ± 0.06; test: 0.94 ± 0.05, 0.98 ± 0.02 and 0.05 ± 0.07).

Mammographic percent density, the proportion of fibroglandular tissue in the breast, is a strong risk factor for breast cancer, but its determinants in young women are unknown. We examined associations of magnetic resonance imaging (MRI) breast-tissue composition at age 21 years with prospectively collected measurements of body size and composition from birth to early adulthood and markers of puberty (all standardized) in a sample of 500 nulliparous women from a prebirth cohort of children born in Avon, United Kingdom, in 1991-1992 and followed up to 2011-2014. Linear models were fitted to estimate relative change in MRI percent water, which is equivalent to mammographic percent density, associated with a 1-standard-deviation increase in the exposure of interest. In mutually adjusted analyses, MRI percent water was positively associated with birth weight (relative change (RC) = 1.03, 95% confidence interval (CI): 1.00, 1.06) and pubertal height growth (RC = 1.07, 95% CI: 1.02, 1.13) but inversely associated with pubertal weight growth (RC = 0.86, 95% CI: 0.84, 0.89) and changes in dual-energy x-ray absorptiometry percent body fat mass (e.g., for change between ages 11 years and 13.5 years, RC = 0.96, 95% CI: 0.93, 0.99). Ages at thelarche and menarche were positively associated with MRI percent water, but these associations did not persist upon adjustment for height and weight growth. These findings support the hypothesis that growth trajectories influence breast-tissue composition in young women, whereas puberty plays no independent role.

Dosimetric quality assurance (QA) of the new Elekta Unity (MR-linac) will differ from the QA performed of a conventional linac due to the constant magnetic field, which creates an electron return effect (ERE). In this work we aim to validate PRESAGE® dosimetry in a transverse magnetic field, and assess its use to validate the research version of the Monaco TPS of the MR-linac. Cylindrical samples of PRESAGE® 3D dosimeter separated by an air gap were irradiated with a cobalt-60 unit, while placed between the poles of an electromagnet at 0.5 T and 1.5 T. This set-up was simulated in EGSnrc/Cavity Monte Carlo (MC) code and relative dose distributions were compared with measurements using 1D and 2D gamma criteria of 3% and 1.5 mm. The irradiation conditions were adapted for the MR-linac and compared with Monaco TPS simulations. Measured and EGSnrc/Cavity simulated profiles showed good agreement with a gamma passing rate of 99.9% for 0.5 T and 99.8% for 1.5 T. Measurements on the MR-linac also compared well with Monaco TPS simulations, with a gamma passing rate of 98.4% at 1.5 T. Results demonstrated that PRESAGE® can accurately measure dose and detect the ERE, encouraging its use as a QA tool to validate the Monaco TPS of the MR-linac for clinically relevant dose distributions at tissue-air boundaries.

Purpose: To compare two methods of automatic breast segmentation with each other and with manual segmentation in a large subject cohort. To discuss the factors involved in selecting the most appropriate algorithm for automatic segmentation and, in particular, to investigate the appropriateness of overlap measures (e.g., Dice and Jaccard coefficients) as the primary determinant in algorithm selection. Methods: Two methods of breast segmentation were applied to the task of calculating MRI breast density in 200 subjects drawn from the Avon Longitudinal Study of Parents and Children, a large cohort study with an MRI component. A semiautomated, bias-corrected, fuzzy C-means (BC-FCM) method was combined with morphological operations to segment the overall breast volume from in-phase Dixon images. The method makes use of novel, problem-specific insights. The resulting segmentation mask was then applied to the corresponding Dixon water and fat images, which were combined to give Dixon MRI density values. Contemporaneously acquired T-1- and T-2-weighted image datasets were analyzed using a novel and fully automated algorithm involving image filtering, landmark identification, and explicit location of the pectoral muscle boundary. Within the region found, fat-water discrimination was performed using an Expectation Maximization-Markov Random Field technique, yielding a second independent estimate of MRI density. Results: Images are presented for two individual women, demonstrating how the difficulty of the problem is highly subject-specific. Dice and Jaccard coefficients comparing the semiautomated BC-FCM method, operating on Dixon source data, with expert manual segmentation are presented. The corresponding results for the method based on T-1- and T-2-weighted data are slightly lower in the individual cases shown, but scatter plots and interclass correlations for the cohort as a whole show that both methods do an excellent job in segmenting and classifying breast tissue. Conclusions: Epidemiological results demonstrate that both methods of automated segmentation are suitable for the chosen application and that it is important to consider a range of factors when choosing a segmentation algorithm, rather than focus narrowly on a single metric such as the Dice coefficient. (C) 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. Materials and Methods Nine prospective patient studies and one prospective volunteer study, performed between 2006 and 2016 with research ethics committee approval and written informed consent from each subject, were included in this single-institution study. A total of 141 tumors and healthy organs were imaged twice (interval between repeated examinations, 45 minutes to 10 days, depending the on study) to assess the repeatability of median and mean ADC estimates. The Levene test was used to determine whether ADC repeatability differed between studies. The Pearson linear correlation coefficient was used to assess correlation between coefficient of variation (CoV) and the year the study started, study size, and volumes of tumors and healthy organs. The repeatability of ADC estimates from small, medium, and large tumors and healthy organs was assessed irrespective of study, and the Levene test was used to determine whether ADC repeatability differed between these groups. Results CoV aggregated across all studies was 4.1% (range for each study, 1.7%-6.5%). No correlation was observed between CoV and the year the study started or study size. CoV was weakly correlated with volume (r = -0.5, P = .1). Repeatability was significantly different between small, medium, and large tumors (P.05), with the lowest CoV (2.6%) for large tumors. There was a significant difference in repeatability between studies-a difference that did not persist after the study with the largest tumors was excluded. Conclusion ADC is a robust imaging metric with excellent repeatability in extracranial soft tissues across a wide range of tumor sites, sizes, patient populations, and imaging protocol variations. Online supplemental material is available for this article.

Measurements near the edges of PRESAGE® 3D dosimeters will be important for validating the electron return effect (ERE) that can occur at tissue-air interfaces during radiotherapy treatment delivered with the Elekta MR-linac. We investigate and characterize the spatially non-uniform response of small samples of PRESAGE® to radiation in a conventional linac. We develop a correction to compensate for these non-uniformities and obtain dose values near the dosimeter edges. Five samples from the same batch were uniformly irradiated in a water tank with a broad beam. The non-uniform response of the samples to radiation was investigated and a radial dose-correction function was generated from each sample to obtain a correction image. We then applied these correction images to another sample from the same batch, irradiated with four beams in an inhomogeneous medium, and compared this with the relevant simulated data. Additionally, we irradiated samples after physically removed their edges (axially and top and bottom edges). Higher sensitivity to radiation was observed at the edges (~6mm) of the samples in comparison with the central region. Applying the dose correction function improved agreement between simulations and measurements, but only partial correction was possible. A uniform response was observed on the samples with the edges removed, which we propose as the best option to measure dose at the edges of PRESAGE® samples.

The combination of MRI and radiotherapy on a single platform has the potential to revolutionise image-guided delivery of radiation doses. However, in order to realise these ambitions, good dosimetry must be available. The electron return effect gives rise to significant perturbations of dose at interfaces between tissue and air within the body, and this might lead to difficulties in dose compensation if air cavities move during treatment. In this article, I review briefly the ways in which the available methods of dosimetry are affected by the presence of magnetic fields and discuss the contribution that three-dimensional measurements can make to studies in this area. The methods of MRI and optical computed tomography have well known issues in imaging close to interfaces. These are described together with progress so far in providing solutions.

Medical image analysis remains a challenging application area for artificial intelligence. When applying machine learning, obtaining ground-truth labels for supervised learning is more difficult than in many more common applications of machine learning. This is especially so for datasets with abnormalities, as tissue types and the shapes of the organs in these datasets differ widely. However, organ detection in such an abnormal dataset may have many promising potential real-world applications, such as automatic diagnosis, automated radiotherapy planning, and medical image retrieval, where new multimodal medical images provide more information about the imaged tissues for diagnosis. Here, we test the application of deep learning methods to organ identification in magnetic resonance medical images, with visual and temporal hierarchical features learned to categorize object classes from an unlabeled multimodal DCE-MRI dataset so that only a weakly supervised training is required for a classifier. A probabilistic patch-based method was employed for multiple organ detection, with the features learned from the deep learning model. This shows the potential of the deep learning model for application to medical images, despite the difficulty of obtaining libraries of correctly labeled training datasets and despite the intrinsic abnormalities present in patient datasets.

Background Breast density, the amount of fibroglandular tissue in the adult breast for a women’s age and body mass index, is a strong biomarker of susceptibility to breast cancer, which may, like breast cancer risk itself, be influenced by events early in life. In the present study, we investigated the association between pre-natal exposures and breast tissue composition. Methods A sample of 500 young, nulliparous women (aged approximately 21 years) from a U.K. pre-birth cohort underwent a magnetic resonance imaging examination of their breasts to estimate percent water, a measure of the relative amount of fibroglandular tissue equivalent to mammographic percent density. Information on pre-natal exposures was collected throughout the mothers’ pregnancy and shortly after delivery. Regression models were used to investigate associations between percent water and pre-natal exposures. Mediation analysis, and a systematic review and meta-analysis of the published literature, were also conducted. Results Adjusted percent water in young women was positively associated with maternal height (p for linear trend [p t] = 0.005), maternal mammographic density in middle age (p t = 0.018) and the participant’s birth size (p t

Polymer gel dosimeters are fabricated from radiation sensitive chemicals which, upon irradiation, polymerize as a function of the absorbed radiation dose. These gel dosimeters, with the capacity to uniquely record the radiation dose distribution in three-dimensions (3D), have specific advantages when compared to one-dimensional dosimeters, such as ion chambers, and two-dimensional dosimeters, such as film. These advantages are particularly significant in dosimetry situations where steep dose gradients exist such as in intensity-modulated radiation therapy (IMRT) and stereotactic radiosurgery. Polymer gel dosimeters also have specific advantages for brachytherapy dosimetry. Potential dosimetry applications include those for low-energy x-rays, high-linear energy transfer (LET) and proton therapy, radionuclide and boron capture neutron therapy dosimetries. These 3D dosimeters are radiologically soft-tissue equivalent with properties that may be modified depending on the application. The 3D radiation dose distribution in polymer gel dosimeters may be imaged using magnetic resonance imaging (MRI), optical-computerized tomography (optical-CT), x-ray CT or ultrasound. The fundamental science underpinning polymer gel dosimetry is reviewed along with the various evaluation techniques. Clinical dosimetry applications of polymer gel dosimetry are also presented.

Anuran vocalizations are valuable in the determination of species identity and have the potential to discriminate intraspecific variation. We developed novel bioacoustic sampling techniques, based on Fast Fourier Transforms, to increase the precision and sensitivity of male advertisement call analysis and applied the method to European water frogs. This approach robustly separated the three types of north European water frogs (Rana ridibunda, R. lessonae and their viable, fertile hybrid R. esculenta) by their call subunit characteristics. The hybrid frog exhibited a high frequency call component absent from both the parental species. Furthermore, call analysis demonstrated significant intraspecific differences among populations of all three frog types. Call characters of R. ridibunda changed systematically as a function of longitude. This trend may reflect either clinal variation in selection pressures across Europe, or the consequences of drift following postglacial colonization from eastern refugia. High resolution vocalization analysis therefore provides a potentially useful method for investigating intraspecific differentiation and the phylogeographical origins of anuran distributions. © 2002 The Linnean Society of London. Biological Journal of the Linnean Society, 2002, 77, 355−365.

Rana lessonae Camerano, 1882 has a well-recorded range across Europe with its distribution recognised as far north as Sweden (lat. 60°N). In recent years new populations have been identified in Arendal. Norway and in Norfolk, England. This study aims to clarify the situation of the Norfolk frogs. Are they native or imported? This paper presents preliminary results of a new approach to this question. By means of various bioacoustic analyses calls of R. lessonae from populations across Europe and Scandinavia have been compared. The water frog species have been subjected to detailed bioacoustic analyses in the past and some characteristics for each species have been determined. We have demonstrated the use of these techniques and developed new methods of analysis that have enabled regional differences in R. lessonae calls to be determined between the populations of Norfolk, Germany and Poland. This in turn may elucidate the situation of the Norfolk Pool Frog.

MRI and laser-scanned optical-CT are widely reported as being three-dimensional readout methods for gel dosimetry. This preliminary study of proton irradiation of a PRESAGETM transparent solid plastic dosimeter is presented as a case study to illustrate the potential of a true-3D approach.

In this paper we describe the particular considerations relating to ultra-rapid, true-3D scanners based on charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) imaging detectors. Central to our ability to image dose distributions has been the development of novel materials whose optical properties change in response to radiation and a survey of these will be given. Finally, we will speculate briefly on the future of the technique. © 2006 IOP Publishing Ltd.

To investigate the feasibility of solid polymer dosimetry as an accurate 3-D dose verification applied to prostatic brachytherapy, the model 6711 Oncoseed TM was selected for a pilot study comparing experimental methods and Monte Carlo simulations. This study is presented as a typical case study of what can be achieved using solid polymer dosimetry. © 2006 IOP Publishing Ltd.

This paper describes the initial steps we have taken in establishing CCD based optical-CT as a viable alternative for 3-D radiation dosimetry. First, we compare the optical density (OD) measurements from a high quality test target and variable neutral density filter (VNDF). A modulation transfer function (MTF) of individual projections is derived for three positions of the sinusoidal test target within the scanning tank. Our CCD is then characterized in terms of its signal-to-noise ratio (SNR). Finally, a sample reconstruction of a scan of a PRESAGETM (registered trademark of Heuris Pharma, NJ, Skillman, USA.) dosimeter is given, demonstrating the capabilities of the apparatus.

Burst is an ultra-rapid imaging sequence that works by excitation of mag- netization using a series of regularly spaced, low flip-angle pulses, applied at the same time as a gradient in the read direction. In the original concept, this gradient is constant, and multiple echoes are refocused under a constant-read gradient. This article brings together the previous literature on the subject, placing the various developments within a common framework. The potential of the technique is discussed, with the aid of a comparison of the signal-to-noise ratio for the various Burst sequences previously proposed and a detailed case study of one of the more promising variants. © 2005 Wiley Periodicals, Inc. Concepts Magn Reson Part A 26A: 11-34, 2005

Preliminary optical density results on irradiated PRESAGE dosimeter are outlined in this article. PRESAGE is a solid dosimeter, based on a clear polyurethane combined with the leuco-dye leuco-malachite green. The purpose of these measurements was a) to obtain spectra for optimizing the wavelength of a new light source for the equipment and b) to obtain a dose-response relation. 10 PRESAGE cuvettes were given uniform doses from 0.1 to 40 Gy and later read out by spectrophotometer. The instrument used was CAMSPEC M350 Double Beam Spectrophotometer.

This article demonstrates the resolution capabilities of the CCD scanner under ideal circumstances and describes the first CCD-based optical CT experiments on a new class of dosimeter, known as PRESAGE™ (Heuris Pharma, Skillman, NJ).

Stereotactic Synchrotron Radiotherapy (SSRT) and Microbeam Radiation Therapy (MRT) are both novel approaches to treat brain tumor and potentially other tumors using synchrotron radiation. Although the techniques differ by their principles, SSRT and MRT share certain common aspects with the possibility of combining their advantages in the future. For MRT, the technique uses highly collimated, quasi-parallel arrays of X-ray microbeams between 50 and 600 keV. Important features of highly brilliant Synchrotron sources are a very small beam divergence and an extremely high dose rate. The minimal beam divergence allows the insertion of so called Multi Slit Collimators (MSC) to produce spatially fractionated beams of typically ~25e75 micron-wide microplanar beams separated by wider (100e400 microns center-to-center(ctc)) spaces with a very sharp penumbra. Peak entrance doses of several hundreds of Gy are extremely well tolerated by normal tissues and at the same time provide a higher therapeutic index for various tumor models in rodents. The hypothesis of a selective radio-vulnerability of the tumor vasculature versus normal blood vessels by MRT was recently more solidified. SSRT (Synchrotron Stereotactic Radiotherapy) is based on a local drug uptake of high-Z elements in tumors followed by stereotactic irradiation with 80 keV photons to enhance the dose deposition only within the tumor. With SSRT already in its clinical trial stage at the ESRF, most medical physics problems are already solved and the implemented solutions are briefly described, while the medical physics aspects in MRT will be discussed in more detail in this paper. © 2015 Published by Elsevier Ltd on behalf of Associazione Italiana di Fisica Medica. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

A quantitative imaging sequence has been developed to exploit the intrinsic sensitivity of Burst NMR data to molecular diffusion. In the scan time of a single spin echo experiment, it is possible to acquire many images of the same slice, with a different T(2) and diffusion weighting. Under favorable conditions, it is possible to obtain both the diffusion coefficient and T(2) from the same experiment; or, by correcting for T(2) relaxation using a control image, more precise diffusion coefficients may be measured. The quantitative values in rat brain are in agreement with those from conventional experiments. The major gains of this method are the potentially reduced scan time, the higher number of acquired images corresponding to different diffusion weightings, the reduced sensitivity to inter-scan motion artifact and to local variations in magnetic susceptibility, and an automatic co-registration between T(2) and diffusion images. Problems with the sequence include a lower signal-to-noise ratio than is achievable with diffusion-weighted spin-echo imaging, the limitation of measuring only in-plane components of diffusion and, at present, single-slice acquisition.

An accurate value for the saturation dose of PRESAGE® is important in elucidating the mechanism of the so-called quenching phenomenon in the 3-D dosimetry of proton beams. This quantity is difficult to obtain, because it involves measuring the optical density of a set of very highly attenuating samples. We present a novel method that makes use of the ability to irradiate microscopically-thin "slices" of a cuvette using microplanar beams from a synchrotron. Using the new method, we were able to measure optical densities of up to 50 cm-1 using a standard spectrophotometer, and we derived a value 14000 Gy for the saturation parameter D 37.

International audience; Optical CT is a method that can potentially provide both accurate dosimetry at high spatial resolution and 3-D visualisation over a large field-of-view in a single dataset. The major factors limiting spatial resolution in previous studies are analysed here and it is shown that improvements in equipment specification can overcome many of these. The need for ultra-high spatial resolution in the verification of microbeam radiation therapy verification is demonstrated and example images of a PRESAGE (R) sample are presented

Picture archiving and communication systems (PACS) provide limited flexibility for the development of novel research methods. By contrast, the research model of data access is more flexible but has vulnerabilities in numerous areas. No single monolithic application can fulfill the diverse and rapidly changing needs of the clinical imaging research community. Instead, the focus should be on the interoperability of preexisting systems. To a large extent, this can be achieved by means of a unified interface for storing and retrieving data. The concept of a research PACS combines the advantages of the clinical and research models of data access while eliminating the disadvantages. A research PACS streamlines the data management process. Instead of a single software program, it consists of a confederation of independent applications brought together by the ability to store and retrieve data in a common database. A prototype research PACS has been developed that is based on the Extensible Neuroimaging Archive Toolkit (XNAT) in association with two new in-house tools: a data selection tool and a data archiving tool. By taking as an example the comparison of regions of interest in multifunctional liver data, it was demonstrated that this framework allows a number of in-house and open-source applications originally designed to work on a stand-alone basis to be integrated into a unified workflow, with minimal redevelopment effort.

The principles governing the NMR behaviour of 1 H-containing fluids permeating porous solids, such as hydrocarbon reservoir rocks, are outlined. The additional capabilities of NMR imaging methods for characterizing these systems is considered. Experimental results are presented for NMR imaging applied to a model porous solid (alumina) and natural sandstone and limestone rocks, saturated with aqueous phases. Both three-dimensional and slice-selected two-dimensional FT spin echo methods are used and the images demonstrate the capability of NMRI in these systems to reveal internal structures of the porous solids. Simple strategies for characterizing the spatial heterogeneity of these materials in terms of histograms and correlation functions are proposed and a general pixel fitting program is used to examine some of the data in terms of such histograms and related property maps.

International audience; Optical Computed Tomography (CT) is a promising technique for dosimetry of Microbeam Radiation Therapy (MRT), providing high resolution 3D dose maps. Here different MRT irradiation geometries are visualised showing the potential of Optical CT as a tool for future MRT trials. The Peak-to-Valley dose ratio (PVDR) is calculated to be 7 at a depth of 3mm in the radiochromic dosimeter PRESAGE (R). This is significantly lower than predicted values and possible reasons for this are discussed

Chemical dosimeters, including PRESAGE® as used in optical CT, exhibit significant quenching effects in response to proton irradiation and this may limit their widespread uptake. This study performs careful measurements of the observed quenching of a recently developed variant of PRESAGE® in a 60 MeV proton beam and uses them to attempt an empirical correction of a simple superposition of two unmodulated beams.

High Intensity Focused ultrasound (HIFU) is a non-invasive cancer therapy that makes use of the mainly thermal effects of ultrasound to destroy tissue. In order to achieve reliable treatment planning, it is necessary to characterise the ultrasound source (transducer) and to understand how the wave propagates in tissue and the energy deposition in the focal region. This novel exploratory study investigated how HIFU affects PRESAGE®, an optical phantom used for radiotherapy dosimetry, which is potentially a rapid method of calibrating the transducer. Samples, of two different formulations, were exposed to focused ultrasound and imaged using Optical Computed Tomography. First results showed that, PRESAGE® changes colour on ultrasound exposure (darker green regions were observed) with the alterations being related to the acoustic power and sample composition. Future work will involve quantification of these alterations and understanding how to relate them to the mechanisms of action of HIFU.