A novel full-inversion-based technique for quantitative ultrasound elastography was investigated in a pilot clinical study on five patients for non-invasive detection and localization of prostate ...cancer and quantification of its extent. Conventional-frequency ultrasound images and radiofrequency (RF) data (~5 MHz) were collected during mechanical stimulation of the prostate using a transrectal ultrasound probe. Pre and post-compression RF data were used to construct the strain images. The Young's modulus (YM) images were subsequently reconstructed using the derived strain images and the stress distribution estimated iteratively using finite element (FE) analysis. Tumor regions determined based on the reconstructed YM images were compared to whole-mount histopathology images of radical prostatectomy specimens. Results indicated that tumors were significantly stiffer than the surrounding tissue, demonstrating a relative YM of 2.5±0.8 compared to normal prostate tissue. The YM images had a good agreement with the histopathology images in terms of tumor location within the prostate. On average, 76%±28% of tumor regions detected based on the proposed method were inside respective tumor areas identified in the histopathology images. Results of a linear regression analysis demonstrated a good correlation between the disease extents estimated using the reconstructed YM images and those determined from whole-mount histopathology images (r
=0.71). This pilot study demonstrates that the proposed method has a good potential for detection, localization and quantification of prostate cancer. The method can potentially be used for prostate needle biopsy guidance with the aim of decreasing the number of needle biopsies. The proposed technique utilizes conventional ultrasound imaging system only while no additional hardware attachment is required for mechanical stimulation or data acquisition. Therefore, the technique may be regarded as a non-invasive, low cost and potentially widely-available clinical tool for prostate cancer diagnosis.
Background
RECQL (also known as RECQ1 and RECQL1) is a gene of recent interest in breast cancer and an association between high levels of RECQL protein in breast cancer tumour cells and good survival ...of patients has been reported.
Methods
To validate this association, we measured the RECQL protein levels in tumours of 933 breast cancer patients using immunohistochemistry analysis and followed the patients for death from breast cancer.
Results
Women with a level of RECQL protein above the 75th percentile had better 15-year disease-specific survival among ER-positive patients (62.5% vs. 48.7%, HR= 0.72, 95%CI= 0.52-0.98, p-value = 0.04), but not among ER- patients (48.9% vs. 48.0%, HR= 1.07, 95%CI= 0.67-1.69, p-value= 0.79). Among the ER-negative patients, high RECQL protein levels were associated with better survival among women who received tamoxifen treatment (67.0% vs. 51.5%, HR= 0.64, 95%CI= 0.41-0.99, p-value= 0.04).
Conclusion
RECQL might be a new predictive marker for tamoxifen treatment among ER-positive patients.
To compare magnetic resonance elastography (MRE) with ventricular pressure changes in an animal model.
Three pigs of different cardiac physiology (weight, 25 to 53 kg; heart rate, 61 to 93 bpm; left ...ventricular LV end-diastolic volume, 35 to 70 ml) were subjected to invasive LV pressure measurement by catheter and noninvasive cardiac MRE. Cardiac MRE was performed in a short-axis view of the heart and applying a 48.3-Hz shear-wave stimulus. Relative changes in LV-shear wave amplitudes during the cardiac cycle were analyzed. Correlation coefficients between wave amplitudes and LV pressure as well as between wave amplitudes and LV diameter were determined.
A relationship between MRE and LV pressure was observed in all three animals (R2 >or= 0.76). No correlation was observed between MRE and LV diameter (R2 <or= 0.15). Instead, shear wave amplitudes decreased 102 +/- 58 ms earlier than LV diameters at systole and amplitudes increased 175 +/- 40 ms before LV dilatation at diastole. Amplitude ratios between diastole and systole ranged from 2.0 to 2.8, corresponding to LV pressure differences of 60 to 73 mmHg.
Externally induced shear waves provide information reflecting intraventricular pressure changes which, if substantiated in further experiments, has potential to make cardiac MRE a unique noninvasive imaging modality for measuring pressure-volume function of the heart.
The finite element (FE) method can accurately calculate tissue deformation. However, its low speed renders it ineffective for many biomedical applications involving real-time data processing. To ...accelerate FE analysis, we introduce a novel tissue mechanics simulation technique. This technique is suitable for real-time estimation of tissue deformation of specific organs, which is required in computer-aided diagnostic or therapeutic procedures. In this method, principal component analysis is used to describe each organ shape and its corresponding FE field for a pool of patients by a small number of weight factors. A mapping function is developed to relate the parameters of organ shape to their FE field counterpart. We show that irrespective of the complexity of the tissue's constitutive law or its loading conditions, the proposed technique is highly accurate and fast in estimating the FE field. Average deformation errors of less than 2% demonstrate the accuracy of the proposed technique.
Purpose:
A novel technique is proposed to characterize lung tissue incompressibility variation during respiration. Estimating lung tissue incompressibility parameter variations resulting from air ...content variation throughout respiration is critical for computer assisted tumor motion tracking. Continuous tumor motion is a major challenge in lung cancer radiotherapy, especially with external beam radiotherapy. If not accounted for, this motion may lead to areas of radiation overdosage for normal tissue. Given the unavailability of imaging modality that can be used effectively for real-time lung tumor tracking, computer assisted approach based on tissue deformation estimation can be a good alternative. This approach involves lung biomechanical model where its fidelity depends on input tissue properties. This investigation shows that considering variable tissue incompressibility parameter is very important for predicting tumor motion accurately, hence improving the lung radiotherapy outcome.
Methods:
First, anin silico lung phantom study was conducted to demonstrate the importance of employing variable Poisson's ratio for tumor motion predication. After it was established that modeling this variability is critical for accurate tumor motion prediction, an optimization based technique was developed to estimate lung tissue Poisson's ratio as a function of respiration cycle time. In this technique, the Poisson's ratio and lung pressure value were varied systematically until optimal values were obtained, leading to maximum similarity between acquired and simulated 4D CT lung images. This technique was applied in an ex vivo porcine lung study where simulated images were constructed using the end exhale CT image and deformation fields obtained from the lung's FE modeling of each respiration time increment. To model the tissue, linear elastic and Marlow hyperelastic material models in conjunction with variable Poisson's ratio were used.
Results:
The phantom study showed that the tumor motion trajectory and its final locations obtained from simulations with and without considering tissue incompressibility variation were very different. For example, tumor displacements in the z direction were −11.23 and −38.10 mm obtained with the Marlow hyperelastic material model in conjunction with constant and variable Poisson's ratio, respectively. By comparing the acquired 4D-CT image sequence of the porcine lung with their image sequence counterparts obtained from the hyperelastic model with constant and variable Poisson's ratio, it was shown that using variable tissue incompressibility reduced errors significantly in tumor motion prediction.
Conclusions:
This investigation demonstrates the importance of incompressibility variation estimation and utilization for accurate tumor tracking in computer assisted lung external beam radiation therapy. An optimization framework was developed to estimate a Poisson's ratio function in terms of respiration cycle time using experimental image data of the lung. Utilizing this function along with respiratory system FE modeling may lead to more effective tumor targeting, hence potentially improving the outcome of lung external beam radiation therapy techniques. This is particularly true for stereotactic body radiation therapy where only one or a few fraction treatments are applied, precluding the possibility of averaging out dosimetric deviations introduced by the respiratory motion.
Soft tissue elasticity has been a subject of interest in biomedical applications as an aid to medical diagnosis since the dawn of medicine. More recently, this has led to the concept of elastography ...with the aim of imaging the spatial distribution of tissue elasticity. Interpreting elastography images requires reliable information pertaining to elastic properties of normal and pathological tissues. Such information is either very limited or not available in the literature. Elastic modulus measurement techniques developed for soft tissues generally require tissue excision to prepare samples for testing. While this may be done with normal tissues, tumour tissue excision is generally not permissible because tumour pathological assessment requires that the tumour be kept intact. To address this limitation, we developed a system to measure the Young's modulus of tumour specimens. The technique consists of indenting the tumour specimen while measuring indentation force and displacements. To obtain the Young's modulus from the measured force-displacement slope, we developed an iterative inversion technique that uses a finite element model of the piecewise homogeneous tissue slice in each iteration. Preliminary elasticity measurement results of various breast tumours are presented and discussed. These results indicate that the proposed method is robust and highly accurate. Furthermore, they indicate that a benign lesion and malignant tumours are roughly five times and ten times stiffer than normal breast tissues respectively.
A computational model is proposed to demonstrate the feasibility of characterizing the motion of lung tumors caused by respiratory diaphragm forces using a tissue biomechanics approach. Compensating ...for such motion is very important for developing effective systems of minimally invasive tumor ablative procedures, e.g., Low Dose Rate (LDR) lung brachytherapy. To minimize the effects of respiratory motion, the target lung is almost completely deflated before starting such procedures. However, a significant amount of motion persists in the target lung due to the diaphragm contact forces required for the other lung's respiration. In this study, a model pipeline was developed which inputs a pre-operative 4D-CT image sequence of the lung to output the predicted 3D motion trajectory of the tumor over the respiratory cycle. A finite element method was used in this pipeline to model the lung tissue deformation in order to predict the tumor motion. Experiments were conducted on an ex vivo porcine lung to demonstrate the performance and assess the accuracy of the proposed pipeline. The resultant tumor motion trajectory obtained from the biomechanical model of the lung was compared to the experimental trajectory obtained from CT imaging. Results were promising, suggesting that tissue mechanics-based modeling can be employed for effective characterization of lung tumor respiratory motion to improve accuracy in lung tumor ablative procedures.
Purpose:
A novel technique is proposed to construct CT image of a totally deflated lung from a free-breathing 4D-CT image sequence acquired preoperatively. Such a constructed CT image is very useful ...in performing tumor ablative procedures such as lung brachytherapy. Tumor ablative procedures are frequently performed while the lung is totally deflated. Deflating the lung during such procedures renders preoperative images ineffective for targeting the tumor. Furthermore, the problem cannot be solved using intraoperative ultrasound (U.S.) images because U.S. images are very sensitive to small residual amount of air remaining in the deflated lung. One possible solution to address these issues is to register high quality preoperative CT images of the deflated lung with their corresponding low quality intraoperative U.S. images. However, given that such preoperative images correspond to an inflated lung, such CT images need to be processed to construct CT images pertaining to the lung’s deflated state.
Methods:
To obtain the CT images of deflated lung, we present a novel image construction technique using extrapolated deformable registration to predict the deformation the lung undergoes during full deflation. The proposed construction technique involves estimating the lung’s air volume in each preoperative image automatically in order to track the respiration phase of each 4D-CT image throughout a respiratory cycle; i.e., the technique does not need any external marker to form a respiratory signal in the process of curve fitting and extrapolation. The extrapolated deformation field is then applied on a preoperative reference image in order to construct the totally deflated lung’s CT image. The technique was evaluated experimentally usingex vivo porcine lung.
Results:
Theex vivo lung experiments led to very encouraging results. In comparison with the CT image of the deflated lung we acquired for the purpose of validation, the constructed CT image was very similar. The intensity mean absolute difference between these two images was calculated to be at 1%. Tumor center as well as a number of anatomical fiducial markers were traced in different corresponding slices of the two images. The average misalignment obtained for the constructed CT image was (0.64, 0.39, 0.11) mm, which indicates a very desirable accuracy for lung brachytherapy applications.
Conclusions:
The image construction accuracy obtained in this research is suitable for intraoperative tasks; e.g., tumor localization and fusing with real time navigation data in lung brachytherapy. These applications involve image registration with intraoperative U.S. images in order to enhance their poor quality. The proposed technique is also useful for preoperative tasks such as planning of lung brachytherapy treatment.
Ultrasound elastography is a prominent noninvasive medical imaging technique that estimates tissue elastic properties to detect abnormalities in an organ. A common approximation to tissue elastic ...modulus is tissue strain induced after mechanical stimulation. To compute tissue strain, ultrasound radio frequency (RF) data can be processed using energy-based algorithms. These algorithms suffer from ill-posedness to tackle. A continuity constraint along with the data amplitude similarity is imposed to obtain a unique solution to the time-delay estimation (TDE) problem. Existing energy-based methods exploit the first-order spatial derivative of the displacement field to construct a regularizer. This first-order regularization scheme alone is not fully consistent with the mechanics of tissue deformation while perturbed with an external force. As a consequence, state-of-the-art techniques suffer from two crucial drawbacks. First, the strain map is not sufficiently smooth in uniform tissue regions. Second, the edges of the hard or soft inclusions are not well-defined in the image. Herein, we address these issues by formulating a novel regularizer taking both first- and second-order derivatives of the displacement field into account. The second-order constraint, which is the principal novelty of this work, contributes both to background continuity and edge sharpness by suppressing spurious noisy edges and enhancing strong boundaries. We name the proposed technique: Second-Order Ultrasound eLastography (SOUL). Comparative assessment of qualitative and quantitative results shows that SOUL substantially outperforms three recently developed TDE algorithms called Hybrid, GLUE, and MPWC-Net++. SOUL yields 27.72%, 62.56%, and 81.37% improvements of the signal-to-noise ratio (SNR) and 72.35%, 54.03%, and 65.17% improvements of the contrast-to-noise ratio (CNR) over GLUE with data pertaining to simulation, phantom, and in vivo tissue, respectively. The SOUL code can be downloaded from code.sonography.ai.
Medical imaging derived cardiac biomechanical models offer a wealth of new information to be used in diagnosis and prognosis of cardiovascular disease. A noteworthy feature of such models is the ...ability to predict myofiber contraction stresses during acute or chronic ischemic events. Current techniques for heterogeneous contraction models require tissue motion tracking capabilities which are neither available on all imaging modalities, nor currently used in the clinic. Proposed in this article is a proof of concept of a tissue tracking independent technique focused on shape optimization to predict the contraction stresses of in-silico left ventricle models simulating various acute myocardial infarction events. The technique involves three variables defined in the left ventricle muscle. Two of the variables represent the contraction stresses in the healthy and infarct regions while the third is a novel periinfarct variable defining a non-contracting myofiber state allowing finer classification of local myofiber damage. Results indicate that the contraction stress reconstruction errors are overall smaller than 12% when considering standard errors associated with population modelling for the new variable of interest.
•Tissue tracking independent technique is proposed to reconstruct contractility parameters of LV with acute MI.•Three variables of contraction stress in healthy/infarct regions, and a myofiber contraction state variable, are considered.•Reconstruction problem was formulated based on LV shape at relaxed and contracted states.•Shape optimization shape formulation was solved using genetic algorithms.•Results show successful parameter reconstruction of a LV in silico model.
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