Optimization of the Balanced Steady State Free Precession (bSSFP) Pulse Sequence for Magnetic Resonance Imaging of the Mouse Prostate at 3T

INTRODUCTION: MRI can be used to non-invasively monitor tumour growth and response to treatment in mouse models of prostate cancer, particularly for longitudinal studies of orthotopically-implanted models. We have optimized the balanced steady-state free precession (bSSFP) pulse sequence for mouse prostate imaging. METHODS: Phase cycling, excitations, flip angle and receiver bandwidth parameters were optimized for signal to noise ratio and contrast to noise ratio of the prostate. The optimized bSSFP sequence was compared to T1- and T2-weighted spin echo sequences. RESULTS: SNR and CNR increased with flip angle. As bandwidth increased, SNR, CNR and artifacts such as chemical shift decreased. The final optimized sequence was 4 PC, 2 NEX, FA 50°, BW ±62.5 kHz and took 14-26 minutes with 200 µm isotropic resolution. The SNR efficiency of the bSSFP images was higher than for T1WSE and T2WSE. CNR was highest for T1WSE, followed closely by bSSFP, with the T2WSE having the lowest CNR. With the bSSFP images the whole body and organs of interest including renal, iliac, inguinal and popliteal lymph nodes were visible. CONCLUSION: We were able to obtain fast, high-resolution, high CNR images of the healthy mouse prostate with an optimized bSSFP sequence

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Comparison of Histogram-based Textural Features between Cancerous and Normal Prostatic Tissue in Multiparametric Magnetic Resonance Images

In the last decade, multiparametric magnetic resonance imaging (mpMRI) has been expanding its role in prostate cancer detection and characterization. In this work, 19 patients with clinically significant peripheral zone (PZ) tumours were studied. Tumour masks annotated on the whole-mount histology sections were mapped on T2-weighted (T2w) and diffusion-weighted (DW) sequences. Gray-level histograms of tumoral and normal tissue were compared using six first-order texture features. Multivariate analysis of variance (MANOVA) was used to compare group means. Mean intensity signal of ADC showed the highest showed the highest area under the receiver operator characteristics curve (AUC) equal to 0.85. MANOVA analysis revealed that ADC features allows a better separation between normal and cancerous tissue with respect to T2w features (ADC: P = 0.0003, AUC = 0.86; T2w: P = 0.03, AUC = 0.74). MANOVA proved that the combination of T2-weighted and apparent diffusion coefficient (ADC) map features increased the AUC to 0.88. Histogram-based features extracted from invivo mpMRI can help discriminating significant PZ PCa

Computer-Assisted Characterization of Prostate Cancer on Magnetic Resonance Imaging

Prostate cancer (PCa) is one of the most prevalent cancers among men. Early diagnosis can improve survival and reduce treatment costs. Current inter-radiologist variability for detection of PCa is high. The use of multi-parametric magnetic resonance imaging (mpMRI) with machine learning algorithms has been investigated both for improving PCa detection and for PCa diagnosis. Widespread clinical implementation of computer-assisted PCa lesion characterization remains elusive; critically needed is a model that is validated against a histologic reference standard that is densely sampled in an unbiased fashion. We address this using our technique for highly accurate fusion of mpMRI with whole-mount digitized histology of the surgical specimen. In this thesis, we present models for characterization of malignant, benign and confounding tissue and aggressiveness of PCa. Further validation on a larger dataset could enable improved characterization performance, improving survival rates and enabling a more personalized treatment plan

Accuracy of tumor segmentation from multi-parametric prostate MRI and 18F-choline PET/CT for focal prostate cancer therapy applications

Abstract Background The study aims to assess the accuracy of multi-parametric prostate MRI (mpMRI) and 18F-choline PET/CT in tumor segmentation for clinically significant prostate cancer. 18F-choline PET/CT and 3 T mpMRI were performed in 10 prospective subjects prior to prostatectomy. All subjects had a single biopsy-confirmed focus of Gleason ≥ 3+4 cancer. Two radiologists (readers 1 and 2) determined tumor boundaries based on in vivo mpMRI sequences, with clinical and pathologic data available. 18F-choline PET data were co-registered to T2-weighted 3D sequences and a semi-automatic segmentation routine was used to define tumor volumes. Registration of whole-mount surgical pathology to in vivo imaging was conducted utilizing two ex vivo prostate specimen MRIs, followed by gross sectioning of the specimens within a custom-made 3D-printed plastic mold. Overlap and similarity coefficients of manual segmentations (seg1, seg2) and 18F-choline-based segmented lesions (seg3) were compared to the pathologic reference standard. Results All segmentation methods greatly underestimated the true tumor volumes. Human readers (seg1, seg2) and the PET-based segmentation (seg3) underestimated an average of 79, 80, and 58% of the tumor volumes, respectively. Combining segmentation volumes (union of seg1, seg2, seg3 = seg4) decreased the mean underestimated tumor volume to 42% of the true tumor volume. When using the combined segmentation with 5 mm contour expansion, the mean underestimated tumor volume was significantly reduced to 0.03 ± 0.05 mL (2.04 ± 2.84%). Substantial safety margins up to 11–15 mm were needed to include all tumors when the initial segmentation boundaries were drawn by human readers or the semi-automated 18F-choline segmentation tool. Combining MR-based human segmentations with the metabolic information based on 18F-choline PET reduced the necessary safety margin to a maximum of 9 mm to cover all tumors entirely. Conclusions To improve the outcome of focal therapies for significant prostate cancer, it is imperative to recognize the full extent of the underestimation of tumor volumes by mpMRI. Combining metabolic information from 18F-choline with MRI-based segmentation can improve tumor coverage. However, this approach requires confirmation in further clinical studies.https://deepblue.lib.umich.edu/bitstream/2027.42/142871/1/13550_2018_Article_377.pd

Illuminating the pathway:For image-guided prostate cancer care

The aim of this thesis is to improve the diagnostic pathway for prostate cancer (PCa) and to develop a minimal invasive focal ablative treatment for PCa. In Chapter 2 risk stratification for detection of clinically significant PCa (csPCa) with systematic biopsy in biopsy naive patients with prostate imaging-reporting and data system (PI-RADS) classification ≤2 on pre-biopsy prostate MRI is evaluated, predictors for csPCa are integrated into a novel risk calculator and compared to contemporary risk calculators. Furthermore, in Chapter 3 an optimal biopsy strategy is determined for prostate biopsy patients with a unilateral PI-RADS classification ≥3 on pre-biopsy prostate MRI based on detection rates of csPCa and iPCa using different combinations of MRI-targeted biopsy, ipsilateral and/or contralateral systematic biopsy. Additionally, in Chapter 4 safety and feasibility of needle-based confocal laser endomicroscopy (CLE) for real-time PCa detection is investigated in prostate biopsy patients. In Chapter 5 safety and feasibility and short-term quality of life outcomes of transperineal focal laser ablation (TPLA) for treatment of PCa under local anesthesia in a daycare setting is evaluated. Moreover, in Chapter 6 three-dimensional ablative effects of TPLA for treatment of PCa are visualized on prostate MRI and contrast-enhanced ultrasound (CEUS) and correlated with whole-mount prostate histology after RARP. Finally, in Chapter 7 safety, feasibility and medium-term oncological and functional outcomes of salvage RARP are studied for recurrent localized PCa following initial focal ablative therapy using irreversible electroporation (IRE)

Raman spectroscopy for medical diagnostics - From in-vitro biofluid assays to in-vivo cancer detection

This is the final version of the article. Available from the publisher via the DOI in this record.Raman spectroscopy is an optical technique based on inelastic scattering of light by vibrating molecules and can provide chemical fingerprints of cells, tissues or biofluids. The high chemical specificity, minimal or lack of sample preparation and the ability to use advanced optical technologies in the visible or near-infrared spectral range (lasers, microscopes, fibre-optics) have recently led to an increase in medical diagnostic applications of Raman spectroscopy. The key hypothesis underpinning this field is that molecular changes in cells, tissues or biofluids, that are either the cause or the effect of diseases, can be detected and quantified by Raman spectroscopy. Furthermore, multivariate calibration and classification models based on Raman spectra can be developed on large "training" datasets and used subsequently on samples from new patients to obtain quantitative and objective diagnosis. Historically, spontaneous Raman spectroscopy has been known as a low signal technique requiring relatively long acquisition times. Nevertheless, new strategies have been developed recently to overcome these issues: non-linear optical effects and metallic nanoparticles can be used to enhance the Raman signals, optimised fibre-optic Raman probes can be used for real-time in-vivo single-point measurements, while multimodal integration with other optical techniques can guide the Raman measurements to increase the acquisition speed and spatial accuracy of diagnosis. These recent efforts have advanced Raman spectroscopy to the point where the diagnostic accuracy and speed are compatible with clinical use. This paper reviews the main Raman spectroscopy techniques used in medical diagnostics and provides an overview of various applications

Investigation of Endogenous In-Vivo Sodium Concentration in Human Prostate Cancer Measured With 23Na Magnetic Resonance Imaging

Prostate cancer (PCa) is the most common malignancy in men. Aggressive prostate tumours must be identified, differentiated from indolent tumours, and treated to ensure survival of the patient. Currently, clinicians use a combination of multi-parametric magnetic resonance imaging (mpMRI) contrasts to improve PCa detection. While these techniques provide very good spatial resolution, the specificity is often insufficient to unequivocally identify malignant lesions. Utilizing specialized MRI hardware developed for sensitive in-vivo detection of sodium, this work has investigated differences in sodium concentration between healthy and malignant prostate tissue. Patients with biopsy-proven PCa underwent conventional mpMRI and sodium MRI followed by radical prostatectomy. Subsequent whole-mount histopathology of the excised prostate was then contoured according to Gleason Grade, a radiological assessment of tumour stage and aggressiveness for PCa. Tissue sodium concentration (TSC) measured by sodium MRI was successfully co-registered with standard image contrasts from multi-parametric MRI and also with pathologist confirmed histopathology as the gold standard. This proposed method provides quantitative, in-vivo sodium information from cancerous human prostates. The results of this study establish the relationship between TSC and malignant PCa, which could prove useful in initial characterization of the disease and for active surveillance of indolent lesions