3D Tendon Strain Estimation Using High-frequency Volumetric Ultrasound Images: A Feasibility Study

Estimation of strain in tendons for tendinopathy assessment is a hot topic within the sports medicine community. It is believed that, if accurately estimated, existing treatment and rehabilitation protocols can be improved and presymptomatic abnormalities can be detected earlier. State-of-the-art studies present inaccurate and highly variable strain estimates, leaving this problem without solution. Out-of-plane motion, present when acquiring two-dimensional (2D) ultrasound (US) images, is a known problem and may be responsible for such errors. This work investigates the benefit of high-frequency, three-dimensional (3D) US imaging to reduce errors in tendon strain estimation. Volumetric US images were acquired in silico, in vitro, and ex vivo using an innovative acquisition approach that combines the acquisition of 2D high-frequency US images with a mechanical guided system. An affine image registration method was used to estimate global strain. 3D strain estimates were then compared with ground-truth values and with 2D strain estimates. The obtained results for in silico data showed a mean absolute error (MAE) of 0.07%, 0.05%, and 0.27% for 3D estimates along axial, lateral direction, and elevation direction and a respective MAE of 0.21% and 0.29% for 2D strain estimates. Although 3D could outperform 2D, this does not occur in in vitro and ex vivo settings, likely due to 3D acquisition artifacts. Comparison against the state-of-the-art methods showed competitive results. The proposed work shows that 3D strain estimates are more accurate than 2D estimates but acquisition of appropriate 3D US images remains a challenge.

Continuous ultrasound speckle tracking with Gaussian mixtures

Speckle tracking echocardiography (STE) is now widely used for measuring strain, deformations, and motion in cardiology. STE involves three successive steps: acquisition of individual frames, speckle detection, and image registration using speckles as landmarks. This work proposes to avoid explicit detection and registration by representing dynamic ultrasound images as sparse collections of moving Gaussian elements in the continuous joint space-time space. Individual speckles or local clusters of speckles are approximated by a single multivariate Gaussian kernel with associated linear trajectory over a short time span. A hierarchical tree-structured model is fitted to sampled input data such that predicted image estimates can be retrieved by regression after reconstruction, allowing a (bias-variance) trade-off between model complexity and image resolution. The inverse image reconstruction problem is solved with an online Bayesian statistical estimation algorithm. Experiments on clinical data could estimate subtle sub-pixel accurate motion that is difficult to capture with frame-to-frame elastic image registration techniques.

Quantification of bone quality using different cone beam computed tomography devices: Accuracy assessment for edentulous human mandibles

PURPOSE

To determine the accuracy of the latest cone beam computed tomography (CBCT) machines in comparison to multi-slice computer tomography (MSCT) and micro computed tomography (micro-CT) for objectively assessing trabecular and cortical bone quality prior to implant placement.

MATERIALS AND METHODS

Eight edentulous human mandibular bone samples were scanned with seven CBCT scanners (3D Accuitomo 170, i-CAT Next Generation, ProMax 3D Max, Scanora 3D, Cranex 3D, Newtom GiANO and Carestream 9300) and one MSCT system (Somatom Definition Flash) using the clinical exposure protocol with the highest resolution. Micro-CT (SkyScan 1174) images served as a gold standard. A volume of interest (VOI) comprising trabecular and cortical bone only was delineated on the micro-CT. After spatial alignment of all scan types, micro-CT VOIs were overlaid on the CBCT and MSCT images. Segmentation was applied and morphometric parameters were calculated for each scanner. CBCT and MSCT morphometric parameters were compared with micro-CT using mixed-effect models. Intraclass correlation analysis was used to grade the accuracy of each scanner in assessing trabecular and cortical quality in comparison with the gold standard. Bone structure patterns of each scanner were compared with micro-CT in 2D and 3D to facilitate the interpretation of the morphometric analysis.

RESULTS

Morphometric analysis showed an overestimation of the cortical and trabecular bone quantity during CBCT and MSCT evaluation compared to the gold standard micro-CT. The trabecular thickness (Tb.Th) was found to be significantly (P < 0.05) different and the smallest overestimation was found for the ProMax 3D Max (180 µm), followed by the 3D Accuitomo 170 (200 µm), Carestream 9300 (220 µm), Newtom GiANO (240 µm), Cranex 3D (280 µm), Scanora 3D (300 µm), high resolution MSCT (310 µm), i-CAT Next Generation (430 µm) and standard resolution MSCT (510 µm). The underestimation of the cortical thickness (Ct.Th) in ProMax 3D Max (-10 µm), the overestimation in Newtom GiANO (10 µm) and the high resolution MSCT (10 µm) were neglible. However, a significant overestimation (P < 0.05) was found for 3D Accuitomo 170 (110 µm), Scanora 3D (140 µm), standard resolution MSCT (150 µm), Carestream 9300 (190 µm), Cranex 3D (190 µm) and i-CAT Next Generation (230 µm). Comparison of the 2D network and 3D surface distance confirmed the overestimation in bone quantity, but only demonstrated a deviant trabecular network for the i-CAT Next Generation and the standard resolution MSCT. Intraclass correlation coefficients (ICCs) showed a significant (P < 0.05) high intra-observer reliability (ICC > 0.70) in morphometric evaluation between micro-CT and commercially available CBCT scanners (3D Accuitomo 170, Newtom GiANO and ProMax 3D Max). The ICC for Tb.Th and Ct.Th were 0.72 and 0.98 (3D Accuitomo 170), 0.71 and 0.96 (Newtom GiANO), and 0.87 and 0.92 (ProMax 3D Max), respectively.

CONCLUSIONS

High resolution CBCT offers a clinical alternative to MSCT to objectively determine the bone quality prior to implant placement. However, not all tested CBCT machines have sufficient resolution to accurately depict the trabecular network or cortical bone. Conflict-of-interest statement: There is no conflict of interest to declare.

FUNDING

Fellowship support came from Research Foundation Flanders (FWO) from the Belgian government, and Coordination for the Improvement of Higher Education Personnel (CAPES) program and Science without borders from the Brazilian government.

Computer quantification of airway collapse on forced expiration to predict the presence of emphysema

Background

Spirometric parameters are the mainstay for diagnosis of COPD, but cannot distinguish airway obstruction from emphysema. We aimed to develop a computer model that quantifies airway collapse on forced expiratory flow–volume loops. We then explored and validated the relationship of airway collapse with computed tomography (CT) diagnosed emphysema in two large independent cohorts.

Methods

A computer model was developed in 513 Caucasian individuals with ≥15 pack-years who performed spirometry, diffusion capacity and CT scans to quantify emphysema presence. The model computed the two best fitting regression lines on the expiratory phase of the flow-volume loop and calculated the angle between them. The collapse was expressed as an Angle of collapse (AC) which was then correlated with the presence of emphysema. Findings were validated in an independent group of 340 individuals.

Results

AC in emphysema subjects (N = 251) was significantly lower (131° ± 14°) compared to AC in subjects without emphysema (N = 223), (152° ± 10°) (p < 0.0001). Multivariate regression analysis revealed AC as best indicator of visually scored emphysema (R² = 0.505, p < 0.0001) with little significant contribution of K_CO, %predicted and FEV_1, %predicted to the total model (total R² = 0.626, p < 0.0001). Similar associations were obtained when using CT-automated density scores for emphysema assessment. Receiver operating characteristic (ROC) curves pointed to 131° as the best cut-off for emphysema (95.5% positive predictive value, 97% specificity and 51% sensitivity). Validation in a second group confirmed the significant difference in mean AC between emphysema and non-emphysema subjects. When applying the 131° cut-off, a positive predictive value of 95.6%, a specificity of 96% and a sensitivity of 59% were demonstrated.

Conclusions

Airway collapse on forced expiration quantified by a computer model correlates with emphysema. An AC below 131° can be considered as a specific cut-off for predicting the presence of emphysema in heavy smokers.

Redefining the target early during treatment. Can we visualize regional differences within the target volume using sequential diffusion weighted MRI?

PURPOSE

In head and neck cancer, diffusion weighted MRI (DWI) can predict response early during treatment. Treatment-induced changes and DWI-specific artifacts hinder an accurate registration between apparent diffusion coefficient (ADC) maps. The aim of the study was to develop a registration tool which calculates and visualizes regional changes in ADC.

METHODS

Twenty patients with stage IV HNC treated with primary radiotherapy received an MRI including DWI before and early during treatment. Markers were manually placed at anatomical landmarks on the different modalities at both time points. A registration method, consisting of a fully automatic rigid and nonrigid registration and two semi-automatic thin-plate spline (TPS) warps was developed and applied to the image sets. After each registration step the mean registration errors were calculated and ΔADC was compared between good and poor responders.

RESULTS

Adding the TPS warps significantly reduced the registration error (in mm, 6.3 ± 6.2 vs 3.2 ± 3.3 mm, p<0.001). After the marker based registration the median ΔADC in poor responders was significantly lower than in good responders (7% vs. 21%; p<0.001).

CONCLUSIONS

This registration method allowed for a significant reduction of the mean registration error. Furthermore the voxel-wise calculation of the ΔADC early during radiotherapy allowed for a visualization of the regional differences of ΔADC within the tumor.

Comprehensive management of a complex traumatic dental injury

A 24-year-old female patient presented with complaint of palatal swelling and a sinus tract facial to tooth #22. She reported an injury to the tooth 15 years earlier and no recollection of treatment, although there was evidence of an endodontic access into the crown. Radiographically the root appeared to have stopped developing, and it was associated with a large periapical lesion. After 3 unsuccessful attempts at apexification using calcium hydroxide (CH), further examination including use of cone-beam computed tomography (CBCT) was carried out. The latter allowed for better evaluating the situation and for better planning a more comprehensive treatment plan to include surgical removal of the apical lesion. The large radiolucent area extended from tooth #21 to #23. Using a dedicated software tool developed to be used in conjunction with CBCT, volumetric assessment of the lesion was carried out for healing follow up. The root end was filled from the apical direction with newly developed accelerated silicate cement 4-5 mm into the apical part of the canal. Subsequently, the rest of the canal was filled with the same type of cement. At the 1-year postsurgical follow up, the tooth remained asymptomatic, and using the CBCT volumetric program, bony healing could be demonstrated.

A novel method to estimate the volume of bone defects using cone-beam computed tomography: an in vitro study

INTRODUCTION

The routine use of high-resolution images derived from 3-dimensional cone-beam computed tomography (CBCT) datasets enables the linear measurement of lesions in the maxillary and mandibular bones on 3 planes of space. Measurements on different planes would make it possible to obtain real volumetric assessments. In this study, we tested, in vitro, the accuracy and reliability of new dedicated software developed for volumetric lesion assessment in clinical endodontics.

METHODS

Twenty-seven bone defects were created around the apices of 8 teeth in 1 young bovine mandible to simulate periapical lesions of different sizes and shapes. The volume of each defect was determined by taking an impression of the defect using a silicone material. The samples were scanned using an Accuitomo 170 CBCT (J. Morita Mfg Co, Kyoto, Japan), and the data were uploaded into a newly developed dedicated software tool. Two endodontists acted as independent and calibrated observers. They analyzed each bone defect for volume. The difference between the direct volumetric measurements and the measurements obtained with the CBCT images was statistically assessed using a lack-of-fit test. A correlation study was undertaken using the Pearson product-moment correlation coefficient. Intra- and interobserver agreement was also evaluated.

RESULTS

The results showed a good fit and strong correlation between both volume measurements (ρ > 0.9) with excellent inter- and intraobserver agreement.

CONCLUSIONS

Using this software, CBCT proved to be a reliable method in vitro for the estimation of endodontic lesion volumes in bovine jaws. Therefore, it may constitute a new, validated technique for the accurate evaluation and follow-up of apical periodontitis.

Subclinical cardiotoxicity detected by strain rate imaging up to 14 months after breast radiation therapy

PURPOSE

Strain rate imaging (SRI) is a new echocardiographic modality that enables accurate measurement of regional myocardial function. We investigated the role of SRI and troponin I (TnI) in the detection of subclinical radiation therapy (RT)-induced cardiotoxicity in breast cancer patients.

METHODS AND MATERIALS

This study prospectively included 75 women (51 left-sided and 24 right-sided) receiving adjuvant RT to the breast/chest wall and regional lymph nodes. Sequential echocardiographs with SRI were obtained before RT, immediately after RT, and 8 and 14 months after RT. TnI levels were measured on the first and last day of RT.

RESULTS

Mean heart and left ventricle (LV) doses were both 9 ± 4 Gy for the left-sided patients and 4 ± 4 Gy and 1 ± 0.4 Gy, respectively, for the right-sided patients. A decrease in strain was observed at all post-RT time points for left-sided patients (-17.5% ± 1.9% immediately after RT, -16.6% ± 1.4% at 8 months, and -17.7% ± 1.9% at 14 months vs -19.4% ± 2.4% before RT, P<.01) but not for right-sided patients. When we considered left-sided patients only, the highest mean dose was given to the anterior left ventricular (LV) wall (25 ± 14 Gy) and the lowest to the inferior LV wall (3 ± 3 Gy). Strain of the anterior wall was reduced after RT (-16.6% ± 2.3% immediately after RT, -16% ± 2.6% at 8 months, and -16.8% ± 3% at 14 months vs -19% ± 3.5% before RT, P<.05), whereas strain of the inferior wall showed no significant change. No changes were observed with conventional echocardiography. Furthermore, mean TnI levels for the left-sided patients were significantly elevated after RT compared with before RT, whereas TnI levels of the right-sided patients remained unaffected.

CONCLUSIONS

In contrast to conventional echocardiography, SRI detected a regional, subclinical decline in cardiac function up to 14 months after breast RT. It remains to be determined whether these changes are related to clinical outcome. In the meantime, we encourage the use of radiation techniques that minimize the exposure of the anterior LV wall in left-sided patients.

Intrafractional prostate motion during online image guided intensity-modulated radiotherapy for prostate cancer

INTRODUCTION

Intrafractional motion consists of two components: (1) the movement between the on-line repositioning procedure and the treatment start and (2) the movement during the treatment delivery. The goal of this study is to estimate this intrafractional movement of the prostate during prostate cancer radiotherapy.

MATERIAL AND METHODS

Twenty-seven patients with prostate cancer and implanted fiducials underwent a marker match procedure before a five-field IMRT treatment. For all fields, in-treatment images were obtained and then processed to enable automatic marker detection. Combining the subsequent projection images, five positions of each marker were determined using the shortest path approach. The residual set-up error (RSE) after kV-MV based prostate localization, the prostate position as a function of time during a radiotherapy session and the required margins to account for intrafractional motion were determined.

RESULTS

The mean RSE and standard deviation in the antero-posterior, cranio-caudal and left-right direction were 2.3±1.5 mm, 0.2±1.1 mm and -0.1±1.1 mm, respectively. Almost all motions occurred in the posterior direction before the first treatment beam as the percentage of excursions>5 mm was reduced significantly when the RSE was not accounted for. The required margins for intrafractional motion increased with prolongation of the treatment. Application of a repositioning protocol after every beam could decrease the 1cm margin from CTV to PTV by 2 mm.

CONCLUSIONS

The RSE is the main contributor to intrafractional motion. This RSE after on-line prostate localization and patient repositioning in the posterior direction emphasizes the need to speed up the marker match procedure. Also, a prostate IMRT treatment should be administered as fast as possible, to ensure that the pre-treatment repositioning efforts are not erased by intrafractional prostate motion. This warrants an optimized workflow with the use of faster treatment techniques.

Development and external validation of a predictive model for pathological complete response of rectal cancer patients including sequential PET-CT imaging

PURPOSE

To develop and validate an accurate predictive model and a nomogram for pathologic complete response (pCR) after chemoradiotherapy (CRT) for rectal cancer based on clinical and sequential PET-CT data. Accurate prediction could enable more individualised surgical approaches, including less extensive resection or even a wait-and-see policy.

METHODS AND MATERIALS

Population based databases from 953 patients were collected from four different institutes and divided into three groups: clinical factors (training: 677 patients, validation: 85 patients), pre-CRT PET-CT (training: 114 patients, validation: 37 patients) and post-CRT PET-CT (training: 107 patients, validation: 55 patients). A pCR was defined as ypT0N0 reported by pathology after surgery. The data were analysed using a linear multivariate classification model (support vector machine), and the model's performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

RESULTS

The occurrence rate of pCR in the datasets was between 15% and 31%. The model based on clinical variables (AUC(train)=0.61±0.03, AUC(validation)=0.69±0.08) resulted in the following predictors: cT- and cN-stage and tumour length. Addition of pre-CRT PET data did not result in a significantly higher performance (AUC(train)=0.68±0.08, AUC(validation)=0.68±0.10) and revealed maximal radioactive isotope uptake (SUV(max)) and tumour location as extra predictors. The best model achieved was based on the addition of post-CRT PET-data (AUC(train)=0.83±0.05, AUC(validation)=0.86±0.05) and included the following predictors: tumour length, post-CRT SUV(max) and relative change of SUV(max). This model performed significantly better than the clinical model (p(train)<0.001, p(validation)=0.056).

CONCLUSIONS

The model and the nomogram developed based on clinical and sequential PET-CT data can accurately predict pCR, and can be used as a decision support tool for surgery after prospective validation.

Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

PURPOSE

A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion.

METHODS

Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth.

RESULTS

The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4 +/- 1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images takes a little less than a second where most time is spent on the image preprocessing.

CONCLUSIONS

The authors have developed a method to automatically detect multiple markers in a pair of projection images that is robust, accurate, and sufficiently fast for clinical use. It can be used for kV, MV, or mixed image pairs and can cope with limited motion between the projection images.

Nonrigid image registration using conditional mutual information

Maximization of mutual information (MMI) is a popular similarity measure for medical image registration. Although its accuracy and robustness has been demonstrated for rigid body image registration, extending MMI to nonrigid image registration is not trivial and an active field of research. We propose conditional mutual information (cMI) as a new similarity measure for nonrigid image registration. cMI starts from a 3-D joint histogram incorporating, besides the intensity dimensions, also a spatial dimension expressing the location of the joint intensity pair. cMI is calculated as the expected value of the cMI between the image intensities given the spatial distribution. The cMI measure was incorporated in a tensor-product B-spline nonrigid registration method, using either a Parzen window or generalized partial volume kernel for histogram construction. cMI was compared to the classical global mutual information (gMI) approach in theoretical, phantom, and clinical settings. We show that cMI significantly outperforms gMI for all applications.

Comparison and evaluation of methods for liver segmentation from CT datasets

This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.

Biological image-guided radiotherapy in rectal cancer: is there a role for FMISO or FLT, next to FDG?

PURPOSE

The purpose of this study is to investigate the use of PET/CT with fluorodeoxyglucose (FDG), fluorothymidine (FLT) and fluoromisonidazole (FMISO) for radiotherapy (RT) target definition and evolution in rectal cancer.

MATERIALS AND METHODS

PET/CT was performed before and during preoperative chemoradiotherapy (CRT) in 15 patients with resectable rectal cancer. PET signals were delineated and CT images on the different time points were non-rigidly registered. Mismatch analyses were carried out to quantify the overlap between FDG and FLT or FMISO tumour volumes (TV) and between PET TVs over time.

RESULTS

Ninety sequential PET/CT images were analyzed. The mean FDG, FLT and FMISO-PET TVs showed a tendency to shrink during preoperative CRT. On each time point, the mean FDG-PET TV was significantly larger than the FMISO-PET TV but not significantly larger than the mean FLT-PET TV. There was a mean 65% mismatch between the FMISO and FDG TVs obtained before and during CRT. FLT TVs corresponded better with the FDG TVs (25% mismatch before and 56% during CRT). During CRT, on average 61% of the mean FDG TV (7 cc) overlapped with the baseline mean TV (15.5 cc) (n=15). For FLT, the TV overlap was 49% (n=5) and for FMISO only 20% of the TV during CRT remained inside the contour at baseline (n=10).

CONCLUSION

FDG, FLT and FMISO-PET reflect different functional characteristics that change during CRT in rectal cancer. FLT and FDG show good spatial correspondence, while FMISO seems less reliable due to the non-specific FMISO uptake in normoxic tissue and tracer diffusion through the bowel wall. FDG and FLT-PET/CT imaging seem most appropriate to integrate in preoperative RT for rectal cancer.

Nonrigid image registration using conditional mutual information

We propose conditional mutual information (cMI) as a new similarity measure for nonrigid image registration. We start from a 3D joint histogram incorporating, besides the reference and floating intensity dimensions, also a spatial dimension expressing the location of the joint intensity pair in the reference image. cMI is calculated as the expectation value of the conditional mutual information between the reference and floating intensities given the spatial distribution. Validation experiments were performed comparing cMI and global MI on artificial CT/MR registrations and registrations complicated with a strong bias field; both a Parzen window and generalised partial volume kernel were used for histogram construction. In both experiments, cMI significantly outperforms global MI. Moreover, cMI is compared to global MI for the registration of three patient CT/MR datasets, using overlap and centroid distance as validation measure. The best results are obtained using cMI.