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A hyperthermia treatment requires accurate, patient-specific treatment planning. This planning is based on 3D anatomical models which are generally derived from computed tomography. Because of its superior soft tissue contrast, magnetic resonance imaging (MRI) information can be introduced to improve the quality of these 3D patient models and therefore the treatment planning itself. Thus, we present here an automatic atlas-based segmentation algorithm for MR images of the head and neck. Our method combines multiatlas local weighting fusion with intensity modelling. The accuracy of the method was evaluated using a leave-one-out cross validation experiment over a set of 11 patients for which manual delineation were available. The accuracy of the proposed method was high both in terms of the Dice similarity coefficient (DSC) and the 95th percentile Hausdorff surface distance (HSD) with median DSC higher than 0.8 for all tissues except sclera. For all tissues, except the spine tissues, the accuracy was approaching the interobserver agreement/variability both in terms of DSC and HSD. The positive effect of adding the intensity modelling to the multiatlas fusion decreased when a more accurate atlas fusion method was used.Using the proposed approach we improved the performance of the approach previously presented for H&N hyperthermia treatment planning, making the method suitable for clinical application.

To provide an adequate level of protection for humans from exposure to radio-frequency (RF) electromagnetic fields (EMF) and to assure that any adverse health effects are avoided. The basic restrictions in terms of the specific energy absorption rate (SAR) were prescribed by IEEE and ICNIRP. An example of a therapeutic application of non-ionizing EMF is hyperthermia (HT), in which intense RF energy is focused at a target region. Deep HT in the head and neck (H&N) region involves inducing energy at 434 MHz for 60 min on target. Still, stray exposure of the brain is considerable, but to date only very limited side-effects were observed. The objective of this study is to investigate the stringency of the current basic restrictions by relating the induced EM dose in the brain of patients treated with deep head and neck (H&N) HT to the scored acute health effects. We performed a simulation study to calculate the induced peak 10 g spatial-averaged SAR (psSAR₁₀g) in the brains of 16 selected H&N patients who received the highest SAR exposure in the brain, i.e. who had the minimum brain-target distance and received high forwarded power during treatment. The results show that the maximum induced SAR in the brain of the patients can exceed the current basic restrictions (IEEE and ICNIRP) on psSAR₁₀g for occupational environments by 14 times. Even considering the high local SAR in the brain, evaluation of acute effects by the common toxicity criteria (CTC) scores revealed no indication of a serious acute neurological effect. In addition, this study provides pioneering quantitative human data on the association between maximum brain SAR level and acute adverse effects when brains are exposed to prolonged RF EMF.

To assess whether deformable registration between CT and MR images can be used to avoid patient immobilization, we compared registration accuracy in various scenarios, with and without immobilization equipment. Whereas both deformable registration and the use of immobilization equipment improved the registration accuracy, the combination gave, the best alignment. (C) 2015 Published by Elsevier Ireland Ltd.

Among various possible health effects of mobile phone radiation, the risk of inducing cancer has the strongest interest of laymen and health organizations. Recently, the Interphone epidemiological study investigated the association between the estimated Radio Frequency (RF) dose from mobile phones and the risk of developing a brain tumor. Their dosimetric analysis included over 100 phone models but only two homogeneous head phantoms. So, the potential impact of individual morphological features on global and local RF absorption in the brain was not investigated. In this study, we performed detailed dosimetric simulations for 20 head models and quantified the variation of RF dose in different brain regions as a function of head morphology. Head models were exposed to RF fields from generic mobile phones at 835 and 1900 MHz in the "tilted" and "cheek" positions. To evaluate the local RF dose variation, we used and compared two different post-processing methods, that is, averaging specific absorption rate (SAR) over Talairach regions and over sixteen predefined 1 cm(3) cube-shaped field-sensors. The results show that the variation in the averaged SAR among the heads can reach up to 16.4 dB at a 1 cm(3) cube inside the brain (field-sensor method) and alternatively up to 15.8 dB in the medulla region (Talairach method). In conclusion, we show head morphology as an important uncertainty source for dosimetric studies of mobile phones. Therefore, any dosimetric analysis dealing with RF dose at a specific region in the brain (e.g., tumor risk analysis) should be based upon real morphology.

Hyperthermia treatment planning (HTP) is used in the head and neck region (H&N) for pretreatment optimization, decision making, and real-time HTP-guided adaptive application of hyperthermia. In current clinical practice, HTP is based on power-absorption predictions, but thermal dose-effect relationships advocate its extension to temperature predictions. Exploitation of temperature simulations requires region- and temperature-specific thermal tissue properties due to the strong thermoregulatory response of H&N tissues. The purpose of our work was to develop a technique for patient group-specific optimization of thermal tissue properties based on invasively measured temperatures, and to evaluate the accuracy achievable. Data from 17 treated patients were used to optimize the perfusion and thermal conductivity values for the Pennes bioheat equation-based thermal model. A leave-one-out approach was applied to accurately assess the difference between measured and simulated temperature (a dagger T). The improvement in a dagger T for optimized thermal property values was assessed by comparison with the a dagger T for values from the literature, i.e., baseline and under thermal stress. The optimized perfusion and conductivity values of tumor, muscle, and fat led to an improvement in simulation accuracy (a dagger T: 2.1 +/- 1.2 A degrees C) compared with the accuracy for baseline (a dagger T: 12.7 A +/- 11.1 A degrees C) or thermal stress (a dagger T: 4.4 A +/- 3.5 A degrees C) property values. The presented technique leads to patient group-specific temperature property values that effectively improve simulation accuracy for the challenging H&N region, thereby making simulations an elegant addition to invasive measurements. The rigorous leave-one-out assessment indicates that improvements in accuracy are required to rely only on temperature-based HTP in the clinic.

PURPOSE: To investigate the feasibility of using deformable registration in clinical practice to fuse MR and CT images of the head and neck for treatment planning.METHOD AND MATERIALS: A state-of-the-art deformable registration algorithm was optimized, evaluated, and compared with rigid registration. The evaluation was based on manually annotated anatomic landmarks and regions of interest in both modalities. We also developed a multiparametric registration approach, which simultaneously aligns T1- and T2-weighted MR sequences to CT. This was evaluated and compared with single-parametric approaches.RESULTS: Our results show that deformable registration yielded a better accuracy than rigid registration, without introducing unrealistic deformations. For deformable registration, an average landmark alignment of approximatively 1.7 mm was obtained. For all the regions of interest excluding the cerebellum and the parotids, deformable registration provided a median modified Hausdorff distance of approximatively 1 mm. Similar accuracies were obtained for the single-parameter and multiparameter approaches.CONCLUSIONS: This study demonstrates that deformable registration of head-and-neck CT and MR images is feasible, with overall a significanlty higher accuracy than for rigid registration.

Accumulating evidence shows that hyperthermia improves head-and-neck cancer treatment. Over the last decade, we introduced a radiofrequency applicator, named HYPERcollar, which enables local heating also of deep locations in this region. Based on clinical experience, we redesigned the HYPERcollar for improved comfort, reproducibility and operator handling. In the current study, we analyze the redesign from an electromagnetic point of view. We show that a higher number of antennas and their repositioning allow for a substantially improved treatment quality. Combined with the much better reproducibility of the water bolus, this will substantially minimize the risk of underexposure. All improvements combined enable a reduction of hot-spot prominence (hot-spot to target SAR quotient) by 32% at an average of 981 W, which drastically reduces the probability for system power to become a treatment limiting source. Moreover, the power deposited in the target selectively can be increased by more than twofold. Hence, we expect that the HYPERcollar redesign currently under construction allows us to double the clinically applied power to the target while reducing the hot-spots, resulting in higher temperatures and, consequently, better clinical outcome.

Purpose: Dosimetry during deep local hyperthermia treatments in the head and neck currently relies on a limited number of invasively placed temperature sensors. The purpose of this study was to assess the feasibility of 3D dosimetry based on patient-specific temperature simulations and sensory feedback. Materials and methods: The study includes 10 patients with invasive thermometry applied in at least two treatments. Based on their invasive thermometry, we optimised patient-group thermal conductivity and perfusion values for muscle, fat and tumour using a 'leave-one-out' approach. Next, we compared the accuracy of the predicted temperature (Delta T) and the hyperthermia treatment quality (Delta T50) of the optimisations based on the patient-group properties to those based on patient-specific properties, which were optimised using previous treatment measurements. As a robustness check, and to enable comparisons with previous studies, we optimised the parameters not only for an applicator efficiency factor of 40%, but also for 100% efficiency. Results: The accuracy of the predicted temperature (Delta T) improved significantly using patient-specific tissue properties, i.e. 1.0 degrees C (inter-quartile range (IQR) 0.8 degrees C) compared to 1.3 degrees C (IQR 0.7 degrees C) for patient-group averaged tissue properties for 100% applicator efficiency. A similar accuracy was found for optimisations using an applicator efficiency factor of 40%, indicating the robustness of the optimisation method. Moreover, in eight patients with repeated measurements in the target region, Delta T50 significantly improved, i.e. Delta T50 reduced from 0.9 degrees C (IQR 0.8 degrees C) to 0.4 degrees C (IQR 0.5 degrees C) using an applicator efficiency factor of 40%. Conclusion: This study shows that patient-specific temperature simulations combined with tissue property reconstruction from sensory data provides accurate minimally invasive 3D dosimetry during hyperthermia treatments: T50 in sessions without invasive measurements can be predicted with a median accuracy of 0.4 degrees C.

In current clinical practice, head and neck (HN) hyperthermia treatment planning (HTP) is solely based on computed tomography (CT) images. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast over CT. The purpose of the authors' study is to investigate the relevance of using MRI in addition to CT for patient modeling in HN HTP.CT and MRI scans were acquired for 11 patients in an immobilization mask. Three observers manually segmented on CT, MRI T1 weighted (MRI-T1w), and MRI T2 weighted (MRI-T2w) images the following thermo-sensitive tissues: cerebrum, cerebellum, brainstem, myelum, sclera, lens, vitreous humor, and the optical nerve. For these tissues that are used for patient modeling in HN HTP, the interobserver variation of manual tissue segmentation in CT and MRI was quantified with the mean surface distance (MSD). Next, the authors compared the impact of CT and CT and MRI based patient models on the predicted temperatures. For each tissue, the modality was selected that led to the lowest observer variation and inserted this in the combined CT and MRI based patient model (CT and MRI), after a deformable image registration. In addition, a patient model with a detailed segmentation of brain tissues (including white matter, gray matter, and cerebrospinal fluid) was created (CT and MRIdb). To quantify the relevance of MRI based segmentation for HN HTP, the authors compared the predicted maximum temperatures in the segmented tissues (Tmax) and the corresponding specific absorption rate (SAR) of the patient models based on (1) CT, (2) CT and MRI, and (3) CT and MRIdb.In MRI, a similar or reduced interobserver variation was found compared to CT (maximum of median MSD in CT: 0.93 mm, MRI-T1w: 0.72 mm, MRI-T2w: 0.66 mm). Only for the optical nerve the interobserver variation is significantly lower in CT compared to MRI (median MSD in CT: 0.58 mm, MRI-T1w: 1.27 mm, MRI-T2w: 1.40 mm). Patient models based on CT (Tmax: 38.0 °C) and CT and MRI (Tmax: 38.1 °C) result in similar simulated temperatures, while CT and MRIdb (Tmax: 38.5 °C) resulted in significantly higher temperatures. The SAR corresponding to these temperatures did not differ significantly.Although MR imaging reduces the interobserver variation in most tissues, it does not affect simulated local tissue temperatures. However, the improved soft-tissue contrast provided by MRI allows generating a detailed brain segmentation, which has a strong impact on the predicted local temperatures and hence may improve simulation guided hyperthermia.

Among various possible health effects of mobile phone radiation, the risk of inducing cancer has the strongest interest of laymen and health organizations. Recently, the Interphone epidemiological study investigated the association between the estimated Radio Frequency (RF) dose from mobile phones and the risk of developing a brain tumor. Their dosimetric analysis included over 100 phone models but only two homogeneous head phantoms. So, the potential impact of individual morphological features on global and local RF absorption in the brain was not investigated. In this study, we performed detailed dosimetric simulations for 20 head models and quantified the variation of RF dose in different brain regions as a function of head morphology. Head models were exposed to RF fields from generic mobile phones at 835 and 1900 MHz in the "tilted" and "cheek" positions. To evaluate the local RF dose variation, we used and compared two different post-processing methods, that is, averaging specific absorption rate (SAR) over Talairach regions and over sixteen predefined 1 cm(3) cube-shaped field-sensors. The results show that the variation in the averaged SAR among the heads can reach up to 16.4 dB at a 1 cm(3) cube inside the brain (field-sensor method) and alternatively up to 15.8 dB in the medulla region (Talairach method). In conclusion, we show head morphology as an important uncertainty source for dosimetric studies of mobile phones. Therefore, any dosimetric analysis dealing with RF dose at a specific region in the brain (e.g., tumor risk analysis) should be based upon real morphology.

Purpose: Magnetic resonance thermometry (MRT) is an attractive means to non-invasively monitor in vivo temperature during head and neck hyperthermia treatments because it can provide multi-dimensional temperature information with high spatial resolution over large regions of interest. However, validation of MRT measurements in a head and neck clinical setup is crucial to ensure the temperature maps are accurate. Here we demonstrate a unique approach for temperature probe sensor localisation in head and neck hyperthermia test phantoms. Methods: We characterise the proton resonance frequency shift temperature coefficient and validate MRT measurements in an oil-gel phantom by applying a combination of MR imaging and 3D spline fitting for accurate probe localisation. We also investigate how uncertainties in both the probe localisation and the proton resonance frequency shift (PRFS) thermal coefficient affect the registration of fibre-optic reference temperature probe and MRT readings. Results: The method provides a two-fold advantage of sensor localisation and PRFS thermal coefficient calibration. We provide experimental data for two distinct head and neck phantoms showing the significance of this method as it mitigates temperature probe localisation errors and thereby increases accuracy of MRT validation results. Conclusions: The techniques presented here may be used to simplify calibration experiments that use an interstitial heating device, or any heating method that provides rapid and spatially localised heat distributions. Overall, the experimental verification of the data registration and PRFS thermal coefficient calibration technique provides a useful benchmarking method to maximise MRT accuracy in any similar context.

Item does not contain fulltext OBJECTIVE: Exercise intolerance is common in total cavopulmonary connection (TCPC) patients. It has been suggested that power loss (Ploss) inside the TCPC plays a role in reduced exercise performance. Our objective is to establish the role of Ploss inside the TCPC during increased flow, simulating exercise in a patient-specific way. METHODS: Cardiac MRI (CMR) was used to obtain flow rates from the caval veins during rest and increased flow, simulating exercise with dobutamine. A 3D reconstruction of the TCPC was created using CMR data. Computational fluid dynamics (CFD) simulations were performed to calculate Ploss inside the TCPC structure for rest and stress conditions. To reflect the flow distribution during exercise, a condition where inferior caval vein (IVC) flow was increased twofold compared with rest was added. 29 TCPC patients (15 intra-atrial lateral tunnel (ILT) and 14 extracardiac conduit (ECC)) were included. RESULTS: Mean Ploss at rest was 1.36 +/- 0.94 (ILT) and 3.20 +/- 1.26 (ECC) mW/m(2) (p

Hyperthermia treatment of head and neck tumors requires accurate treatment planning, based on 3D patient models that are derived from segmented 3D images. These segmentations are currently obtained by manual outlining of the relevant tissue regions, which is a tedious and time-consuming procedure (≈ 8 h) limiting the clinical applicability of hyperthermia treatment. In this context, the authors present and evaluate an automatic segmentation algorithm for CT images of the head and neck.The proposed method combines anatomical information, based on atlas registration, with local intensity information in a graph cut framework. The method is evaluated with respect to ground truth manual delineation and compared with multiatlas-based segmentation on a dataset of 18 labeled CT images using the Dice similarity coefficient (DSC), the mean surface distance (MSD), and the Hausdorff surface distance (HSD) as evaluation measures. On a subset of 13 labeled images, the influence of different labelers on the method's accuracy is quantified and compared with the interobserver variability.For the DSC, the proposed method performs significantly better for the segmentation of all the tissues, except brain stem and spinal cord. The MSD shows a significant improvement for optical nerve, eye vitreous humor, lens, and thyroid. For the HSD, the proposed method performs significantly better for eye vitreous humor and brainstem. The proposed method has a significantly better score for DSC, MSD, and HSD than the multiatlas-based method for the eye vitreous humor. For the majority of the tissues (8/11) the segmentation accuracy of the proposed method is approaching the interobserver agreement. The authors' method showed better robustness to variations in atlas labeling compared with multiatlas segmentation. Moreover, the method improved the segmentation reproducibility compared with human observer's segmentations.In conclusion, the proposed framework provides in an accurate automatic segmentation of head and neck tissues in CT images for the generation of 3D patient models, which improves reproducibility, and substantially reduces labor involved in therapy planning.

Outcome optimization of hyperthermia tumor treatment in the head and neck requires accurate hyperthermia treatment planning. Hyperthermia treatment planning is based on tissue segmentation for 3D patient model generation. We present here an automatic atlas-based segmentation algorithm for the organs at risk from CT images of the head and neck. To overcome the large anatomical variability, atlas registration and intensity-based classification were combined. A cost function composed of an intensity energy term, a spatial prior energy term based on the atlas registration and a regularization term is globally minimized using graph cut. The method was evaluated by measuring Dice similarity coefficient, mean and Hausdorff surface distances with respect to manual delineation. Overall a high correspondence was found with Dice similarity coefficient higher than 0.86 and a mean distance lower than the voxel resolution.

Purpose: In current clinical practice, head and neck (H&N) hyperthermia treatment planning (HTP) is solely based on computed tomography (CT) images. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast over CT. The purpose of the authors’ study is to investigate the relevance of using MRI in addition to CT for patient modeling in H&N HTP. Methods: CT and MRI scans were acquired for 11 patients in an immobilization mask. Three observers manually segmented on CT, MRI T1 weighted (MRI-T1w), and MRI T2 weighted (MRI-T2w) images the following thermo-sensitive tissues: cerebrum, cerebellum, brainstem, myelum, sclera, lens, vitreous humor, and the optical nerve. For these tissues that are used for patient modeling in H&N HTP, the interobserver variation of manual tissue segmentation in CT and MRI was quantified with the mean surface distance (MSD). Next, the authors compared the impact of CT and CT and MRI based patient models on the predicted temperatures. For each tissue, the modality was selected that led to the lowest observer variation and inserted this in the combined CT and MRI based patient model (CT and MRI), after a deformable image registration. In addition, a patient model with a detailed segmentation of brain tissues (including white matter, gray matter, and cerebrospinal fluid) was created (CT and MRIdb). To quantify the relevance of MRI based segmentation for H&N HTP, the authors compared the predicted maximum temperatures in the segmented tissues (T max) and the corresponding specific absorption rate (SAR) of the patient models based on (1) CT, (2) CT and MRI, and (3) CT and MRIdb. Results: In MRI, a similar or reduced interobserver variation was found compared to CT (maximum of median MSD in CT: 0.93 mm, MRI-T1w: 0.72 mm, MRI-T2w: 0.66 mm). Only for the optical nerve the interobserver variation is significantly lower in CT compared to MRI (median MSD in CT: 0.58 mm, MRI-T1w: 1.27 mm, MRI-T2w: 1.40 mm). Patient models based on CT (T max: 38.0 °C) and CT and MRI (T max: 38.1 °C) result in similar simulated temperatures, while CT and MRIdb (T max: 38.5 °C) resulted in significantly higher temperatures. The SAR corresponding to these temperatures did not differ significantly. Conclusions: Although MR imaging reduces the interobserver variation in most tissues, it does not affect simulated local tissue temperatures. However, the improved soft-tissue contrast provided by MRI allows generating a detailed brain segmentation, which has a strong impact on the predicted local temperatures and hence may improve simulation guided hyperthermia.

Purpose: Hyperthermia treatment of head and neck tumors requires accurate treatment planning, based on 3D patient models that are derived from segmented 3D images. These segmentations are currently obtained by manual outlining of the relevant tissue regions, which is a tedious and time-consuming procedure (∼8 h) limiting the clinical applicability of hyperthermia treatment. In this context, the authors present and evaluate an automatic segmentation algorithm for CT images of the head and neck. Methods: The proposed method combines anatomical information, based on atlas registration, with local intensity information in a graph cut framework. The method is evaluated with respect to ground truth manual delineation and compared with multiatlas-based segmentation on a dataset of 18 labeled CT images using the Dice similarity coefficient (DSC), the mean surface distance (MSD), and the Hausdorff surface distance (HSD) as evaluation measures. On a subset of 13 labeled images, the influence of different labelers on the method's accuracy is quantified and compared with the interobserver variability. Results: For the DSC, the proposed method performs significantly better for the segmentation of all the tissues, except brain stem and spinal cord. The MSD shows a significant improvement for optical nerve, eye vitreous humor, lens, and thyroid. For the HSD, the proposed method performs significantly better for eye vitreous humor and brainstem. The proposed method has a significantly better score for DSC, MSD, and HSD than the multiatlas-based method for the eye vitreous humor. For the majority of the tissues (8/11) the segmentation accuracy of the proposed method is approaching the interobserver agreement. The authors' method showed better robustness to variations in atlas labeling compared with multiatlas segmentation. Moreover, the method improved the segmentation reproducibility compared with human observer's segmentations. Conclusions: In conclusion, the proposed framework provides in an accurate automatic segmentation of head and neck tissues in CT images for the generation of 3D patient models, which improves reproducibility, and substantially reduces labor involved in therapy planning.

Monitoring of RF hyperthermia treatment by means of Magnetic Resonance Imaging is the logical thing to do. MRI is a versatile imaging modality capable of imaging anatomy, physiology and moreover, temperature. Thus, detailed treatment monitoring of hyperthermia becomes possible. In the last 10 to 15 years various successful MRI/hyperthermia systems have been built. In this same period, RF technology in MRI has undergone a tremendous expansion. This growth originates mainly from the RF challenges of going towards higher magnetic field strengths. Some of these developments offer very new exciting opportunities for hyperthermia and especially for hybrid MRI/hyperthermia systems. In this paper we discuss some of these prospects paving the way to next generation hybrid hyperthermia/MRI systems