Deep learning based MLC aperture and monitor unit prediction as a warm start for breast VMAT optimisation.

Objective. Automated treatment planning today is focussed on non-exact, two-step procedures. Firstly, dose-volume histograms (DVHs) or 3D dose distributions are predicted from the patient anatomy. Secondly, these are converted in multi-leaf collimator (MLC) apertures and monitor units (MUs) using a generic optimisation to obtain the final treatment plan. In contrast, we present a method to predict volumetric modulated arc therapy (VMAT) MLC apertures and MUs directly from patient anatomy using deep learning. The predicted plan is then provided as initialisation to the optimiser for fine-tuning.Approach. 148 patients (training: 101; validation: 23; test: 24), treated for right breast cancer, are replanned to obtain a homogeneous database of 3-arc VMAT plans (PTVBreast: 45.57 Gy; PTVBoost: 55.86 Gy) according to the clinical protocol, using RapidPlanTMwith automatic optimisation and extended convergence mode (clinical workflow). Projections of the CT and contours are created along the beam's eye view of all control points and given as input to a U-net type convolutional neural networks (CNN). The output are the MLC aperture and MU for all control points, from which a DICOM RTplan is built. This is imported and further optimised in the treatment planning system using automatic optimisation without convergence mode, with clinical PTV objectives and organs-at-risk (OAR) objectives based on the DVHs calculated from the imported plan (CNN workflow).Main results. Mean dose differences between the clinical and CNN workflow over the test set are 0.2 ± 0.5 Gy atD95%and 0.6 ± 0.4 Gy atD0.035ccof PTVBreastand -0.4 ± 0.3 Gy atD95%and 0.7 ± 0.3 Gy atD0.035ccof PTVBoost. For the OAR, they are -0.2 ± 0.2 Gy forDmean,heartand 0.04 ± 0.8 Gy forDmean,ipsilateral lung. The mean computation time is 60 and 25 min respectively.Significance. VMAT optimisation can be initialised by MLC apertures and MUs, directly predicted from patient anatomy using a CNN, reducing planning time with more than half while maintaining clinically acceptable plans. This procedure puts the planner in a supervising role over an AI-based treatment planning workflow.

Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy.

PURPOSE/OBJECTIVE(S): Precise segmentation of clinical target volumes (CTV) in breast cancer is indispensable for state-of-the art radiotherapy. Despite international guidelines, significant intra- and interobserver variability exists, negatively impacting treatment outcomes. The aim of this study is to evaluate the performance and efficiency of segmentation of CTVs in planning CT images of breast cancer patients using a 3D convolutional neural network (CNN) compared to the manual process. MATERIALS/METHODS: An expert radiation oncologist (RO) segmented all CTVs separately according to international guidelines in 150 breast cancer patients. This data was used to create, train and validate a 3D CNN. The network's performance was additionally evaluated in a test set of 20 patients. Primary endpoints are quantitative and qualitative analysis of the segmentation data generated by the CNN for each level specifically as well as for the total PTV to be irradiated. The secondary endpoint is the evaluation of time efficiency. RESULTS: In the test set, segmentation performance was best for the contralateral breast and the breast CTV and worst for Rotter's space and the internal mammary nodal (IMN) level. Analysis of impact on PTV resulted in non-significant over-segmentation of the primary PTV and significant under-segmentation of the nodal PTV, resulting in slight variations of overlap with OARs. Guideline consistency improved from 77.14% to 90.71% in favor of CNN segmentation while saving on average 24 minutes per patient with a median time of 35 minutes for pure manual segmentation. CONCLUSION: 3D CNN based delineation for breast cancer radiotherapy is feasible and performant, as scored by quantitative and qualitative metrics.

Interobserver variability in organ at risk delineation in head and neck cancer.

BACKGROUND: In radiotherapy inaccuracy in organ at risk (OAR) delineation can impact treatment plan optimisation and treatment plan evaluation. Brouwer et al. showed significant interobserver variability (IOV) in OAR delineation in head and neck cancer (HNC) and published international consensus guidelines (ICG) for OAR delineation in 2015. The aim of our study was to evaluate IOV in the presence of these guidelines. METHODS: HNC radiation oncologists (RO) from each Belgian radiotherapy centre were invited to complete a survey and submit contours for 5 HNC cases. Reference contours (OARref) were obtained by a clinically validated artificial intelligence-tool trained using ICG. Dice similarity coefficients (DSC), mean surface distance (MSD) and 95% Hausdorff distances (HD95) were used for comparison. RESULTS: Fourteen of twenty-two RO (64%) completed the survey and submitted delineations. Thirteen (93%) confirmed the use of delineation guidelines, of which six (43%) used the ICG. The OARs whose delineations agreed best with the OARref were mandible [median DSC 0.9, range (0.8-0.9); median MSD 1.1 mm, range (0.8-8.3), median HD95 3.4 mm, range (1.5-38.7)], brainstem [median DSC 0.9 (0.6-0.9); median MSD 1.5 mm (1.1-4.0), median HD95 4.0 mm (2.3-15.0)], submandibular glands [median DSC 0.8 (0.5-0.9); median MSD 1.2 mm (0.9-2.5), median HD95 3.1 mm (1.8-12.2)] and parotids [median DSC 0.9 (0.6-0.9); median MSD 1.9 mm (1.2-4.2), median HD95 5.1 mm (3.1-19.2)]. Oral cavity, cochleas, PCMs, supraglottic larynx and glottic area showed more variation. RO who used the consensus guidelines showed significantly less IOV (p = 0.008). CONCLUSIONS: Although ICG for delineation of OARs in HNC exist, they are only implemented by about half of RO participating in this study, which partly explains the delineation variability. However, this study highlights that guidelines alone do not suffice to eliminate IOV and that more effort needs to be done to accomplish further treatment standardisation, for example with artificial intelligence.

Deep learning for elective neck delineation: More consistent and time efficient.

BACKGROUND/PURPOSE: Delineation of the lymph node levels of the neck for irradiation of the elective clinical target volume in head and neck cancer (HNC) patients is time consuming and prone to interobserver variability (IOV), although international consensus guidelines exist. The aim of this study was to develop and validate a 3D convolutional neural network (CNN) for semi-automated delineation of all nodal neck levels, focussing on delineation accuracy, efficiency and consistency compared to manual delineation. MATERIAL/METHODS: The CNN was trained on a clinical dataset of 69 HNC patients. For validation, 17 lymph node levels were manually delineated in 16 new patients by two observers, independently, using international consensus guidelines. Automated delineations were generated by applying the CNN and were subsequently corrected by both observers separately as needed for clinical acceptance. Both delineations were performed two weeks apart and blinded to each other. IOV was quantified using Dice similarity coefficient (DSC), mean surface distance (MSD) and Hausdorff distance (HD). To assess automated delineation accuracy, agreement between automated and corrected delineations were evaluated using the same measures. To assess efficiency, the time taken for manual and corrected delineations were compared. In a second step, only the clinically relevant neck levels were selected and delineated, once again manually and by applying and correcting the network. RESULTS: When all lymph node levels were delineated, time taken for correcting automated delineations compared to manual delineations was significantly shorter for both observers (mean: 35 vs 52 min, p < 10-5). Based on DSC, automated delineation agreed best with corrected delineation for lymph node levels Ib, II-IVa, VIa, VIb, VIIa, VIIb (DSC >85%). Manual corrections necessary for clinical acceptance were 1.4 mm MSD on average and were especially low (<1mm) for levels II-IVa, VIa, VIIa and VIIb. IOV was significantly smaller with automated compared to manual delineations (MSD: 1.4 mm vs 2.5 mm, p < 10-11). When delineating only the clinically relevant neck levels, the correction time was also significantly shorter (mean: 8 vs 15 min, p < 10-5). Based on DSC, automated delineation agreed very well with corrected delineation (DSC > 87%). Manual corrections necessary for clinical acceptance were 1.3 mm MSD on average. IOV was significantly smaller with automated compared to manual delineations (MSD: 0.8 mm vs 2.3 mm, p < 10-3). CONCLUSION: The CNN developed for automated delineation of the elective lymph node levels in the neck in HNC was shown to be more efficient and consistent compared to manual delineation, which justifies its implementation in clinical practice.

Benefits of deep learning for delineation of organs at risk in head and neck cancer.

PURPOSE/OBJECTIVE: Precise delineation of organs at risk (OARs) in head and neck cancer (HNC) is necessary for accurate radiotherapy. Although guidelines exist, significant interobserver variability (IOV) remains. The aim was to validate a 3D convolutional neural network (CNN) for semi-automated delineation of OARs with respect to delineation accuracy, efficiency and consistency compared to manual delineation. MATERIAL/METHODS: 16 OARs were manually delineated in 15 new HNC patients by two trained radiation oncologists (RO) independently, using international consensus guidelines. OARs were also automatically delineated by applying the CNN and corrected as needed by both ROs separately. Both delineations were performed two weeks apart and blinded to each other. IOV between both ROs was quantified using Dice similarity coefficient (DSC) and average symmetric surface distance (ASSD). To objectify network accuracy, differences between automated and corrected delineations were calculated using the same similarity measures. RESULTS: Average correction time of the automated delineation was 33% shorter than manual delineation (23 vs 34 minutes) (p < 10-6). IOV improved significantly with network initialisation for nearly all OARs (p < 0.05), resulting in decreased ASSD averaged over all OARs from 1.9 to 1.2 mm. The network achieved an accuracy of 90% and 84% DSC averaged over all OARs for RO1 and RO2 respectively, with an ASSD of 0.7 and 1.5 mm, which was in 93% and 73% of the cases lower than the IOV. CONCLUSION: The CNN developed for automated OAR delineation in HNC was shown to be more efficient and consistent compared to manual delineation, which justify its implementation in clinical practice.

[Psychosis due to idiopathic basal ganglia calcification]. / Psychose door idiopathische calcificatie van de basale ganglia.

Idiopathic basal ganglia calcification is a rare neuropathological syndrome characterised by symmetrical and bilateral calcifications found primarily in the basal ganglia. Psychosis is describedas an acute presentation of idiopathic ganglia calcification. We describe the development of psychosis in a 48-year-old man, initially hospitalised on the neurology ward due to syncope. A ct scan of the brain showed bilateral, symmetrical calcification of the basal ganglia and nucleus dentatus. Laboratory research excluded other pathological disorders. The patient was referred to a psychiatric ward, where the administration of risperidone led to alleviation of his mental state. This case report underlines the importance of an accurate, comprehensive differential diagnosis and the associated significance of neuroimaging.

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

A spectroscopic study of the chromatic properties of GafChromicEBT3 films.

PURPOSE: This work provides an interpretation of the chromatic properties of GafChromicEBT3 films based on the chemical nature of the polydiacetylene (PDA) molecules formed upon interaction with ionizing radiation. The EBT3 films become optically less transparent with increasing radiation dose as a result of the radiation-induced polymerization of diacetylene monomers. In contrast to empirical quantification of the chromatic properties, less attention has been given to the underlying molecular mechanism that induces the strong decrease in transparency. METHODS: Unlaminated GafChromicEBT3 films were irradiated with a 6 MV photon beam to dose levels up to 20 Gy. The optical absorption properties of the films were investigated using visible (vis) spectroscopy. The presence of PDA molecules in the active layer of the EBT3 films was investigated using Raman spectroscopy, which probes the vibrational modes of the molecules in the layer. The vibrational modes assigned to PDA's were used in a theoretical vis-absorption model to fit our experimental vis-absorption spectra. From the fit parameters, one can assess the relative contribution of different PDA conformations and the length distribution of PDA's in the film. RESULTS: Vis-spectroscopy shows that the optical density increases with dose in the full region of the visible spectrum. The Raman spectrum is dominated by two vibrational modes, most notably by the ν(C≡C) and the ν(C=C) stretching modes of the PDA backbone. By fitting the vis-absorption model to experimental spectra, it is found that the active layer contains two distinct PDA conformations with different absorption properties and reaction kinetics. Furthermore, the mean PDA conjugation length is found to be 2-3 orders of magnitude smaller than the crystals PDA's are embedded in. CONCLUSIONS: Vis- and Raman spectroscopy provided more insight into the molecular nature of the radiochromic properties of EBT3 films through the identification of the excited states of PDA and the presence of two PDA conformations. The improved knowledge on the molecular composition of EBT3's active layer provides a framework for future fundamental modeling of the dose-response.

[Measuring alexithymia in fibromyalgia: the need for a multimodal measurement method to replace the TAS-20]. / Alexithymie bij fibromyalgie: meetinstrumenten; argumenten voor een multimodale benadering.

BACKGROUND: In an earlier publication that investigated alexithymia in fibromyalgia, we showed the Toronto Alexithymia Scale was the only instrument being used to measure alexithymia. AIM: To find out which instruments are currently available for measuring alexithymia, to compare the psychometric properties of these instruments and to decide whether some of the test methods involved should be used to give extra value to alexithymia research. METHOD: We conducted a systematic review of the literature in Medline/PubMed with a number of search terms. We selected articles relating to psychometric properties of the tests performed and decided whether they could be influenced by negative affect. RESULTS: We found that 14 different instruments were used to measure alexithymia. From our evaluation we excluded tests which had weak psychometric properties or had been inadequately assessed. There remained three observation scales and two self-report questionnaires, which had been adequately validated and whose relative strengths and weaknesses were compared. CONCLUSION: In view of these findings, we recommend that in studies of alexithymia in fibromyalgia a multimodal measurement method should be used rather than only the tas-20.

On organic emissions testing from indoor consumer products' use.

A wide range of consumer and personal care products may, during their use, release significant amounts of volatile organic compounds (VOC) into the air. The identification and quantification of the emissions from such sources is typically performed in emission test chambers. A major question is to what degree the obtained emissions are reproducible and directly applicable to real situations. The present work attempts partly to address this question by comparison of selected VOC emissions in specific consumer products tested in chambers of various dimensions. The measurements were performed in three test chambers of different volumes (0.26-20 m(3)). The analytic performance of the laboratories was rigorously assessed prior to chamber testing. The results show emission variation for major VOC (terpenes); however, it remains in general, within the same order of magnitude for all tests. This variability does not seem to correlate with the chamber volume. It rather depends on the overall testing conditions. The present work is undertaken in the frame of EPHECT European Project.

[Alexithymia in fibromyalgia: prevalence]. / Alexithymie bij fibromyalgie: prevalentie.

BACKGROUND: In fibromyalgia, problems of affect regulation are considered important. Alexithymia, too, is related to disturbed affect regulation. Recognising alexithymia is important with regard to the doctor-patient relationship, the pitfalls in this relationship and the therapeutic strategy. AIM: To look into the prevalence of alexithymia in fibromyalgia and find out which measures were used. METHOD: We reviewed the literature systematically using Medline, PubMed and Cochrane and key words. RESULTS: We found 11 relevant studies which revealed a significantly high prevalence of alexithymia in fibromyalgia patients, namely between 15 and 52%, whereas the prevalence in the general population was only 6 to 8%. All of these studies used the Toronto Alexithymia Scale (20-item or 26-item version) as the only test for alexithymia. Male fibromyalgia patients were not examined adequately, nor were patients in a residential setting. Three studies used patients with a painful chronic condition as a control group, but we did not find any studies that involved psychiatric control groups. CONCLUSION: In view of the high prevalence of alexithymia and the implications of this for therapy, we recommend that patients with fibromyalgia should be screened systematically for alexithymia. Further research involving male patients and residential fibromyalgia patients is required and future studies will have to include psychiatric control groups.

A comparative evaluation of cone beam CT and micro-CT on trabecular bone structures in the human mandible.

OBJECTIVES: The main purpose of this study was to determine the accuracy of cone beam CT (CBCT) in measuring the trabecular bone microstructure, in comparison with micro-CT. The subobjective was to examine to what extent bone quality assessment is influenced by X-ray tube current and voltage settings as well as soft tissue surrounding the bone. METHODS: Eight human mandibular bone samples were scanned using three different clinical exposure protocol within water (W1-3) and without water (NW1-3) by a high-resolution (80 µm) CBCT machine (3D Accuitomo 170(®); Morita, Kyoto, Japan). Subsequently, the samples underwent micro-CT scanning (SkyScan 1174®; SkyScan, Antwerp, Belgium). After image acquisition, similar volumes of interest of the trabecular structures captured with CBCT and micro-CT were aligned with each other. Segmentation was then performed, and the morphometric parameters were quantified within the volumes of interest by CTAn software (CTAnalyser(®); SkyScan, Antwerp, Belgium). Descriptive statistical analyses and multiple comparisons between all protocols were applied in R software. RESULTS: High positive Pearson's correlation coefficients were observed between CBCT and micro-CT protocols for all tested morphometric indices except for trabecular thickness. No significant differences were observed between all exposure protocols except for trabecular separation. When examining the soft-tissue effect on trabecular bone structures, no significant differences between NW (1-3) and W (1-3) protocols were observed for all variables. CONCLUSIONS: The present study demonstrated the potential of high-resolution CBCT imaging for in vivo applications of quantitative bone morphometry and bone quality assessment. However, the overestimation of morphometric parameters and acquisition settings in CBCT must be taken into account.

Calibrating page sized Gafchromic EBT3 films.

PURPOSE: The purpose is the development of a novel calibration method for dosimetry with Gafchromic EBT3 films. The method should be applicable for pretreatment verification of volumetric modulated arc, and intensity modulated radiotherapy. Because the exposed area on film can be large for such treatments, lateral scan errors must be taken into account. The correction for the lateral scan effect is obtained from the calibration data itself. METHODS: In this work, the film measurements were modeled using their relative scan values (Transmittance, T). Inside the transmittance domain a linear combination and a parabolic lateral scan correction described the observed transmittance values. The linear combination model, combined a monomer transmittance state (T(0)) and a polymer transmittance state (T(∞)) of the film. The dose domain was associated with the observed effects in the transmittance domain through a rational calibration function. On the calibration film only simple static fields were applied and page sized films were used for calibration and measurements (treatment verification). Four different calibration setups were considered and compared with respect to dose estimation accuracy. The first (I) used a calibration table from 32 regions of interest (ROIs) spread on 4 calibration films, the second (II) used 16 ROIs spread on 2 calibration films, the third (III), and fourth (IV) used 8 ROIs spread on a single calibration film. The calibration tables of the setups I, II, and IV contained eight dose levels delivered to different positions on the films, while for setup III only four dose levels were applied. Validation was performed by irradiating film strips with known doses at two different time points over the course of a week. Accuracy of the dose response and the lateral effect correction was estimated using the dose difference and the root mean squared error (RMSE), respectively. RESULTS: A calibration based on two films was the optimal balance between cost effectiveness and dosimetric accuracy. The validation resulted in dose errors of 1%-2% for the two different time points, with a maximal absolute dose error around 0.05 Gy. The lateral correction reduced the RMSE values on the sides of the film to the RMSE values at the center of the film. CONCLUSIONS: EBT3 Gafchromic films were calibrated for large field dosimetry with a limited number of page sized films and simple static calibration fields. The transmittance was modeled as a linear combination of two transmittance states, and associated with dose using a rational calibration function. Additionally, the lateral scan effect was resolved in the calibration function itself. This allows the use of page sized films. Only two calibration films were required to estimate both the dose and the lateral response. The calibration films were used over the course of a week, with residual dose errors ≤2% or ≤0.05 Gy.

Computational models for wall shear stress estimation in scaffolds: a comparative study of two complete geometries.

Fluid mechanical stimuli are known to upregulate cell differentiation and matrix formation. Since wall shear stress plays an important role various studies tried to estimate the scaffold fluid dynamic environment. However, because of the geometrical complexity, nearly all studies created their CFD model based on a submodel of the entire scaffold assuming that the model covers heterogeneity sufficiently. However to the authors' knowledge no study exist providing guidelines in this matter. In a previous study we demonstrated that submodels are influenced by the boundary conditions, inevitable when flow channels are chopped off. For the current study we therefore developed µCT based models of two complete scaffold geometries (one titanium and one hydroxyapatite). Imposing a 0.04 ml/min flow rate resulted in a surface area averaged wall shear stress of 1.41 mPa for titanium and 1.09 mPa for hydroxyapatite. In order to get insight in required model size we subdivided the domain in regions of different size. From our results we propose a model size between 6 and 10 times the average pore size. The wall shears stress should be calculated on a region at least one pore size away from the boundaries. These guidelines could be of use for computationally more costly simulations where it is not possible to simulate the complete scaffold domain.

SU-E-J-138: Fast 2-D Fiducial Marker Detection on Sequential MV Projections in Arc Therapy.

PURPOSE: To automatically detect intrafraction motion during arc radiotherapy for prostate cancer patients by tracking fiducial markers in two-dimensional MV images acquired using the treatment beam, in order to adjust radiation dose accordingly. METHODS: Four fiducial gold markers are implanted in a patient's prostate. Patients are irradiated using a Varian Linac 2100 C/D with RapidArc upgrade (Varian Medical Systems, Palo Alto, CA). MV images (1024 × 768 pixels, 0.392 × 0.392 mm2 pixel size) acquired during a 360 degree gantry rotation at a one second interval (5 degrees) are preprocessed by subtracting a smoothed version of the image to retain only high image frequencies. Edge detection is then applied, followed by a one pixel wide dilation and erosion to transform the edges into contiguous regions. Next, our method searches the centers of visible markers (i.e. not covered by the MLC), constrained by marker estimates from the planning CT. This is done by finding all contiguous regions and maximizing a marker-region distance criterion for every visible marker. A two-dimensional estimate correction over consecutive projections is also implemented to improve marker estimates during gantry rotation. RESULTS: We applied our method on four treatment fractions of the same patient. As such, a total of 191 projections with manually indicated marker ends as ground truth were used as validation. Markers were indicated twice on all images, to include observer errors. Results show a mean detection error of less than 0.5 mm in the projection image (standard deviation 0.6 mm), with an execution time of less than one second per image in matlab. Undetected markers and false positives mostly occurred at moving leaf boundaries, where marker visibility was determined by the observer. CONCLUSIONS: Preliminary findings demonstrate that this method can be used to detect intrafraction motion during arc radiotherapy by only using projected MV images. Research sponsored by Varian Medical Systems, Palo Alto, CA.

Development of micro-CT protocols for in vivo follow-up of mouse bone architecture without major radiation side effects.

In vivo micro-computed tomography (micro-CT) will offer unique information on the time-related changes in bone mass and structure of living mice, provided that radiation-induced side effects are prevented. Lowering the radiation dose, however, inevitably decreases the image quality. In this study we developed and validated a protocol for in vivo micro-CT imaging of mouse bone architecture that retains high quality images but avoids radiation-induced side effects on bone structure and hematological parameters. The left hindlimb of male C57Bl/6 mice was scanned in vivo at 3 consecutive time points, separated each time by a 2-week interval. Two protocols for in vivo micro-CT imaging were evaluated, with pixel sizes of 9 and 18 µm and administered radiation doses of 434 mGy and 166 mGy per scan, respectively. These radiation doses were found not to influence trabecular or cortical bone architecture in pre-pubertal or adult mice. In addition, there was no evidence for hematological side effects as peripheral blood cell counts and the colony-forming capacity of hematopoietic progenitor cells from bone marrow and spleen were not altered. Although the images obtained with these in vivo micro-CT protocols were more blurred than those obtained with high resolution (5 µm) ex vivo CT imaging, longitudinal follow-up of trabecular bone architecture in an orchidectomy model proved to be feasible using the 9 µm pixel size protocol in combination with a suitable bone segmentation technique (i.e. local thresholding). The image quality of the 18 µm pixel size protocol was too degraded for accurate bone segmentation and the use of this protocol is therefore restricted to monitor marked changes in bone structure such as bone metastatic lesions or fracture healing. In conclusion, we developed two micro-CT protocols which are appropriate for detailed as well as global longitudinal studies of mouse bone architecture and lack noticeable radiation-induced side effects.

Metabolic and type 1 cannabinoid receptor imaging of a transgenic rat model in the early phase of Huntington disease.

Several lines of evidence imply early alterations in metabolic and endocannabinoid neurotransmission in Huntington disease (HD). Using [(18)F]MK-9470 and small animal PET, we investigated for the first time cerebral changes in type 1 cannabinoid (CB1) receptor binding in vivo in pre-symptomatic and early symptomatic rats of HD (tgHD), in relation to glucose metabolism, morphology and behavioral testing for motor and cognitive function. Twenty-three Sprague-Dawley rats (14 tgHD and 9 wild-types) were investigated between the age of 2 and 11 months. Relative glucose metabolism and parametric CB1 receptor images were anatomically standardized to Paxinos space and analyzed voxel-wise. Volumetric microMRI imaging was performed to assess HD neuropathology. Within the first 10 months, bilateral volumes of caudate-putamen and lateral ventricles did not significantly differ between genotypes. Longitudinal- and genotype evolution showed that relative [(18)F]MK-9470 binding progressively decreased in the caudate-putamen and lateral globus pallidus of tgHD rats (-8.3%, p≤1.1×10(-5) at 5 months vs. -10.9%, p<1.5×10(-5) at 10 months). In addition, relative glucose metabolism increased in the bilateral sensorimotor cortex of 2-month-old tgHD rats (+8.1%, p≤1.5×10(-5)), where it was positively correlated to motor function at that time point. TgHD rats developed cognitive deficits at 6 and 11 months of age. Our findings point to early regional dysfunctions in endocannabinoid signalling, involving the lateral globus pallidus and caudate-putamen. In vivo CB1 receptor measurements using [(18)F]MK-9470 may thus be a useful early biomarker for HD. Our results also provide evidence of subtle motor and cognitive deficits at earlier stages than previously described.

Evaluation of the specificity and sensitivity of ferritin as an MRI reporter gene in the mouse brain using lentiviral and adeno-associated viral vectors.

The development of in vivo imaging protocols to reliably track transplanted cells or to report on gene expression is critical for treatment monitoring in (pre)clinical cell and gene therapy protocols. Therefore, we evaluated the potential of lentiviral vectors (LVs) and adeno-associated viral vectors (AAVs) to express the magnetic resonance imaging (MRI) reporter gene ferritin in the rodent brain. First, we compared the induction of background MRI contrast for both vector systems in immune-deficient and immune-competent mice. LV injection resulted in hypointense (that is, dark) changes of T(2)/T(2)(*) (spin-spin relaxation time)-weighted MRI contrast at the injection site, which can be partially explained by an inflammatory response against the vector injection. In contrast to LVs, AAV injection resulted in reduced background contrast. Moreover, AAV-mediated ferritin overexpression resulted in significantly enhanced contrast to background on T(2)(*)-weighted MRI. Although sensitivity associated with the ferritin reporter remains modest, AAVs seem to be the most promising vector system for in vivo MRI reporter gene imaging.

Model-based segmentation using graph representations.

A generic supervised segmentation approach is presented. The object is described as a graph where the vertices correspond to landmarks points and the edges define the landmark relations. Instead of building one single global shape model, a priori shape information is represented as a concatenation of local shape models that consider only local dependencies between connected landmarks. The objective function is obtained from a maximum a posteriori criterion and is build up of localized energies of both shape and landmark intensity information. The optimization problem is discretized by searching candidates for each landmark using individual landmark intensity descriptors. The discrete optimization problem is then solved using mean field annealing or dynamic programming techniques. The algorithm is validated for hand bone segmentation from RX datasets and for 3D liver segmentation from contrast enhanced CT images.

Image quality vs radiation dose of four cone beam computed tomography scanners.

OBJECTIVES: To evaluate image quality by examining segmentation accuracy and assess radiation dose for cone beam CT (CBCT) scanners. METHODS: A skull phantom, scanned by a laser scanner, and a contrast phantom were used to evaluate segmentation accuracy. The contrast phantom consisted of a polymethyl methacrylate (PMMA) cylinder with cylindrical inserts of air, bone and PMMA. The phantoms were scanned on the (1) Accuitomo 3D, (2) MercuRay, (3) NewTom 3G, (4) i-CAT and (5) Sensation 16. The structures were segmented with an optimal threshold. Thicknesses of the bone of the mandible and the diameter of the cylinders in the contrast phantom were measured across lines at corresponding places in the CT image vs a ground truth. The accuracy was in the 95th percentile of the difference between corresponding measurements. The correlation between accuracy in skull and contrast phantom was calculated. The radiation dose was assessed by DPI(100,c) (dose profile integral (100,c)) at the central hole of a CT dose index (CTDI) phantom. RESULTS: The results for the DPI(100,c) were 107 mGy mm for (1), 1569 mGy mm for (2), 446 mGy mm for (3), 249 mGy mm for (4) and 1090 mGy mm for (5). The segmentations in the contrast phantom were submillimeter accurate in all scanners. The segmentation accuracy of the mandible was 2.9 mm for (1), 4.2 mm for (2), 3.4 mm for (3), 1.0 mm for (4) and 1.2 mm for (5). The correlation between measurements in the contrast and skull phantom was below 0.37 mm. CONCLUSIONS: The best radiation dose vs image quality was found for the i-CAT.