Browsing by Subject "Breast"

Computerized breast phantoms have been popular for low-cost alternatives to collecting clinical data by combing them with highly realistic simulation tools. Image segmentation of three-dimensional breast computed tomography (bCT) data is one method to create such phantoms, but requires multiple image processing steps to accurately classify the tissues within the breast. One key step in our segmentation routine is the use of a bilateral filter to smooth homogeneous regions, preserve edges and thin structures, and reduce the sensitivity of the voxel classification to noise corruption. In previous work, the well-known process of bilateral filtering was completed on the entire bCT volume with the primary goal of reducing the noise in the entire volume. In order to improve on this method, knowledge of the varying bCT noise in each slice was used to adaptively increase or decrease the filtering effect as a function of distance to the chest wall. Not only does this adaptive bilateral filter yield thinner structures in the segmentation result but is adaptive on a case-by-case basis, allowing for easy implementation with future virtual phantom generations.

The overall goal of this dissertation is to optimize and evaluate the performance of the single photon emission computed tomography (SPECT) subsystem of a dedicated three-dimensional (3D) dual-modality breast imaging system for enhanced semi-automated, quantitative clinical imaging. This novel hybrid imaging system combines functional or molecular information obtained with a SPECT subsystem with high-resolution anatomical imaging obtained with a low dose x-ray Computed Tomography (CT) subsystem. In this new breast imaging paradigm, coined "mammotomography," the subject is imaged lying prone while the individual subsystems sweep 3-dimensionally about her uncompressed, pendant breast, providing patient comfort compared to traditional compression-based imaging modalities along with high fidelity and information rich images for the clinician.

System evaluation includes a direct comparison between dedicated 3D SPECT and dedicated 2D scintimammography imaging using the same high performance, semi-conductor gamma camera. Due to the greater positioning flexibility of the SPECT system gantry, under a wide range of measurement conditions, statistically significantly (p<0.05) more lesions and smaller lesion sizes were detected with dedicated breast SPECT than with compressed breast scintimammography. The importance of good energy resolution for uncompressed SPECT breast imaging was also investigated. Results clearly illustrate both visual and quantitative differences between the various energy windows, with energy windows slightly wider than the system resolution having the best image contrast and quality.

An observer-based contrast-detail study was performed in an effort to evaluate the limits of object detectability under various imaging conditions. The smallest object detail was observed using a 45-degree tilted trajectory acquisition. The complex 3D projected sine wave acquisition, however, had the most consistent combined intra and inter-observer results, making it potentially the best imaging approach for consistent clinical imaging.

Automatic ROR contouring is implemented using a dual-layer light curtain design, ensuring that an arbitrarily shaped breast is within ~1 cm of the camera face, but no closer than 0.5 cm at every projection angle of a scan. Autocontouring enables simplified routine scanning using complex 3D trajectories, and yields improved image quality. Absolute quantification capabilities are also integrated into the SPECT system, allowing the calculation of in vivo total lesion activity. Initial feasibility studies in controlled low noise experiments show promising results with total activity agreement within 10% of the dose calibrator values.

The SPECT system is integrated with a CT scanner for added diagnostic power. Initial human subject studies demonstrate the clinical potential of the hybrid SPECT-CT breast imaging system. The reconstructed SPECT-CT images illustrate the power of fusing functional SPECT information to localize lesions not easily seen in the anatomical CT images. Enhanced quantitative 3D SPECT-CT breast imaging, now with the ability to dynamically contour any sized breast, has high potential to improve detection, diagnosis, and characterization of breast cancer in upcoming larger-scale clinical testing.

Background

Patients and methods

Results

Conclusion

The work presented in this dissertation focuses on evaluation of absolute quantification accuracy in dedicated breast SPECT-CT. The overall goal was to investigate through simulations and measurements the impact and utilization of various correction methods for scattered and attenuated photons, characterization of incomplete charge collection in Cadmium Zinc Telluride detectors as a surrogate means of improving scatter correction, and resolution recovery methods for modeling collimator blur during image reconstruction. The quantification accuracy of attenuation coefficients in CT reconstructions was evaluated in geometric phantoms, and a slice-by-slice breast segmentation algorithm was developed to separate adipose and glandular tissue. All correction and segmentation methods were then applied to a pilot study imaging parathyroid patients to determine the average uptake of Tc-99m Sestamibi in healthy breast tissue, including tissue specific uptake in adipose and glandular tissue.

Monte Carlo methods were utilized to examine the changes in incident scatter energy distribution on the SPECT detector as a function of 3D detector position about a pendant breast geometry. A simulated prone breast geometry with torso, heart, and liver was designed. An ideal detector was positioned at various azimuthal and tilted positions to mimic the capabilities of the breast SPECT subsystem. The limited near-photopeak scatter energy range in simulated spectra was linearly fit and the slope used to characterize changes in scatter distribution as a function of detector position. Results show that the detected scatter distribution changes with detector tilt, with increasing incidence of high energy scattered photons at larger detector tilts. However, reconstructions of various simulated trajectories show minimal impact on quantification (<5%) compared to a primary-only reconstruction.

Two scatter compensation methods were investigated and compared to a narrow photopeak-only windowing for quantification accuracy in large uniform regions and small, regional uptake areas: 1) a narrow ±4% photopeak energy window to minimize scatter in the photopeak window, 2) the previously calibrated dual-energy window scatter correction method, and 3) a modified dual-energy window correction method that attempts to account for the effects of incomplete charge collection in Cadmium Zinc Telluride detectors. Various cylindrical phantoms, including those with imbedded hot and cold regions, were evaluated. Results show that the Photopeak-only and DEW methods yield reasonable quantification accuracy (within 10%) for a wide range of activity concentrations and phantom configurations. The mDEW demonstrated highly accurate quantification measurements in large, uniform regions with improved uniformity compared to the DEW method. However, the mDEW method is susceptible to the calibration parameters and the activity concentration of the scanned phantom. The sensitivity of the mDEW to these factors makes it a poor choice for robust quantification applications. Thus, the DEW method using a high-performance CZT gamma camera is still a better choice for quantification purposes

Phantoms studies were performed to investigate the application of SPECT vs CT attenuation correction. Minor differences were observed between SPECT and CT maps when assuming a uniformly filled phantom with the attenuation coefficient of water, except when the SPECT attenuation map volume was significantly larger than the CT volume. Material specific attenuation coefficients reduce the corresponding measured activity concentrations compared to a water-only correction, but the results do not appear more accurate than a water-only attenuation map. Investigations on the impact of image registration show that accurate registration is necessary for absolute quantification, with errors up to 14% observed for 1.5cm shifts.

A method of modeling collimator resolution within the SPECT reconstruction algorithm was investigated for its impact on contrast and quantification accuracy. Three levels of resolution modeling, each with increasing ray-sampling, were investigated. The resolution model was applied to both cylindrical and anthropomorphic breast phantoms with hot and cold regions. Large volume quantification results (background measurements) are unaffected by the application of resolution modeling. For smaller chambers and simulated lesions, contrast generally increases with resolution modeling. Edges of lesions also appear sharper with resolution modeling. No significant differences were seen between the various levels of resolution modeling. However, Gibbs artifacts are amplified at the boundaries of high contrast regions, which can significantly affect absolute quantification measurements. Convergence with resolution modeling is also notably slower, requiring more iterations with OSEM to reach a stable mean activity concentration. Additionally, reconstructions require far more computing time with resolution modeling due to the increase in number of sampling rays. Thus while the edge enhancement and contrast improvements may benefit lesion detection, the artifacts, slower convergence, and increased reconstruction time limit the utility of resolution modeling for both absolute quantification and clinical imaging studies.

Finally, a clinical pilot study was initiated to measure the average uptake of Tc-99m Sestamibi in healthy breast tissue. Subjects were consented from those undergoing diagnostic parathyroid studies at Duke. Each subject was injected with 25mCi of Sestamibi as part of their pre-surgical parathyroid SPECT imaging studies and scanned with the dedicated breast SPECT-CT system before their diagnostic parathyroid SPECT scan. Based on phantom studies of CT reconstructed attenuation coefficient accuracy, a slice-by-slice segmentation algorithm was developed to separate breast CT data into adipose and glandular tissue. SPECT data were scatter, attenuation, and decay corrected to the time of injection. Segmented CT images were used to measure average radiotracer concentration in the whole breast, as well as adipose and glandular tissue. With 8 subjects scanned, the average measured whole breast activity concentration was found to be 0.10µCi/mL. No significant differences were seen between adipose and glandular tissue uptake.

In conclusion, the application of various characterization and correct methods for quantitative SPECT imaging were investigated. Changes in detected scatter distribution appear to have minimal impact on quantification, and characterization of low-energy tailing for a modified scatter subtraction method yields inferior overall quantification results. Comparable quantification accuracy is seen with SPECT and CT-based attenuation maps, assuming the SPECT-based volume is fairly accurate. In general, resolution recovery within OSEM yields higher contrast, but quantification accuracy appears more susceptible to measurement location. Finally, scatter, attenuation, and resolution recovery methods, along with a breast segmentation algorithm, were implemented in a clinical imaging study for quantifying Tc-99m Sestamibi uptake. While the average whole breast uptake was measured to be 0. 10µCi/mL, no significant differences were seen between adipose and glandular tissue or when implementing resolution recovery. Thus, for future clinical imaging, it's recommended that the application of the investigated correction methods should be limited to the traditional DEW method and CT-based attenuation maps for quantification studies.

The majority of breast tumors express the estrogen receptor (ER), and more than half of these cancers also express the progesterone receptor (PR). While the actions of ER on breast cancer pathogenesis are well understood, those of PR are still unclear. The Women's Health Initiative trial in 2002 brought into focus the alarming result that women receiving both estrogen and progestins as hormone replacement therapy are at greater risk for breast cancer than women receiving estrogen alone. Thus, there is considerable interest in defining the mechanisms that underlie the pharmacological actions of progestins in the normal and malignant breast.

Progestins facilitate cell cycle progression through multiple mechanisms, one of which is the induction of phosphorylation of the tumor suppressor retinoblastoma (Rb) protein. Stimulation by growth factors induces the transcription of Cyclin D1 which in turn activates the cyclin dependent kinases (CDKs). The Cyclin D1- Cdk4/6 complex phosphorylates the Rb protein, leading to the release of E2F1, which then binds and activates other target genes, leading to G1-S transition of the cell cycle. Given the reported action of PR to activate MAPK signaling, we initially thought that the progestin-induced Rb phosphorylation was mediated by this pathway. However, we turned to an alternate hypothesis based on our data using MEK inhibitors demonstrating that this was not the case.

Given the primacy of Cyclin D1 in cell cycle control, we then turned our attention to defining the mechanism by which Cyclin D1 expression is regulated by PR. Interestingly, it was determined that progestin mediated up- regulation of Cyclin D1 is rapid, peaking at 6hrs post hormone addition followed by a decrease in expression reaching a nadir at 18hrs. Unexpectedly, we found that contrary to what has been published before, the induction of Cyclin D1 mRNA expression was a primary transcriptional event and we have demonstrated the specific interaction of PR with PREs (progesterone response elements) located on this gene. We have further determined that the half-life of Cyclin D1 mRNA is decreased significantly by progestin addition explaining how the levels of this mRNA following the addition of hormone are quickly attenuated. Thus, when taken together, our data suggest that progestins exert both positive and negative effects on Cyclin D1 mRNA, the uncoupling of which is likely to impact the pathogenesis of breast cancer

The observation that PR reduces the Cyclin D1 mRNA stability led us to investigate the effects of PR on RNA binding proteins, especially those which are involved in RNA stability. We discovered that PR induces the expression of several RNA binding proteins. Although the work to determine the effects of these RNA binding proteins on CyclinD1 mRNA stability is still ongoing, we have discovered a role for one of the PR-induced RNA binding proteins tristetraprolin (TTP), in the suppression of the inflammation pathway in breast cancer. We found that while TTP was not required for the PR-mediated decrease in Cyclin D1 mRNA stability, overexpression of this tumor suppressive protein was able to inhibit IL-1β-mediated stimulation of inflammatory genes in our breast cancer model. Since it is established that the upregulation of the inflammatory pathway is oncogenic, we are currently exploring the intersection of PR and TTP-mediated signaling on the inflammation transcriptome in breast cancer.

Thus, collectively these data provide us with a better picture of the poorly understood actions of PR on breast cancer proliferation and tumorigenesis. We believe that further investigation of the studies developed in this thesis will lead to novel and better-targeted approaches to the use of PR as a therapeutic target in the clinic.

Proposed is a method for investigating optimal acquisition parameters in NSECT, neutron stimulated emission computed tomography, for good image quality and low dose for diagnosing liver and breast cancers. These parameters include the number of angles, number of translations per angle, beam width, and beam width spacing. These parameters will affect dose, which will increase with increasing total neutron flux. Therefore, a balance must be achieved for the parameters mentioned above, to yield a desired dose limit and tolerable spatial resolution necessary for liver and breast cancer diagnosis.

Using Monte Carlo simulation toolkit GEANT4, the effects of beam spread due to neutron elastic scatter was explored. Then, a geometrical water torso phantom with slanted edge solid iron phantom was run for different acquisition parameters, and an MTF was taken to determine resolution for each set. For dose considerations, two anthropomorphic voxelized phantoms, one with liver cancer lesions, and one with breast cancer lesions, were scanned with the same parameter sets, and organ doses and DVHs, dose volume histograms, was computed for each set. In addition, images of the phantom in the lesion plane were reconstructed for those parameter sets showing best resolution and lowest dose.

It is found that beam spread due to elastic scatter off of Hydrogen atoms is negligible for all beam widths. For optimal resolution in the primary breast phantom, it was found that acquisition parameters of a 5 mm beam, with no gaps, with any of the five angles provided the superior resolution. For the optimal resolution in the liver, it was found that down sampling angles and introducing gaps between projections greatly affected image accuracy and resolution. Also, the 5 mm beam width provided better geometrical accuracy, but the 1 cm bream width provided slightly better resolution.

Organ doses are computed for the primary organ and organs at risk for each parameter set at 500 K neutrons per projection. For a scan of the full volume of the liver, liver organ doses ranged from 25.83 to 0.19 mSv. For the same scan, the organ doses for the heart ranged from 0.18 to 0.05 mSv. For a scan with the same pool of acquisition parameters of the full volume of the breast, breast organ doses ranged from 49.87 to 0.38 mSv. Furthermore, the DVHs for both scans showed a very steep drop-off at low dose bins for secondary organs at risk and a reasonable drop-off for the primary organ.

In choosing the optimal acquisition parameters using both resolution and dose, a metric equal to resolution times dose is used, in which low values are optimal. An upper threshold for the metric was chosen based on dose values in currently used medical imaging modalities. A pool of optimal parameter sets was then identified using the metric. To further identify the optimum, a metric estimating geometrical accuracy of the reconstructed square was used. For the breast scan, the optimal parameter set was a 1 cm beam width, with 0 mm a gap, with 12 angles. For the liver scan, the optimal parameter set was a 1 cm beam width, with a 0 mm gap, with 36 angles.

Finally, reconstructed images of the anthropomorphic scans using the super sampled geometry in the liver scan showed one lesion, using images of iron and phosphorous. With more degraded image quality, reconstructed images of the breasts using the super sampled geometry showed only the three cm lesion accurately. The images reconstructed from the optimal set identified for liver scans also showed the larger lesion, except with some noise from the presence of iron and phosphorous in other organs. The images reconstructed from the optimal set identified for the breast scans had a similar result to that of the super-sampled case, albeit with lower contrast. The least sampled case for both scans were found to be diagnostically useless. From these anthropomorphic images, this work demonstrates that in-vivo imaging of breast and liver cancers may be potentially possible with NSECT at a low dose.

Scatter in medical imaging is typically cast off as image-related noise that detracts from meaningful diagnosis. It is therefore typically rejected or removed from medical images. However, it has been found that every material, including cancerous tissue, has a unique X-ray coherent scatter signature that can be used to identify the material or tissue. Such scatter-based tissue-identification provides the advantage of locating and identifying particular materials over conventional anatomical imaging through X-ray radiography. A coded aperture X-ray coherent scatter spectral imaging system has been developed in our group to classify different tissue types based on their unique scatter signatures. Previous experiments using our prototype have demonstrated that the depth-resolved coherent scatter spectral imaging system (CACSSI) can discriminate healthy and cancerous tissue present in the path of a non-destructive x-ray beam. A key to the successful optimization of CACSSI as a clinical imaging method is to obtain anatomically accurate phantoms of the human body. This thesis describes the development and fabrication of 3D printed anatomical scatter phantoms of the breast and lung.

The purpose of this work is to accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Tissue-equivalent anatomical phantoms were designed to assess the capability of the CACSSI system to classify different types of breast tissue (adipose, fibroglandular, malignant). These phantoms were 3D printed based on DICOM data obtained from CT scans of prone breasts. The phantoms were tested through comparison of measured scatter signatures with those of adipose and fibroglandular tissue from literature. Tumors in the phantom were modeled using a variety of biological tissue including actual surgically excised benign and malignant tissue specimens. Lung based phantoms have also been printed for future testing. Our imaging system has been able to define the location and composition of the various materials in the phantom. These phantoms were used to characterize the CACSSI system in terms of beam width and imaging technique. The result of this work showed accurate modeling and characterization of the phantoms through comparison of the tissue-equivalent form factors to those from literature. The physical construction of the phantoms, based on actual patient anatomy, was validated using mammography and computed tomography to visually compare the clinical images to those of actual patient anatomy.