Thesis
Improved Detection and Characterization of Obscured Central Gland Tumors of the Prostate:
requirementsRequirements for the degree of
2016
©2016 by
All rights reserved
Approved by
First Reader
Boris Nicolas Bloch, M.D.
Associate Professor of Radiology and
Director of Bioimaging Science
Second Reader
Kevin Thomas, Ph.D.
Assistant Professor of Bioimaging and Health Emergency
DEDICATION
I would like to dedicate this work to my patient spouse Landry, my wonderful children Charlie and Phoenix, and my dog Armani.
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ACKNOWLEDGMENTS
Sometimes, a thesis or thesis will have an acknowledgments page. Here's where you thank the people who helped you write this work. Your advisor and committee, archivists and librarians, your best friends, your spouse, your study buddy.
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ACKNOWLEDGMENTS
Improved Detection and Characterization of Obscured Central Gland Tumors of the Prostate:
Texture Analysis of non contrast and contrast enhanced MR Images for Differentiation of Benign Prostate Hyperplasia (BPH) Nodules and Cancer
ABSTRACT
The body of the abstract begins here and is typed double spaced. A Master’s thesis abstract is limited to 750 words.
ABSTRACT
TITLEi
READER APPROVAL PAGE..iii
Approved by IIIIII
DEDICATION IVIV
ACKNOWLEDGMENTS VV
ABSTRACT VIVI
LIST OF TABLES VIIVIII
LIST OF FIGURES IXIX
LIST OF ABBREVIATIONS XX
Chapter I: Introduction XIXI
Chapter II: Background XIIXIII
Chapter III: Methods and Materials XXXXI
3.1 MRI Protocols XXXXI
3.2 Patient Selection and Preparation XXXXI
Texture analysis XXIXXIII
Image preparation Katie Gallagher who she annotated the images XXIXXIII
3.3 MR Applications at the BIDMC XXIIXXIV
Chapter IV: Result XXXVXXVI
Chapter V: Discussion XXXVIIXXVI
Chapter VI: Conclusion XLXXVI
Bibliography XLXXVI
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LIST OF FIGURES
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LIST OF FIGURES
LIST OF ABBREVIATIONS
ACS American Cancer Society
BIDMC Beth Israel Deaconess Medical Center
BPH Benign Prostatic Hyperplasia
CT Computed Tomography
CZ Central Zone
DCE Dynamic Contrast Enhancement
DRE Digital Rectal Exam
ECE Extracapsular Extension
erCoil Endo-Rectal Coil
FDA Food and Drug Administration
PSA Prostate Specific Antigen
PCa Prostate Cancer
PZ Peripheral Zone
TRUS Trans-Rectal Ultrasound
TA Texture Analysis
US United States
USI Ultrasound Imaging
1.5T 1.5 Tesla
3T 3 Tesla
Chapter I: Introduction
In the United States, Prostate cancer (PCa) is the most common non-cutaneous malignancy after lung cancer in men in the US with an incident of 126 per 100,000 people. The American Cancer Society (ACS) stated reported that the number of new cases of men diagnosed with PCa by 2016 will be an approximately 180,890 cases. PCa is still considered as thea second leading cause of cancer death in men. Also, the ACS added that the estimation for death will occur from PCa is 26,120 deaths in 2016. Today, many studies stated that mortality rate is gradually decreasing compared with the past years, and this due to the developing of screening the prostate cancer using serum prostatic specific antigen (PSA) and transrectal ultrasound (TRUS) in which they allow the detection of the prostate cancer earlier and stage identification. PSA is approved by the U.S Food and Drug Administration (FDA) in 1986 to be used as a primary biomarker to diagnose PCa (Li, et al., 2013). It has some limitation in which it is not capable of differentiating between PCa and benign prostatic hyperplasia (BPH). The screening for PCa has been improved when trans-rectal ultrasound (TRUS) guided prostate biopsy is employed which provide histopathological examination, and the positive results indicate a clinical suspicion of PCa (Li, et al., 2013). But they also provide limited information on the extent and the differentiation of PCa. It is expected that the number of patients who are diagnosed with prostate cancer will double in the future. Consequently, there is a need for an effective technique to aid the physicians first for an accurate diagnose and the patients for best treatment decision. Among all the imaging modality the availability of Magnetic Resonance Imaging (MRI) provides a solution as an excellent imaging modality to meet these challenges to detect, localize, and stage the aggressiveness of PCa (Bloch, Lenkinski, & Rofsky, 2008). However, MRI still need for an external hardware to strengthen the utility of this imaging modality Furthermore, the application of texture analysis (TA) is a promising tool to assess PCa which has an advantage in early detection and measurement of the disease without the increase of the acquisition time.
Chapter II: Background
Prostate cancer and treatment options
In 1853, John Adams, a surgeon at The London Hospital discovered the first prostatic cancer case as a rare disease in a 59-year-old male patient by histological examination (Li, et al., 2013). 150 years later, the number of cases diagnosed with prostate cancer has increased remarkably and became a significant health problem in the US with 180,000 new cases and about 31,000 deaths occurring annually (Samuel R. Denmeade, 2002). PCa is one of the cancers that can slowly grow that they can be not threatening to patient’s life. Conversely, if its metastasize, the disease will become fatal and threaten the lives as there is currently no cure (Bloch, Lenkinski, & Rofsky, 2008).
PCa staging relies on three factors tumor, node, and metastasis (TNM) staging (Li, et al., 2013). PCa begins within the prostate gland, and it is most successfully treated when the tumor has still enclosed the gland. As mentioned earlier, once the tumor extends outside the prostate, the chances of cure diminished significantly. There are different cell lines, some of which multiply more quickly than others and tend to mutate into a more aggressive disease (Feng TS, 2015). Moreover, these cells have a higher probability of reaching the firm outer edge of the gland, called the capsule, and breaking through it(Feng TS, 2015). This capsule is called extracapsular extension (ECE), so the tumor has penetrated the capsule and begun growing outside of it (Feng TS, 2015). ECE is not often determined by ultrasound imaging (USI), or by TRUS biopsy (Feng TS, 2015). Rather, the probability of ECE was predicted by using nomograms based on clinical factors such as age, PSA and Gleason score drawn from large-scale population data (Feng TS, 2015). Without known evidence of ECE, many patients with both favorable and unfavorable clinical factors chose to be treated by radical prostatectomy, usually based on their doctors’ recommendations (Feng TS, 2015). Once the gland is removed and sent to pathology for examination, the discovery of ECE is not a pleasant revelation (Feng TS, 2015). Compared with organ-confined disease, prostate cancer with extracapsular extension is associated with decreased overall and cancer-specific survival following radical prostatectomy (Feng TS, 2015). Patients found to have ECE are typically be sent for a course of beam radiation and/or be put on androgen deprivation therapy as a management strategy though it is not curative (Feng TS, 2015). Thus, the detection and treatment plan are still in a dilemma as prostate cancers demonstrate a broad range of biologic activity with the majority of a case not leading to a prostate specific death. Also, the current treatment options available for patients have significant side effects such as incontinence, rectal injury, and impotence. Patient’s survival depends on the type of tumor is determined. In 2000, MRI in detecting ECE began to be noticed in many medical journals. MRI is highly sensitive and becomes a determining factor to provide pretreatment information and helping the physician in the treatment decision. Furthermore, Recent advances in MRI/MRS of the prostate are beginning to meet these challenges.
Clinical staging without imaging:
Currently, elevated levels of the PSA in the blood and DRE are still used remain is used for diagnosing and staging prostatic cancer. PSA ishas been approved by the U.S Food and Drug Administration (FDA) in 1986 to be used as a primary biomarker to diagnose PCa (Li, et al., 2013). It has some limitation in which it is not capable of differentiating between PCa and benign prostatic hyperplasia (BPH). High PSA levels typically indicate for a blinded sextant TRUS-guided symmetrical needle biopsy. However, TRUS biopsies have been associated with a significantly lower Cap detection accuracy due to the low specificity of the PSA and poor image resolution of ultrasound. Thus, recent advances in medical imaging such as MRI and others are beginning to meet these challenges.
Imaging of prostate cancer:
Ultrasound Imaging (USII):
High PSA levels typically indicate for a blinded sextant TRUS-guided symmetrical needle biopsy. However, TRUS biopsies have been associated with a significantly lower Cap detection accuracy due to the low specificity of the PSA and poor image resolution of ultrasound. USI has limited value to its limitation to its spatial resolution and not proven satisfactory for local staging of prostate cancer (got this from https://acsearch.acr.org/docs/69371/Narrative/REF of one real paper from Pubmed). Furthermore, prostate cancer appears as a hypoechoic lesion in the peripheral zone on the transrectal probe. Many cancers can be undetected and are presumably isoechoic. A study of 2427 men provided through the American Society of 2427 men, a total of 52 cancers were detected. Of these, TRUS identified 44 (85%), indicating its limited sensitivity. The addition of color and power Doppler has been reported to improve the detection of prostate cancer by identifying increased vascularity but has not yet been shown to improve staging accuracy. (got this from https://acsearch.acr.org/docs/69371/Narrative/ ) REF of real paper..
Computed Tomography (CT)
CT lacks sufficient soft tissue contrast in initial staging and in assessing the local extent of prostatic carcinoma in low-to-intermediate –risk patients. However, it has a great value in the evaluation of distant spread of the disease and should be reserved for use in patients with higher probability of metastases (John M. Heath, 1998).
Magnetic Resonance Imaging MRI
Magnetic Resonance Imaging has been employed in the development of the noninvasive approach to assess and detects prostate cancer because it provides the highest spatial resolution compared with the other imaging modalities. It can be performed with or without the insertion of the endorectal coil. Although the endorectal coil insertion discomfort some patients, using it whether in 1.5T or higher field strength has the benefit of providing the highest spatial resolution among all the imaging modalities. Furthermore, the variation of techniques including T1-weighted images, T2 weighted images, dynamic contrast enhanced (DCE) T1-weighted images (DCE-T1-WI), MR spectroscopy (MRS), diffusion weighted images (DWI), provide many chanced to diagnose the biologic processes.
T2 weighted images (T2-WI):
T2 weighted image is the most commonly used since it led to an excellent image quality and resolution. There are intrinsic complexities in imaging prostate that limit staging accuracy. The good spatial resolution achieved with the endorectal coil in 3T MRI scan with at least halving the voxel size (voxel size 0.35 mm3 v 0.66-1.12 mm3), reveals pathoanatomic details on T2-WI not seen at 1.5T or 3T without endorectal coil (Bloch, Lenkinski, & Rofsky, 2008). In T2-WI, the interpretation of PCa can be affected by false-positive findings such as prostatitis, post-biopsy hemorrhage, and fibrosis. Thus, the addition of functional magnetic resonance imaging (fMRI) is necessary to improve the accuracy of diagnosing PCa such as dynamic contrast enhanced-MRI (DCE-MRI), MR spectroscopy (MRS), diffusion weighted imaging (DWI) (Li, et al., 2013).
Dynamic Contrast Enhanced MRI (DCE- MRI):
DCE-MRI can diagnose earlier and more intense enhancement in sites of tumor compared with the normal peripheral zone. Prostate cancer like any tumors has two factors microvessel density (MVD) and angiogenic that were evaluated as prognostic factors in patients with prostate cancer. MVD has been correlated with clinical and pathological stage, metastasis, and histological grade in prostate cancer (Bloch, Lenkinski, & Rofsky, 2008). Although there is some controversy, MVD also has been correlated with disease-specific survival and progression after treatment. Moreover, recent data suggest that DCE-MRI can provide valuable information about individual MVD in prostate cancer. Thus, there are biological features associated with prostate cancer that can be demonstrated with DCE-MRI for further disease characterization (Bloch, Lenkinski, & Rofsky, 2008).
Magnetic Resonance Spectroscopic Imaging (MRSI):
The addition of MRSI to MR imaging significantly improves characterization of peripheral zone prostate tissue as benign or malignant. Coakley et al. demonstrated that prostate cancers have a characteristic loss of the citrate peak and gain in the choline/creatine peak on MRSI. Moreover, the ratio of choline to citrate is related to the Gleason score, indicating that MRSI provides information about tumor aggressiveness (got this from https://acsearch.acr.org/docs/69371/Narrative/ ). MRS facilitates the differentiation of normal and altered tissue metabolism. Therefore, it is different to other imaging methods that only assess abnormalities of structure or perfusion. Incremental improvement in accuracy of cancer detection and staging has been reported when MRSI was added to endorectal MRI (erMRI) alone (got this from https://acsearch.acr.org/docs/69371/Narrative/ ). As an indicator of outcome, MRSI has been shown predictive of biochemical recurrence. However, a recent American College of Radiology Imaging Network® (ACRIN®) multicenter trial showed no incremental benefit of MRSI for localizing prostate cancer over 1.5T erMRI alone (got this from https://acsearch.acr.org/docs/69371/Narrative/ ). MRSI cannot yet be considered to provide significant advantages in local staging before treatment (got this from https://acsearch.acr.org/docs/69371/Narrative/ ).
Diffusion-weighted imaging (DWI):
The inclusion of DWI technique to MR prostate imaging gives an additional method to improve prostate tumor detection and localization compared to T2-Weighted Images alone (got this from https://acsearch.acr.org/docs/69371/Narrative/). It generates tissue contrast reflecting water molecular diffusion using apparent diffusion coefficient (ADC) mapping. MR diffusion has been used commonly for evaluating acute stroke in the brain. Recently, it has been suggested that DWI may also play a role in the early detection of tumor response to therapy.
BPH vs Ca and what do we see on MRI
Why difficult to differentiate
Challenges of prostate MRI ( central gland, BPH, WHAT IS BPHMRI Prostate Challenges:
Although MRI in managing and detecting the prostate cancer is expanding, its exact role is not yet defined. The staging of PCa is still challenging in which there are potential indications for prostate MRI include surveillance in patients known to have low-risk prostate cancer, for staging in patients with intermediate and high-risk cancer prior to therapy, and for detection of cancer in patients with elevated PSA but negative TRUS biopsy (Sajal S. Pokharel, 2015).
Benign prostatic hyperplasia (BPH) is not a prostate cancer. It is a benign enlargement of the prostate due to an abnormal growth of the noncancerous prostate cells. They differ in the way they develop. Prostate cancer commences in the outer peripheral zone of the prostate and grown outward invading the surrounding tissues whereas in BPH the growth in inward toward the prostate’s core and begins in the inner area of the prostate called the transition zone that is a ring tissue circling and tightening the urethra. That’s why BHP produces noticeable symptoms such as affecting the urination while the prostate cancer is often silent disease with no obvious symptoms often for years.
CAD analysis of DCE MRI ( Breast MRI prostate MRI)
Summary, Challenges ( BPH and Cancer overlap.)
Texture analysis
Among other promising imaging techniques to assess prostate cancer us texture analysisAlthough there is an increase interest in the role of MRI to evaluate PCa aggressiveness, there is still need for advance methods of image processing and analysis as a next step to overcome the challenges. Texture analyses is a branch of image processing which aims to reduce image information by extracting texture description from image (Brian Barry, 2014) have been proven to be a useful tool for determining prostate cancer. This extraction may allow for the It features mathematical and statistical analyses to detect a subtle MRI signal changes among image pixels (Brian Barry, 2014). In other words, it determines of the relationship between adjacent pixels within an image that is not seen and distinguish by human eye (Wibmer A1, 2015). It describes how often one grey tone will appear in a specified spatial relationship to another grey tone on the Theimage (Wibmer A1, 2015) (Haralick RM, 1973). By using a series of mathematical equations, it generates a range of quantitative parameters (‘texture features’) that characterize the spatial variation of grey levels throughout an image (Wibmer A1, 2015). The early changes in the image texture are of particular relevance, as relatively normal-appearing tissues with subtle microscopic disturbances due to disease, such as in the case of hepatic fibrosis, may be detected in its earlier stages (HeiShun Yu, 2015).
The major advantage of this approach is the ability to detect early and quantify a chronic disease without increasing the acquisition time of the image or the dose for the patient.
Chapter III: Methods and Materials
The data cohort of 10 patients in this study was collected from a previously conducted prospective study approved by the Institutional Review Board (IRB) at The Beth Israel Deaconess Medical Center (BIDMC). All these patients in this prospective study was confirmed to have PCa through positive core needle biopsy. Before performing the radical prostatectomy, they were scanned using 3T MRI scan with both coils torso-phased array and erCoil. After the surgery, it was ensured that the sectioning was done in a plane corresponding to the pre-oprative MRI by sectioning and staining with hematoxylin and eosinthe excised glands.
McNeals recommendation is that patient study was classified into two categories; central gland (CG) and peripheral zone (PZ) PCa if more than 70% of prostate volume was found in a particular zone. From the 22 MRI data sets, 16 were determined as PZ PCa (50 2D sections) and 6 were found as having PCa in the CG (30 2D sections). Only those sections were chosen to be included in the study which showed an explicit focus of PCa in either CG or PZ to make sure that the sets of CG and PZ PCa were distinct from each other.
The prostate region of interest (ROI) was automatically delineated by an expert pathologist on T2-WI and DCE images using automated prostate capsule segmentation scheme. In brief the scheme involves first automatically identifying prostatic voxels within a bounding box around the prostate area to obtain a boundary initialization for an Active Shape Model (ASM) scheme. A total of 110 texture features were then extracted on a per-voxel basis from all T2-WI and DC data sets. Then, Redundancy Maximum Relevance (mrRMR)Statistical significance test was used for feature selection scheme is used to find an ensemble of features that will allow for optimal identificationdifferentiation of PCa from BPH presence on MRI. A two separate sets of data were comprised the feature and label data corresponding to voxels from 16 data sets with PZ PCa and from 6 data sets with CG PCa.
3.1 MRI Protocols
10 patients, whether they are evaluated for pre- or post-therapeutic assessment, undergo the same standardized comprehensive MR protocol at The Beth Israel Deaconess Medical Center (BIDMC):
3.2 Patient Selection and Preparation
Patients are asked to refrain from ejaculation for three days preceding the exam to ensure optimal distension of the seminal vesicles. A sodium phosphate enema is administered on the day of the study in order to minimize fecal residue in the rectum. A1mg glucagon i.m. injection is administered to reduce peristaltic motion. The ERC (MRInnervu, Medrad, Pittsburgh, PA) is inserted into the rectum and connected to a pelvic phased-array coil with a coupling device to combine the surface phased array coil with the endorectal coil. Barium suspension is used to fill the ERC balloon, with a typical volume of 80cc’s, however, adjusted for patient tolerance. The use of Barium reduces susceptibility effects when compared to the use of air and should improve MRS and DWI results.
The imaging parameters are summarized in Table 1.
T2W images— transverse and coronal fast spin-echo T2-weighted images are obtained from below the prostatic apex to above the seminal vesicles using the following parameters:
repetition time msec/echo time msec (effective) 4,500–7600/165, 2.0–2.2mm section thickness and no intersection gap, 3 averages, 14-cm field of view, 256 Å~ 192 matrix, and no phase wrap. A unique attribute of this protocol is the use of thinner sections than have been the previous routine. This results in 30% – 50% more sampling of the gland compared to the traditional 3–4 mm section approach. The phase encoding direction is left-right.
Three-dimensional (3D) T1-weighted (T1W) gradient echo (GRE) images— These are acquired prior to, during, and after contrast injection. DCE images are obtained after bolus injection of gadopentetate dimeglumine (Magnevist®; Berlex Laboratories, Wayne, NJ) at a dose of 0.1 mmol / kg of body weight administered with a mechanical injection system (Spectris® MR Injection System, MEDRAD, Pittsburgh, PA) at a flow rate of 4ml/sec. The imaging parameters of the 3D GRE sequence are: TR/TE 9.3/4.2 msec, flip angle 18°, FOV 14cm, matrix 256 Å~ 224, ST: 2.0–2.6mm, no phase wrap, which can be obtained with a temporal resolution of approximately 1 minute, 35 seconds. Two pre-contrast and five post-contrast sequential acquisitions are obtained.
For the pre-contrast scans, the first is used to ensure relevant anatomic coverage; the second is used as part of a continuous series of pre- and post-acquisitions in which the instrument settings (gain and attenuation values) are identical. Contrast injection is initiated during the last 10 seconds of the 2nd pre-contrast acquisition.
Echo-planar Diffusion weighted images (EPI)— transverse DWI with whole gland coverage is performed with the following parameters: TR/TE = 6500/80.6 msec; parallel imaging factor = 2; averages= 2 NEX; FOV 24cm; slice thickness = 3 thick; matrix = 256 Å~ 192; scan time: 7:12 min; B-value= 0,1000; number of directions = 25. Instead of using more averages (NEX) to gain adequate signal at this high spatial resolution, we choose 25 directions, to achieve not only a better signal-to-noise ratio, but also improved results in diffusion tensor imaging and anisotropic maps as well as enhanced contrast in the ADC maps.
Axial spin-echo or fast spin-echo T1W images— T1-weighted images from the aortic bifurcation to the symphysis pubis. TR/TE = 600–700/− 12 msec. Slice thickness 4–6 mm. Interslice gap 0–1 mm. Matrix 256 Å~ 192. Frequency direction transverse (to prevent obscuration of pelvic nodes by endorectal coil motion artifact). Number of excitations = 1. FOV 20–32 cm.
3.3 MR Applications at the BIDMC
combined a T2-W and DCE-MR protocol revealed a mean sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the detection of ECE of 86%, 95%, 90% and 93%, respectively [77]. The sensitivity for ECE MRI was improved by more than 25% using the combined T2-W/DCE-MRI approach compared to T2-W MRI alone. The combined T2-W/DCE-MRI approach had a mean overall staging accuracy of 95%, as determined by the area under the receiver operating characteristic curve. Staging results were significantly improved (p < .05) using the combined approach compared to T2-W MRI alone. Figure 1 shows an example of MRI at 3T performed for pre-therapeutic evaluation and staging.
These nomograms are based on clinical parameters, such as clinical stage and grade before prostatectomy/radiation therapy, PSA doubling time, and time between therapy and PSA relapse, nomograms estimate the probability of local and distant recurrence based on averages over large numbers of patients. Thus, these parameters are of limited benefit to the individual seeking advice on the approach to his disease. Hence, both patient and clinician are forced to make important choices among local and systemic therapies without knowing the true localization and the extent of the recurrent disease. Essential questions to be answered are: 1) is the PSA relapse caused by local or distant recurrence? 2) Is the tumor multi-focal, and if so, how many tumors are there within the prostate (bed)? 3) What is the total volume of the recurrent cancer? 4) Have malignant cells already spread to the nearby lymph nodes? Without answers to these questions, patients and physicians are relegated to critical decisions based on statistical probabilities.
Prostate cancer has many expressions and needs to be addressed on an individual basis for optimized management in each patient. Conventional MR imaging shows limited results in local recurrence detection, influenced by the negative impact of post-interventional changes on tumor detection. T2-W MRI cannot not readily distinguish between the low signal intensities of fibrotic changes, scar tissue and cancerous tissue after prostatectomy, or the low signal intensities of post radiation changes. DCE-MRI, however, is able to differentiate between cancer tissue and fibrotic or radiated tissue based on the enhancement features. Figure 2 shows an example of high resolution DCE-MRI and detection of local recurrence after Brachytherapy at 3T.
The patient underwent Brachytherapy seed implantation 3 years prior to the MRI, and was referred after PSA-relapse. Note the local recurrence in a “cold spot” where there is a relative lack of seeds, in the posterior right peripheral zone. Note the seeds visualized as small signal voids (black) in post-contrast image (Figure 2b) and the clear visualization of the cancer on the parametric map (Figure 2c). The MRI diagnosis was confirmed by targeted biopsy.
Prostate Cancer Detection and Localization in Patients with Repeat Negative
Biopsies— In an ongoing prospective study we are currently investigating the value of high spatial resolution dynamic contrast enhanced (DCE-) with high spatial resolution T2-weighted (T2-W) endorectal (ER) coil magnetic resonance imaging (MRI) at 3 Tesla for detection and localization of prostate cancer in patients with repeat negative biopsies and rising prostate specific antigen (PSA), using histopathology of the subsequent biopsy as the reference standard. The preliminary results are promising. MR based biopsy detected prostate cancer in
>50% of patients, with the tumor being located in the anterior gland, as predicted by MRI, in the majority of the cases. These results suggest an improvement over previously reported results of randomly performed repeat biopsies or targeted sextant biopsies with emphasis on anterior and lateral tissue sampling [83–85]. This preliminary data suggests that MRI can assist in the reduction of repeat negative biopsies in patients with rising PSA. Figure 3 shows a patient with 3x repeat negative biopsies (total 63 negative cores) and a rising PSA (27 ng/ml) prior to the MR exam. A targeted ultra-sound guided biopsy based on the MRI findings confirmed cancer in the anterior gland. Consequently, the patient underwent prostatectomy.
Below is added from the power point
Pre-processing
The pre-processing procedures for the T2 weighted images -> involved the correction of the bias and the standardization of the image intensities to yield a representative image. For the DCE images, the pre-processing procedures involved the correction of bias and the registration of images to the point 1 for every patient. Bias correction and all images intensities are standardized to a representative template
DCE images -> Bias correction and all images are registered to time point 1 for that patient
Following pre-processing texture features from ROI were extracted and analyzed. Some of the tTexture features that were extracted included the are,
Iintensity mean and standard deviation.
The intensity mean and the standard deviation are important values in the analysis of digital images. This is especially the case when the texture analysis is performed using MATLAB. The mean values for the intensity are used in the first-order grey scale analysis. The standard deviation is an important part of the interpretation of the mean intensity.
The other texture feature was Sobel (Edge detection).
The analysis of data required the determination of the intensity of the digital images taken using the magnetic resonance imaging machine and the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI). The intensity function can only be determined at discrete points. The underlying assumption in the application of the Sobel operator for edge detection is that there is a continuous intensity function. The Sobel operator serves as a differentiation operator which determines the by approximation the image intensity function’s gradient.
Haralick features and Gabor features were also some of the texture features.
Haralick features are important in the differentiation of the homogenous low SI regions of the prostate cancer. The analysts use the Haralick features to differentiate them from the normal prostate which have a hyper-intense appearance (Haralick, 1973).
Gabor features
The Gabor feature of interest was the Gabor wavelet transform. This was acquired through the application of the Gaussian function to modulate a complex sinusoid. The purpose of this feature is to the matching of localized frequency characteristics based on their scales and orientations. This feature is important in the identification of the appearance of prostate cancer. This is through the quantification of the visual processing features that radiologists rely upon in the examination of the appearance of the prostate cancer.
Chapter IV: Result
Results
The analysis of the images found that there was a statistically significant difference in the T2 weighted images as was observed using the Haralick features. Of note is the fact that the T2 weighted images were taken using a magnetic resonance imaging machine (Viswanath et al., 2012).
In T2 images statistical significant differences were observed in Haralick features (Slide 2)
The analysis of the images that were taken using the the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) showed that there was a statistically significant difference in the mean intensity, Sobel, Gabor, and Haralick features.
In DCE images statistically significant differences were observed in mean intensity, Sobel, Gabor and Haralick features (Slide 3)
below as requested to be add them here
FIGURE: Difference in feature expression is observed between Cancer and BPH using Haralick entropy and inertia features.The figure above which is generated when inertia forces and Haralick entropy is used shows that there is a difference in the expression of features when the cancer is compared to the benign prostatic hyperplasia. :..
Discussion
The initial findings of the exercise are very promising. The statistically significant differences between the benign prostatic hyperplasia and the prostate cancer as determined using the magnetic resonance imaging and the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) contributes to the body of information on the subject. It also contributes to the understanding of the modalities though which the accuracy in the detection of prostate cancer can be improved given the limitations in the methods available.
The use of a Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) results in better differentiation of the benign prostatic hyperplasia when compared to the T2-weighted images which are taken using a magnetic resonance imaging machine. As discussed above, the improved differentiation when the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) is used is because of the heightened sensitivity. The heighted differentiation of the benign prostatic hyperplasia is also because of the increase resolution when the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) is used in generating the images of the subject.
When the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) was used, the researcher also found that there were statistically significant differences in the mean intensity, Sobel, Gabor, and Haralick features. This is very significant for future research into the detection, localization and the differentiation between the prostate cancer and the benign prostatic hyperplasia. Researchers can combine the statistically significant features in mean intensity, Sobel, Gabor, and Haralick to build a detection system that can be used not only in the detection and localization, but also in the differentiation of prostate cancer and the benign prostatic hyperplasia.
This can be achieved by using the statistically significant different features as a baseline against which images can be compared. However, there is need for refinement of the image and their combination in a manner that helps achieve these objectives. Despite the insurmountable challenges, the thesis made significant findings that not only contributed to the body of knowledge but also helped generate a potential area for future research in the detection and localization of prostate cancer as well as the differentiation of prostate cancer and the benign prostatic hyperplasia.
The current study was limited in the fact that the number of patients who were enrolled to participate was small. A small sample size has an effect on the validity and credibility of the results. It also affects the sampling criteria and by association, the generalizability of the results. Future studies require a detailed logistical planning to ensure that a sizable sample is acquired for any studies.
Chapter V: ConclusionDiscussion
The proper treatment of cancer is dependent on its accurate detection, characterization of the tumor, and the differentiation of benign cells and from cancerous cells. Texture analysis presents a solution to mitigate some of the challenges that have been addressed in the thesis. Texture analysis shows great potential in the detection of prostate and breast cancer. The analysis of the intensities in the region of interest using superior software such as MATLAB has shown a significant improvement in the detection of cancerous cells.
The accurate detection and characterization of cancer cells is important in understanding its prognosis. It also helps to improve the patient outcomes through its influence in the formulation of individualized treatments. However, the characterization of tumors has been challenged by technological challenges. Texture analysis offers a reprieve in that regard. Texture analysis offers potential for the advancement of this area of cancer research and treatment.
Finally, texture analysis is important in the differentiation of benign prostatic hyperplasia from cancerous cells. The application of texture analysis has shown that there is a statistically significant difference when different images are analyzed using superior statistical analysis and image analysis approaches and tools. This potential can be developed further in future studies. Various conclusions can be drawn from the results and finding s from analysis presented above. The use of a Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) results in better differentiation of the benign prostatic hyperplasia when compared to the T2-weighted images which are taken using a magnetic resonance imaging machine. As discussed above, the improved differentiation when the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) is used is because of the heightened sensitivity. The heighted differentiation of the benign prostatic hyperplasia is also because of the increase resolution when the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) is used in generating the images of the subject. When the Dynamic Contrast Material-Enhanced Magnetic Resonance Imaging (DCE-MRI) was used, the researcher also found that there were statistically significant differences in the mean intensity, Sobel, Gabor, and Haralick features. This is very significant for future research into the detection, localization and the differentiation between the prostate cancer and the benign prostatic hyperplasia. Researchers can combine the statistically significant features in mean intensity, Sobel, Gabor, and Haralick to build a detection system that can be used not only in the detection and localization, but also in the differentiation of prostate cancer and the benign prostatic hyperplasia. This can be achieved by using the statistically significant different features as a baseline against which images can be compared. However, there is need for refinement of the image and their combination in a manner that helps achieve these objectives. Despite the insurmountable challenges, the thesis made significant findings that not only contributed to the body of knowledge but also helped generate a potential area for future research in the detection and localization of prostate cancer as well as the differentiation of prostate cancer and the benign prostatic hyperplasia.
Conclusions
BPH is better differentiated in DCE images compared to T2
The statically significant features may be combined to build a BPH vs cancer detection system in future.
Chapter VI: Conclusion
APPENDIX
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REFERENCES
Bloch, N. B., Lenkinski, R., & Rofsky, N. (2008). The role of magnetic resonance I maging (MRI) in prostate cancer imaging and staging at 1.5 and 3 Tesla: the Beth Israel Deaconess Medical Center (BIDMC) approach. Cancer Biomark , 251-262.
Haralick R. (1973). Textural Features for Image Classification. IEEE Trans Syst Man Cybern , 610–621.
Viswanath, S., Bloch, N., Chappelow, J., Toth, R., Rofsky, N., Ganega, E., Lenkinski, R. and Madabhushi, A. (2012). Central Gland and Peripheral Zone Prostate Tumors Have Significantly Different Quantitative Imaging Signatures on 3 Tesla Endorectal, In Vivo T2-Weighted MR Imagery. Journal of Magnetic Resonance Imaging, 36: 213-224.
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CURRICULUM VITAE
[This is where your CV goes. You may place a Vita here instead, and change the heading. If you do a Vita, it should be a third-person narrative; change the paragraph spacing to double. This section must include you year of birth (not full birthday), contact information and education. Name must match your name on the title and abstract page exactly].
Chapter VI: Conclusion
Bibliography
Reference list:
HYPERLINK "http://www.cancer.net/cancer-types/prostate-cancer/statistics" http://www.cancer.net/cancer-types/prostate-cancer/statistics
HYPERLINK "http://www.pcf.org/site/c.leJRIROrEpH/b.5780045/k.3758/Benign_Prostatic_Hyperplasia_BPH.htm" http://www.pcf.org/site/c.leJRIROrEpH/b.5780045/k.3758/Benign_Prostatic_Hyperplasia_BPH.htm
HYPERLINK "http://sperlingprostatecenter.com/extracapsular-extension-and-treatment-decisions/" http://sperlingprostatecenter.com/extracapsular-extension-and-treatment-decisions/
