Dual-Centre Harmonised Multimodal Positron Emission Tomography/Computed Tomography Image Radiomic Features and Machine Learning Algorithms for Non-small Cell Lung Cancer Histopathological Subtype Phenotype Decoding

AIMS

We aimed to build radiomic models for classifying non-small cell lung cancer (NSCLC) histopathological subtypes through a dual-centre dataset and comprehensively evaluate the effect of ComBat harmonisation on the performance of single- and multimodality radiomic models.

MATERIALS AND METHODS

A public dataset of NSCLC patients from two independent centres was used. Two image fusion methods, namely guided filtering-based fusion and image fusion based on visual saliency map and weighted least square optimisation, were used. Radiomic features were extracted from each scan, including first-order, texture and moment-invariant features. Subsequently, ComBat harmonisation was applied to the extracted features from computed tomography (CT), positron emission tomography (PET) and fused images to correct the centre effect. For feature selection, least absolute shrinkage and selection operator (Lasso) and recursive feature elimination (RFE) were investigated. For machine learning, logistic regression (LR), support vector machine (SVM) and AdaBoost were evaluated for classifying NSCLC subtypes. Training and evaluation of the models were carried out in a robust framework to offset plausible errors and performance was reported using area under the curve, balanced accuracy, sensitivity and specificity before and after harmonisation. N-way ANOVA was used to assess the effect of different factors on the performance of the models.

RESULTS

Support vector machine fed with selected features by recursive feature elimination from a harmonised PET feature set achieved the highest performance (area under the curve = 0.82) in classifying NSCLC histopathological subtypes. Although the performance of the models did not significantly improve for CT images after harmonisation, the performance of PET and guided filtering-based fusion feature signatures significantly improved for almost all models. Although the selection of the image modality and feature selection methods was effective on the performance of the model (ANOVA P-values <0.001), machine learning and harmonisation did not change the performance significantly (ANOVA P-values = 0.839 and 0.292, respectively).

CONCLUSION

This study confirmed the potential of radiomic analysis on PET, CT and hybrid images for histopathological classification of NSCLC subtypes.

Histological and chemical damage induced by microcystin-LR and microcystin-RR on land snail Helix aspersa tissues after acute exposure

Microcystins (MCs) are the most common cyanotoxins with more than 200 variants. Among these cyanotoxins, microcystin-LR (MC-LR) and microcystin-RR (MC-RR) are the most studied congeners due to their high toxicity and frequent occurrence in surface waters. MC-LR has been detected in more than 75% of natural cyanobacteria bloom, along with other toxic and less toxic congeners. Accumulation of several microcystins variants (MC-LR and MC-RR) has been confirmed in aquatic snails exposed naturally or in the laboratory to toxic blooms. Thus, this paper aims to compare the biochemical and histological impact of both toxic variants (microcystin-LR and microcystin-RR) and their mixed form on a bioindicator, the land snail Helix aspersa. During experiments, snails were gavaged with a single acute dose (0.5 μg/g) of purified MC-LR, MC-RR, or mixed MC-LR + MC-RR (0.25 + 0.25 μg/g). After 96 h of exposure, effects on the hepatopancreas, kidney, intestine and lungs were assessed by histological observations and analysis of oxidative stress biomarkers. The results show that a small dose of MCs variants can increase the non-enzymatic antioxidant glutathione (GSH), inhibit glutathione-s-transferase (GST) level and trigger a defense system by activating glutathione peroxidase (GPx), catalase (CAT) and superoxide dismutase (SOD). Microcystin-RR causes serious anomalies in the hepatopancreas and kidney than Microcystin-LR. The organ most affected is the kidney. The damage caused by MC-LR + MC-RR is greater than that caused by single variants.

Survival and Proliferation under Severely Hypoxic Microenvironments Using Cell-Laden Oxygenating Hydrogels

Different strategies have been employed to provide adequate nutrients for engineered living tissues. These have mainly revolved around providing oxygen to alleviate the effects of chronic hypoxia or anoxia that result in necrosis or weak neovascularization, leading to failure of artificial tissue implants and hence poor clinical outcome. While different biomaterials have been used as oxygen generators for in vitro as well as in vivo applications, certain problems have hampered their wide application. Among these are the generation and the rate at which oxygen is produced together with the production of the reaction intermediates in the form of reactive oxygen species (ROS). Both these factors can be detrimental for cell survival and can severely affect the outcome of such studies. Here we present calcium peroxide (CPO) encapsulated in polycaprolactone as oxygen releasing microparticles (OMPs). While CPO releases oxygen upon hydrolysis, PCL encapsulation ensures that hydrolysis takes place slowly, thereby sustaining prolonged release of oxygen without the stress the bulk release can endow on the encapsulated cells. We used gelatin methacryloyl (GelMA) hydrogels containing these OMPs to stimulate survival and proliferation of encapsulated skeletal myoblasts and optimized the OMP concentration for sustained oxygen delivery over more than a week. The oxygen releasing and delivery platform described in this study opens up opportunities for cell-based therapeutic approaches to treat diseases resulting from ischemic conditions and enhance survival of implants under severe hypoxic conditions for successful clinical translation.

Clinical predictive factors of histological chorioamnionitis: case-control study

Introduction

Histological chorioamnionitis or "intrauterine inflammation or infection" (Triple I) it is an acute inflammation of amniotic membrane, chorionic plate and umbilical cord.

Subject

To assess in the event of the clinical predictive factors associated to histological chorioamnionitis.

Methods

Prospective examination of 50 placentas from aberrant pregnancies, and 50 placentas from 'normal' deliveries. The Placentas analyzed by the conventional histopathology method, and the severity of chorioamnionitis was classified histologically according to the intensity and the topography of placental inflammation.The clinical and histopathological features of the study groups were introduced into the SPSS 13 database (License University Mohammed V-Rabat).

Results

36/50 placentas of aberrant pregnancies showed a histological chorioamnionitis often associated to a funisitis, and 11/50 normal placentas have shown some lesions of histological chorioamnionitis mainly grade one without funisitis.On the other hand we noted a statistically significant association between histological chorioamnionitis and premature rupture of the membranes (PROM) over than 12h (p < 0.001).

Conclusions

Our study confirmed the predominance of histological chorioamnionitis lesions in clinically suspected cases of chorioamnionitis with 72% versus 22% in the controls group.Among the clinical parameters studied, only the premature rupture of the Membranes was shown a statistically significant association with the appearance of histological signs of chorioamnionitis.In conclusion, chorioamnionitis is sometimes clinically silent. Morphological placental study could be a confirmation of this pathology, which is predominantly associated to PROM over than 12 h.

Radiomics for classification of bone mineral loss: A machine learning study

PURPOSE

The purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.

MATERIALS AND METHODS

A total of 147 patients were included in this retrospective single-center study. There were 12 men and 135 women with a mean age of 56.88±10.6 (SD) years (range: 28-87 years). For each patient, seven regions including four lumbar and three femoral including trochanteric, intertrochanteric and neck were segmented on bone mineral densitometry images and 54 texture features were extracted from the regions. The performance of four feature selection methods, including classifier attribute evaluation (CLAE), one rule attribute evaluation (ORAE), gain ratio attribute evaluation (GRAE) and principal components analysis (PRCA) along with four classification methods, including random forest (RF), random committee (RC), K-nearest neighbor (KN) and logit-boost (LB) were evaluated. Four classification categories, including osteopenia vs. normal, osteoporosis vs. normal, osteopenia vs. osteoporosis and osteoporosis+osteopenia vs. osteoporosis were examined for the defined seven regions. The classification model performances were evaluated using the area under the receiver operator characteristic curve (AUC).

RESULTS

The AUC values ranged from 0.50 to 0.78. The combination of methods RF+CLAE, RF+ORAE and RC+ORAE yielded highest performance (AUC=0.78) in discriminating between osteoporosis and normal state in the trochanteric region. The combinations of RF+PRCA and LB+PRCA had the highest performance (AUC=0.76) in discriminating between osteoporosis and normal state in the neck region.

CONCLUSION

The machine learning radiomic approach can be considered as a new method for bone mineral deficiency disease classification using bone mineral densitometry image features.

Robustness of post-reconstruction and direct kinetic parameter estimates under rigid head motion in dynamic brain PET imaging

OBJECTIVE

Dynamic PET imaging is extensively used in brain imaging to estimate parametric maps. Inter-frame motion can substantially disrupt the voxel-wise time-activity curves (TACs), leading to erroneous maps during kinetic modelling. Therefore, it is important to characterize the robustness of kinetic parameters under various motion and kinetic model related factors.

METHODS

Fully 4D brain simulations ([¹⁵O]H₂O and [¹⁸F]FDG dynamic datasets) were performed using a variety of clinically observed motion patterns. Increasing levels of head motion were investigated as well as varying temporal frames of motion initiation. Kinetic parameter estimation was performed using both post-reconstruction kinetic analysis and direct 4D image reconstruction to assess bias from inter-frame emission blurring and emission/attenuation mismatch.

RESULTS

Kinetic parameter bias heavily depends on the time point of motion initiation. Motion initiated towards the end of the scan results in the most biased parameters. For the [¹⁸F]FDG data, k₄ is the more sensitive parameter to positional changes, while K₁ and blood volume were proven to be relatively robust to motion. Direct 4D image reconstruction appeared more sensitive to changes in TACs due to motion, with parameter bias spatially propagating and depending on the level of motion.

CONCLUSION

Kinetic parameter bias highly depends upon the time frame at which motion occurred, with late frame motion-induced TAC discontinuities resulting in the least accurate parameters. This is of importance during prolonged data acquisition as is often the case in neuro-receptor imaging studies. In the absence of a motion correction, use of TOF information within 4D image reconstruction could limit the error propagation.

Combined evaluation of myocardial perfusion and coronary morphology in the identification of subclinical CAD

Purpose: To evaluate the mean effective radiation dose of 13N-ammonia PET/CT and ECGpulsing CT angiography (CTA) in the evaluation of myocardial perfusion, myocardial blood flow (MBF) and coronary morphology for the identification of subclinical CAD. Patients, material, methods: Following rest-stress 13N-ammonia PET/CT perfusion imaging and MBF quantification, ECG-pulsing CTA at a pulse window of 70% of the R-R cycle was performed in ten healthy controls and in sixteen individuals with cardiovascular risk factors. Individual radiation dose exposure for ECG-pulsing CTA was estimated from the dose-length product. Results: PET demonstrated normal perfusion in all study individuals, while hyperemic MBFs during dipyridamole stimulation and the myocardial flow reserve (MFR) in cardiovascular risk individuals were significantly lower than in healthy controls (1.34 ± 0.26 vs. 2.28 ± 0.47 ml/g/min and 1.48 ± 0.39 vs. 3.24 ± 0.81, both p . 0.0001). Further, ECG-pulsing CTA identified mild calcified and non-calcified coronary plaque burden in 7 (43%) individuals of the cardiovascular risk group. Rest-stress 13N-ammonia PET/CT perfusion study yielded a mean effective radiation dose of 3.07 ± 0.06 mSv (2.07 ± 0.06 mSv from the rest-stress 13N-ammonia injections and 1.0 mSv from the 2 CT transmission scans), while ECG-pulsing CTA was associated with 5.57 ± 2.00 mSv. The mean effective radiation dose of the combined 13N-ammonia PET/CT and ECG-pulsing CTA exams in the evaluation of myocardial perfusion and coronary morphology was 8.0 ± 1.5 mSv. Conclusion: 13N-ammonia PET/CT and ECG-pulsing CTA affords cardiac hybrid imaging studies in the evaluation of subclinical CAD with a relatively low mean effective radiation exposure of 8.0 ± 1.5mSv.

Application of adaptive kinetic modelling for bias propagation reduction in direct 4D image reconstruction

Parametric imaging in thoracic and abdominal PET can provide additional parameters more relevant to the pathophysiology of the system under study. However, dynamic data in the body are noisy due to the limiting counting statistics leading to suboptimal kinetic parameter estimates. Direct 4D image reconstruction algorithms can potentially improve kinetic parameter precision and accuracy in dynamic PET body imaging. However, construction of a common kinetic model is not always feasible and in contrast to post-reconstruction kinetic analysis, errors in poorly modelled regions may spatially propagate to regions which are well modelled. To reduce error propagation from erroneous model fits, we implement and evaluate a new approach to direct parameter estimation by incorporating a recently proposed kinetic modelling strategy within a direct 4D image reconstruction framework. The algorithm uses a secondary more general model to allow a less constrained model fit in regions where the kinetic model does not accurately describe the underlying kinetics. A portion of the residuals then is adaptively included back into the image whilst preserving the primary model characteristics in other well modelled regions using a penalty term that trades off the models. Using fully 4D simulations based on dynamic [(15)O]H2O datasets, we demonstrate reduction in propagation-related bias for all kinetic parameters. Under noisy conditions, reductions in bias due to propagation are obtained at the cost of increased noise, which in turn results in increased bias and variance of the kinetic parameters. This trade-off reflects the challenge of separating the residuals arising from poor kinetic modelling fits from the residuals arising purely from noise. Nonetheless, the overall root mean square error is reduced in most regions and parameters. Using the adaptive 4D image reconstruction improved model fits can be obtained in poorly modelled regions, leading to reduced errors potentially propagating to regions of interest which the primary biologic model accurately describes. The proposed methodology, however, depends on the secondary model and choosing an optimal model on the residual space is critical in improving model fits.

Contourlet-based active contour model for PET image segmentation

PURPOSE

PET-guided radiation therapy treatment planning, clinical diagnosis, assessment of tumor growth, and therapy response rely on the accurate delineation of the tumor volume and quantification of tracer uptake. Most PET image segmentation techniques proposed thus far are suboptimal in the presence of heterogeneity of tracer uptake within the lesion. This work presents an active contour model approach based on the method of Chan and Vese ["Active contours without edges," IEEE Trans. Image Process. 10, 266-277 (2001)] designed to take into account the high level of statistical uncertainty (noise) and to handle the heterogeneity of tumor uptake typically present in PET images.

METHODS

In the proposed method, the fitting terms in the Chan-Vese formulation are modified by introducing new input images, including the smoothed version of the original image using anisotropic diffusion filtering (ADF) and the contourlet transform of the image. The advantage of utilizing ADF for image smoothing is that it avoids blurring the object's edges and preserves the average activity within a region, which is important for accurate PET quantification. Moreover, incorporating the contourlet transform of the image into the fitting terms makes the energy functional more effective in directing the evolving curve toward the object boundaries due to the enhancement of the tumor-to-background ratio (TBR). The proper choice of the energy functional parameters has been formulated by making a clear consensus based on tumor heterogeneity and TBR levels. This cautious parameter selection leads to proper handling of heterogeneous lesions. The algorithm was evaluated using simulated phantom and clinical studies, where the ground truth and histology, respectively, were available for accurate quantitative analysis of the segmentation results. The proposed technique was also compared to a number of previously reported image segmentation techniques.

RESULTS

The results were quantitatively analyzed using three evaluation metrics, including the spatial overlap index (SOI), the mean relative error (MRE), and the mean classification error (MCE). Although the performance of the proposed method was analogous to other methods for some datasets, overall the proposed algorithm outperforms all other techniques. In the largest clinical group comprising nine datasets, the proposed approach improved the SOI from 0.41±0.14 obtained using the best-performing algorithm to 0.54±0.12 and reduced the MRE from 54.23±103.29 to 0.19±16.63 and the MCE from 112.86±69.07 to 60.58±18.43.

CONCLUSIONS

The proposed segmentation technique is superior to other representative segmentation techniques in terms of highest overlap between the segmented volume and the ground truth∕histology and minimum relative and classification errors. Therefore, the proposed active contour model can result in more accurate tumor volume delineation from PET images.

K-edge ratio method for identification of multiple nanoparticulate contrast agents by spectral CT imaging

OBJECTIVE

Recently introduced energy-sensitive X-ray CT makes it feasible to discriminate different nanoparticulate contrast materials. The purpose of this work is to present a K-edge ratio method for differentiating multiple simultaneous contrast agents using spectral CT.

METHODS

The ratio of two images relevant to energy bins straddling the K-edge of the materials is calculated using an analytic CT simulator. In the resulting parametric map, the selected contrast agent regions can be identified using a thresholding algorithm. The K-edge ratio algorithm is applied to spectral images of simulated phantoms to identify and differentiate up to four simultaneous and targeted CT contrast agents.

RESULTS

We show that different combinations of simultaneous CT contrast agents can be identified by the proposed K-edge ratio method when energy-sensitive CT is used. In the K-edge parametric maps, the pixel values for biological tissues and contrast agents reach a maximum of 0.95, whereas for the selected contrast agents, the pixel values are larger than 1.10. The number of contrast agents that can be discriminated is limited owing to photon starvation. For reliable material discrimination, minimum photon counts corresponding to 140 kVp, 100 mAs and 5-mm slice thickness must be used.

CONCLUSION

The proposed K-edge ratio method is a straightforward and fast method for identification and discrimination of multiple simultaneous CT contrast agents.

ADVANCES IN KNOWLEDGE

A new spectral CT-based algorithm is proposed which provides a new concept of molecular CT imaging by non-iteratively identifying multiple contrast agents when they are simultaneously targeting different organs.

Evaluation of whole-body MR to CT deformable image registration

Multimodality image registration plays a crucial role in various clinical and research applications. The aim of this study is to present an optimized MR to CT whole‐body deformable image registration algorithm and its validation using clinical studies. A 3D intermodality registration technique based on B‐spline transformation was performed using optimized parameters of the elastix package based on the Insight Toolkit (ITK) framework. Twenty‐eight (17 male and 11 female) clinical studies were used in this work. The registration was evaluated using anatomical landmarks and segmented organs. In addition to 16 anatomical landmarks, three key organs (brain, lungs, and kidneys) and the entire body volume were segmented for evaluation. Several parameters — such as the Euclidean distance between anatomical landmarks, target overlap, Dice and Jaccard coefficients, false positives and false negatives, volume similarity, distance error, and Hausdorff distance — were calculated to quantify the quality of the registration algorithm. Dice coefficients for the majority of patients (>75%) were in the 0.8–1 range for the whole body, brain, and lungs, which satisfies the criteria to achieve excellent alignment. On the other hand, for kidneys, Dice coefficients for volumes of 25% of the patients meet excellent volume agreement requirement, while the majority of patients satisfy good agreement criteria (>0.6). For all patients, the distance error was in 0–10 mm range for all segmented organs. In summary, we optimized and evaluated the accuracy of an MR to CT deformable registration algorithm. The registered images constitute a useful 3D whole‐body MR‐CT atlas suitable for the development and evaluation of novel MR‐guided attenuation correction procedures on hybrid PET‐MR systems.

PACS number: 07.05.Pj

[Human genetics of tuberculosis]

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major public health problem worldwide, resulting in 8.7 million new cases and 1.4 million deaths each year. One third of the world's population is exposed to M. tuberculosis and, after exposure, most, but not all, individuals become infected. Among infected subjects, only a minority (∼10%) will eventually develop clinical disease, which is typically either a primary, often extra-pulmonary, TB in children, or a reactivation, pulmonary TB in adults. Considerable genetic epidemiological evidence has accumulated to support a major role for human genetic factors in the development of TB. Numerous association studies with various candidate genes have been conducted in pulmonary TB, with very few consistent results. Recent genome-wide association studies revealed only a modest role for two inter-genic polymorphisms. However, a first major locus for pulmonary TB was mapped to chromosome 8q12-q13 in a Moroccan population after a genome-wide linkage screen. Using a similar strategy, two other major loci controlling TB infection were recently identified. While the precise identification of these major genes is ongoing, the other fascinating observation of these last years was the demonstration that TB can also reflect a Mendelian predisposition. Following the findings obtained in the syndrome of Mendelian susceptibility to mycobacterial diseases, several children with complete IL-12Rβ1 deficiency, were found to have severe TB as their sole phenotype. Overall, these recent findings provide the proof of concept that the human genetics of TB involves a continuous spectrum from Mendelian to complex predisposition with intermediate major gene involvement. The understanding of the molecular genetic basis of TB will have fundamental immunological and medical implications, in particular for the development of new vaccines and treatments.

Accurate Monte Carlo modeling and performance assessment of the X-PET subsystem of the FLEX triumph preclinical PET/CT scanner

PURPOSE

X-PET is a commercial small animal PET scanner incorporating several innovative designs to achieve improved performance. It is employed as a PET subsystem in the FLEX Triumph preclinical PET/CT scanner, the first commercial small animal PET/CT scanner worldwide. The authors report on a novel Monte Carlo (MC) model designed for the evaluation of performance parameters of the X-PET METHODS: The Geant4 Application for Tomographic Emission (GATE) MC code was used as a simulation tool. The authors implemented more accurate modeling of the geometry of detector blocks and associated electronic chains, including dead-time and time-independent parameters, compared to previously presented MC models of the X-PET scanner. Validation of the MC model involved comparison between simulated and measured performance parameters of the X-PET, including spatial resolution, sensitivity, and noise equivalent count rate (NECR). Thereafter, various simulations were performed to assess scanner performance parameters according to NEMA NU 4-2008 standards with the aim to present a reliable Monte Carlo platform for small animal PET scanner design optimization.

RESULTS

The average differences between simulated and measured results were 11.2%, 33.3%, and 9.1% for spatial resolution, sensitivity, and NECR, respectively. The average system absolute sensitivity was 2.7%. Furthermore, the peak true count rate, peak NECR, and scatter fraction were 2050 kcps, 1520 kcps, and 4.7%, respectively, for a mouse phantom and 1017 kcps, 469 kcps, and 18.2%, respectively, for a rat phantom. Spatial resolution was also measured in ten different positions at two axial locations. The radial, tangential, and axial FWHM ranged from 1.31 to 1.96 mm, 1.17 to 2.11 mm, and 1.77 to 2.44 mm, respectively, as the radial position varied from 0 to 25 mm at the centre of the axial field-of-view.

CONCLUSIONS

The developed MC simulation platform provides a reliable tool for performance evaluation of small animal PET scanners and has the potential to be used in other applications such as detector design optimization, correction of image degrading factors such as randoms, scatter, intercrystal scatter, parallax error, and partial volume effect.

Design and performance evaluation of a whole-body Ingenuity TF PET-MRI system

The Ingenuity TF PET-MRI is a newly released whole-body hybrid PET-MR imaging system with a Philips time-of-flight GEMINI TF PET and Achieva 3T X-series MRI system. Compared to PET-CT, modifications to the positron emission tomography (PET) gantry were made to avoid mutual system interference and deliver uncompromising performance which is equivalent to the standalone systems. The PET gantry was redesigned to introduce magnetic shielding for the photomultiplier tubes (PMTs). Stringent electromagnetic noise requirements of the MR system necessitated the removal of PET gantry electronics to be housed in the PET-MR equipment room. We report the standard NEMA measurements for the PET scanner. PET imaging and performance measurements were done at Geneva University Hospital as described in the NEMA Standards NU 2-2007 manual. The scatter fraction (SF) and noise equivalent count rate (NECR) measurements with the NEMA cylinder (20 cm diameter) were repeated for two larger cylinders (27 cm and 35 cm diameter), which better represent average and heavy patients. A NEMA/IEC torso phantom was used for overall assessment of image quality. The transverse and axial resolution near the center was 4.7 mm. Timing and energy resolution of the PET-MR system were measured to be 525 ps and 12%, respectively. The results were comparable to PET-CT systems demonstrating that the effect of design modifications required on the PET system to remove the harmful effect of the magnetic field on the PMTs was negligible. The absolute sensitivity of this scanner was 7.0 cps kBq(-1), whereas SF was 26%. NECR measurements performed with cylinders having three different diameters, and image quality measurements performed with IEC phantom yielded excellent results. The Ingenuity TF PET-MRI represents the first commercial whole-body hybrid PET-MRI system. The performance of the PET subsystem was comparable to the GEMINI TF PET-CT system using phantom and patient studies. It is conceived that advantages of hybrid PET-MRI will become more evident in the near future.

Analysis of wall shear stress around a competitive swimmer using 3D Navier-Stokes equations in CFD

This paper deals with the flow dynamics around a competitive swimmer during underwater glide phases occurring at the start and at every turn. The influence of the head position, namely lifted up, aligned and lowered, on the wall shear stress and the static pressure distributions is analyzed. The problem is considered as 3D and in steady hydrodynamic state. Three velocities (1.4 m/s, 2.2 m/s and 3.1 m/s) that correspond to inter-regional, national and international swimming levels are studied. The flow around the swimmer is assumed turbulent. The Reynolds-averaged Navier-Stokes (RANS) equations are solved with the standard k-ω turbulent model by using the CFD (computational fluid dynamics) numerical method based on a volume control approach. Numerical simulations are carried out with the ANSYS FLUENT® CFD code. The results show that the wall shear stress increases with the velocity and consequently the drag force opposing the movement of the swimmer increases as well. Also, high wall shear stresses are observed in the areas where the body shape, globally rigid in form, presents complex surface geometries such as the head, shoulders, buttocks, heel and chest.

Compton scattered imaging based on the V-line radon transform and its medical imaging applications

The Radon transform (RT) on straight lines deals as mathematical foundation for many tomographic modalities (e.g. Xray scanner, Positron Emission Tomography), using only primary radiation. In this paper, we consider a new RT defined on a pair of half-lines forming a letter V, arising from the modeling a two-dimensional emission imaging process by Compton scattered gamma rays. We establish its analytic inverse, which is shown to support the feasibility of the reconstruction of a two-dimensional image from scattered radiation collected on a one-dimensional collimated camera. Moreover, a filtered back-projection inversion method is also constructed. Its main advantages are algorithmic efficiency and computational rapidity. We present numerical simulations to illustrate the working. To sum up, the V-line RT leads not only to a new imaging principle, but also to a new concept of detector with high energetic resolution capable to collect the scattered radiation.

Quantifying the effect of anode surface roughness on diagnostic x-ray spectra using Monte Carlo simulation

PURPOSE

The accurate prediction of x-ray spectra under typical conditions encountered in clinical x-ray examination procedures and the assessment of factors influencing them has been a longstanding goal of the diagnostic radiology and medical physics communities. In this work, the influence of anode surface roughness on diagnostic x-ray spectra is evaluated using MCNP4C-based Monte Carlo simulations.

METHODS

An image-based modeling method was used to create realistic models from surface-cracked anodes. An in-house computer program was written to model the geometric pattern of cracks and irregularities from digital images of focal track surface in order to define the modeled anodes into MCNP input file. To consider average roughness and mean crack depth into the models, the surface of anodes was characterized by scanning electron microscopy and surface profilometry. It was found that the average roughness (Ra) in the most aged tube studied is about 50 pm. The correctness of MCNP4C in simulating diagnostic x-ray spectra was thoroughly verified by calling its Gaussian energy broadening card and comparing the simulated spectra with experimentally measured ones. The assessment of anode roughness involved the comparison of simulated spectra in deteriorated anodes with those simulated in perfectly plain anodes considered as reference. From these comparisons, the variations in output intensity, half value layer (HVL), heel effect, and patient dose were studied.

RESULTS

An intensity loss of 4.5% and 16.8% was predicted for anodes aged by 5 and 50 microm deep cracks (50 kVp, 6 degrees target angle, and 2.5 mm A1 total filtration). The variations in HVL were not significant as the spectra were not hardened by more than 2.5%; however, the trend for this variation was to increase with roughness. By deploying several point detector tallies along the anode-cathode direction and averaging exposure over them, it was found that for a 6 degrees anode, roughened by 50 microm deep cracks, the reduction in exposure is 14.9% and 13.1% for 70 and 120 kVp tube voltages, respectively. For the evaluation of patient dose, entrance skin radiation dose was calculated for typical chest x-ray examinations. It was shown that as anode roughness increases, patient entrance skin dose decreases averagely by a factor of 15%.

CONCLUSIONS

It was concluded that the anode surface roughness can have a non-negligible effect on output spectra in aged x-ray imaging tubes and its impact should be carefully considered in diagnostic x-ray imaging modalities.

Three-phase 18F-fluorocholine PET/CT in the evaluation of prostate cancer recurrence

AIM

Contribution of 3-phase 18F-fluorocholine PET/CT in suspected prostate cancer recurrence at early rise of PSA.

PATIENTS, METHODS

Retrospective analysis was performed in 47 patients after initial treatment with radiotherapy (n=30) or surgery (n=17). Following CT, 10 minutes list-mode PET acquisition was done over the prostate bed after injection of 300 MBq of 18F-fluorocholine. Three timeframes of 3 minutes each were reconstructed for analysis. All patients underwent subsequent whole body PET/CT. Delayed pelvic PET/CT was obtained in 36 patients. PET/CT was interpreted visually by two observers and SUVmax determined for suspicious lesions. Biopsies were obtained from 13 patients.

RESULTS

Biopsies confirmed the presence of cancer in 11 of 13 patients with positive PET for a total of 15 local recurrences in which average SUVmax increased during 14 minutes post injection and marginally decreased in delayed scanning. Conversely inguinal lymph nodes with mild to moderate metabolic activity on PET showed a clearly different pattern with decreasing SUVmax on dynamic images. Three-phase PET/CT contributed to the diagnostic assessment of 10 of 47 patients with biological evidence of recurrence of cancer. It notably allowed the discrimination of confounding blood pool or urinary activity from suspicious hyperactivities. PET/CT was positive in all patients with PSA>or=2 ng/ml (n=34) and in 4/13 patients presenting PSA values<2 ng/ml.

CONCLUSION

18F-fluorocholine 3-phase PET/CT showed a progressively increasing SUVmax in biopsy confirmed cancer lesions up to 14 minutes post injection while decreasing in inguinal lymph nodes interpreted as benign. Furthermore, it was very useful in differentiating local recurrences from confounding blood pool and urinary activity.