134 research outputs found

    Choline PET and PET/CT in Primary Diagnosis and Staging of Prostate Cancer

    Get PDF
    PET and PET/CT using [11C]- and [18F]-labelled choline derivates is increasingly being used for imaging of primary and recurrent prostate cancer. While PET and PET/CT with [11C]- and [18F]-labelled choline derivates in patients suffering from biochemical recurrence of prostate cancer has been examined in many studies that demonstrate an increasing importance, its role in the primary staging of prostate cancer is still a matter of debate

    Genitourinarni karcinomi: potencijalna uloga oslikavanja

    Get PDF
    Imaging is an essential part of the management of patients with genitourinary cancers. Imaging is necessary for diagnosis, treatment selection and planning, applying minimally invasive image-guided techniques, assessment of response to treatment, and post-treatment follow-up. With advances in technology, imaging now comprises far more than descriptive anatomy. In the next decade anatomic, functional and molecular imaging information will increasingly be combined to achieve more accurate disease characterization and better patient care. In this review we present standard as well as some new imaging methods used in patients with kidney and prostate cancer.Oslikavanje je sastavni dio liječenja bolesnika s genitourinarnim karcinomima. Oslikavanje je nužno za dijagnozu bolesti, izbor i planiranje terapije, te vođenje minimalno invazivnih tehnika liječenja, procjenu odgovora na terapiju, te praćenje bolesnika nakon liječenja. S napretkom tehnologije oslikavanje je danas puno više od deskriptivne anatomije. U sljedećoj dekadi kombinirat će se informacije anatomskog, funkcionalnog i molekularnog oslikavanja s ciljem postizanja što bolje karakterizacije bolesti, a samim time i boljeg liječenja bolesnika. U ovom članku prikazat ćemo standardne i neke nove metode oslikavanja koje se primjenjuju kod bolesnika s karcinomom bubrega i karcinomom prostat

    Non-Cancerous Abnormalities That Could Mimic Prostate Cancer Like Signal in Multi-Parametric MRI Images

    Get PDF
    Prostate Cancer (PCa) is the most common non-cutaneous cancer in North American men. Multi-parametric magnatic resonance imaging (mpMRI) has the potential to be used as a non-invasive procedure to predict locations and prognosis of PCa. This study aims to examine non-cancerous pathology lesions and normal histology that could mimic cancer in mpMRI signals. This study includes 19 radical prostatectomy specimens from the London Health Science Centre (LHSC) that were marked with 10 strand-shaped fiducials per specimen which were used as landmarks in histology processing and ex vivo MRI. Initial registration between fiducials on histology and MR images was performed followed by the development of an interactive digital technique for deformable registration of in vivo to ex vivo MRI with digital histopathology images. The relationship between MRI signals and non-cancerous abnormalities that could mimic PCa has not been tested previously in correlation with digital histopathology imaging. The unregistered mp-MRI images are contoured by 4 individual radiology observers according to the Prostate Imaging Reporting and Data System (PI-RADS). Analysis of the radiology data showed prostatic intraepithelial neoplasia (PIN), atrophy and benign prostatic hyperplasia (BPH) as main non-cancerous abnormalities responsible for cancer like signals on mpMRI. This study will help increase the accuracy of detecting PCa and play a role in the diagnosis and classification of confounders that mimic cancer in MR images

    Evaluation with diffusion weighted magnetic resonance imaging in staging and grading of urinary bladder cancer.

    Get PDF
    INTRODUCTION : Bladder cancer is a common genitourinary tract malignancy. Following prostatic adenocarcinoma, it represents the second most common tumour of urological malignancy in the world1. Urothelial tumours are cancers of the environment and advanced age. Bladder cancer is associated with old age and exposure to industrial toxins and smoking. It occurs most commonly in males than compared to female patients with ratio of 3:1 and is rare in the population less than 40 years of age. According to WHO 2004 classification, urothelial tumours are categorized to muscle non-invasive and muscle invasive, based on invasion of detrusor muscle. Eighty percent of urothelial cancers are non-muscle invasive in nature and present with various types of growth pattern. Muscle-invasive tumour is defined by high grade and cancer cells invading through the lamina propria into the deeper muscle layers. Histologically, urothelial carcinoma constitutes 90 percent of bladder cancers, five percent are squamous cell carcinoma and less than five percent are adenocarcinoma or other types of tumours. The management of bladder cancer varies according to muscle non-invasive and muscle invasive nature of the cancer. Muscle non-invasive tumours are managed with transurethral resection (TUR) and intravesical immunotherapy /chemotherapy. The treatment options for muscle invasive bladder cancer are radical cystectomy, radiation therapy, chemotherapy, or a combination. Thus it would be prudent to diagnose and differentiate between these two categories preoperatively by imaging techniques which helps in planning the treatment and in identifying the prognostic factors. AIM AND OBJECTIVES : To predict the pathological stage and grade of bladder cancer preoperatively by using Diffusion weighted Magnetic Resonance Imaging. To study the correlation of Diffusion Weighted MRI findings with clinical, radiological and pathological findings. PATIENTS AND METHODS : Inclusion Criteria : All new patients presented with total hematuria were evaluated initially with ultrasonography of abdomen and pelvis and diagnosed cases of Carcinoma bladder were included. Exclusion Criteria: 1. Patients with Previous TURBT, 2. Previously received intravesical therapy, systemic chemotherapy and external beam radiotherapy. METHOD OF STUDY : Informed consent obtained from all the patients after explaining details of the study. All details were recorded in a proforma as an inpatient procedure. Analysis was done with the collected details prospectively. All cases of carcinoma bladder was evaluated by clinical examination, renal function tests, urine cytology, imaging studies in the form of USG/CECT KUB. DW MRI of KUBU region was taken at the time of hospital admission. The TUR procedure was done within one week from the imaging procedure. CONCLUSION : DW MRI findings significantly correlate with histopathology in differentiating non muscle invasive bladder tumours from muscle invasive bladder tumours and also in local nodal staging. Grading of bladder tumour could be assessed with DW MRI as high grade tumours had significantly lower ADC values compared to low grade tumours. Hence in the preoperative evaluation of bladder cancers, DW MRI is a useful diagnostic imaging study both for grading and local staging of bladder cancers

    Potential of hybrid 18F-fluorocholine PET/MRI for prostate cancer imaging

    Get PDF
    Purpose: To report the first results of hybrid 18F-fluorocholine PET/MRI imaging for the detection of prostate cancer. Methods: This analysis included 26 consecutive patients scheduled for prostate PET/MRI before radical prostatectomy. The examinations were performed on a hybrid whole-body PET/MRI scanner. The MR acquisitions which included T2-weighted, diffusion-weighted and dynamic contrast-enhanced sequences were followed during the same session by whole-body PET scans. Parametric maps were constructed to measure normalized T2-weighted intensity (nT2), apparent diffusion coefficient (ADC), volume transfer constant (K trans), extravascular extracellular volume fraction (v e) and standardized uptake values (SUV). With pathology as the gold standard, ROC curves were calculated using logistic regression for each parameter and for the best combination with and without PET to obtain a MR model versus a PETMR model. Results: Of the 26 patients initially selected, 3 were excluded due to absence of an endorectal coil (2 patients) or prosthesis artefacts (1 patient). In the whole prostate, the area under the curve (AUC) for SUVmax, ADC, nT2, K trans and v e were 0.762, 0.756, 0.685, 0.611 and 0.529 with a best threshold at 3.044 for SUVmax and 1.075×10−3mm2/s for ADC. The anatomical distinction between the transition zone and the peripheral zone showed the potential of the adjunctive use of PET. In the peripheral zone, the AUC of 0.893 for the PETMR model was significantly greater (p = 0.0402) than the AUC of 0.84 for the MR model only. In the whole prostate, no relevant correlation was observed between ADC and SUVmax. The SUVmax was not affected by the Gleason score. Conclusion: The performance of a hybrid whole-body 18F-fluorocholine PET/MRI scan in the same session combined with a prostatic MR examination did not interfere with the diagnostic accuracy of the MR sequences. The registration of the PET data and the T2 anatomical MR sequence data allowed precise localization of hypermetabolic foci in the prostate. While in the transition zone the adenomatous hyperplasia interfered with cancer detection by PET, the quantitative analysis tool performed well for cancer detection in the peripheral zone

    Developing multiparametric and novel magnetic resonance imaging biomarkers for prostate cancer

    Get PDF
    Whilst biomarker research is gaining momentum within the cancer sciences, disappointingly few biomarkers are successfully translated into clinical practice, which is partly due to lack of rigorous methodology. In this thesis, I aim to systematically study several quantitative magnetic resonance imaging (MRI) biomarkers (QIBs), at various stages of biomarker development for use as tools in the assessment of local and metastatic prostate cancer according to clinical need. I initially focus on QIBs derived from conventional multiparametric (mp) prostate MRI sequences, namely T2 weighted (T2W), apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE). Firstly, by optimising analytical methods used throughout the thesis, deciding which approach is more reliable between single-slice region-of-interest vs. contouring the whole tumour volume using two different software packages. I then consider whether metric reproducibility can be improved by normalisation to different anatomical structures, and assess whether it is preferable to use statistics derived from imaging histograms rather than the current convention of using mean values. I combine multiple QIBs in a logistic regression model to predict a Gleason 4 component in known prostate cancer, which represents an unmet clinical need, as noninvasive tools to distinguish these more aggressive tumours do not currently exist. I subsequently ‘technically validate’ a novel microstructural diffusion-weighted MRI technique called VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours) to detect aggressive prostate cancer as part of a prospective cohort study. I assess the image quality, contrast-to-noise ratio, repeatability and performance of quantitative parametric VERDICT maps to discriminate between Gleason grades vs. the current best performing, but still imperfect tool of ADC. In the final two results chapters, motivated by the limited diagnostic accuracy of the prostate cancer staging modalities in current clinical use, I investigate the ability of mp whole-body (WB) MRI to stage aggressive cancer outside the prostate in patients with a high risk of metastases at primary diagnosis, and in biochemical failure following prostatectomy

    Quantitative PET-CT Perfusion Imaging of Prostate Cancer

    Get PDF
    Functional imaging of 18F-Fluorocholine PET holds promise in the detection of dominant prostatic lesions. Quantitative parameters from PET-CT Perfusion may be capable of measuring choline kinase activity, which could assist in identification of the dominant prostatic lesion for more accurate targeting of biopsies and radiation dose escalation. The objectives of this thesis are: 1) investigate the feasibility of using venous TACs in quantitative graphical analysis, and 2) develop and test a quantitative PET-CT Perfusion imaging technique that shows promise for identifying dominant prostatic lesions. Chapter 2 describes the effect of venous dispersion on distribution volume measurements with the Logan Plot. The dispersion of venous PET curves was simulated based on the arterio-venous transit time spectrum measured in a perfusion CT study of the human forearm. The analysis showed good agreement between distribution volume measurements produced by the arterial and venous TACs. Chapter 3 details the mathematical implementation of a linearized solution of the 3-Compartment kinetic model for hybrid PET-CT Perfusion imaging. A noise simulation determined the effect of incorporating CT perfusion parameters into the PET model on the accuracy and variability of measurements of the choline kinase activity. Results indicated that inclusion of CT perfusion parameters known a priori can significantly improve the accuracy and variability of imaging parameters measured with PET. Chapter 4 presents the implementation of PET-CT Perfusion imaging in a xenograft mouse model of human prostate cancer. Image-derived arterial TACs from the left ventricle were corrected for partial volume and spillover effects and validated by comparing to blood sampled curves. The PET-CT Perfusion imaging technique produced parametric maps of the choline kinase activity, k3. The results showed that the partial volume and spillover corrected arterial TACs agreed well with the blood sampled curves, and that k3max was significantly correlated with tumor volume, while SUV was not. In summary, this thesis establishes a solid foundation for future clinical research into 18F-fluorocholine PET imaging for the identification of dominant prostatic lesions. Quantitative PET-CT Perfusion imaging shows promise for assisting targeting of biopsy and radiation dose escalation of prostate cancer

    Diseases of the Abdomen and Pelvis 2018-2021: Diagnostic Imaging - IDKD Book

    Get PDF
    Gastrointestinal disease; PET/CT; Radiology; X-ray; IDKD; Davo

    Deep learning applications in the prostate cancer diagnostic pathway

    Get PDF
    Prostate cancer (PCa) is the second most frequently diagnosed cancer in men worldwide and the fifth leading cause of cancer death in men, with an estimated 1.4 million new cases in 2020 and 375,000 deaths. The risk factors most strongly associated to PCa are advancing age, family history, race, and mutations of the BRCA genes. Since the aforementioned risk factors are not preventable, early and accurate diagnoses are a key objective of the PCa diagnostic pathway. In the UK, clinical guidelines recommend multiparametric magnetic resonance imaging (mpMRI) of the prostate for use by radiologists to detect, score, and stage lesions that may correspond to clinically significant PCa (CSPCa), prior to confirmatory biopsy and histopathological grading. Computer-aided diagnosis (CAD) of PCa using artificial intelligence algorithms holds a currently unrealized potential to improve upon the diagnostic accuracy achievable by radiologist assessment of mpMRI, improve the reporting consistency between radiologists, and reduce reporting time. In this thesis, we build and evaluate deep learning-based CAD systems for the PCa diagnostic pathway, which address gaps identified in the literature. First, we introduce a novel patient-level classification framework, PCF, which uses a stacked ensemble of convolutional neural networks (CNNs) and support vector machines (SVMs) to assign a probability of having CSPCa to patients, using mpMRI and clinical features. Second, we introduce AutoProstate, a deep-learning powered framework for automated PCa assessment and reporting; AutoProstate utilizes biparametric MRI and clinical data to populate an automatic diagnostic report containing segmentations of the whole prostate, prostatic zones, and candidate CSPCa lesions, as well as several derived characteristics that are clinically valuable. Finally, as automatic segmentation algorithms have not yet reached the desired robustness for clinical use, we introduce interactive click-based segmentation applications for the whole prostate and prostatic lesions, with potential uses in diagnosis, active surveillance progression monitoring, and treatment planning
    corecore