Academic literature on the topic 'Multiparametric Magnetic Resonance Imaging (mp-MRI)'

AbstractMultiparametric magnetic resonance imaging (mp-MRI) has emerged as an important tool for the detection and characterization of prostatic lesions. It now plays a quintessential role in the surveillance, diagnosis, and staging of prostate cancer (PCa), as well as for the detection of local recurrence. As reliance on serum prostate-specific antigen has declined in the recent times, mp-MRI has emerged as the go-to tool for urologists all over the world. Hence, for the clinician, it has become necessary to be well versed with the technique, image interpretation, and fallacies of mp-MRI. Since mp-MRI has the advantage of better contrast resolution, combining PSMA PET (prostate-specific membrane antigen-positron emission tomography) with MRI could provide additional functional information. However, due to the absence of enough evidence supporting its routine use, mp-MRI still has the unsurpassed role in the initial diagnosis and local staging of PCa.

AbstractImage-guided prostate biopsies are changing the outlook of prostate cancer (PCa) diagnosis, with the degree of suspicion on multiparametric magnetic resonance imaging (mp-MRI) being a strong predictor of targeted biopsy outcome. It is important not only to detect these suspicious lesions but also to be aware of the potential pitfalls in mp-MRI prostate imaging. The aim of this pictorial essay is to show a wide spectrum of representative cases, which are frequently misdiagnosed as PIRADS ⅘ while reporting mp-MRI of the prostate. We provide some valuable recommendations to avoid these fallacies and improve mp-MRI of prostate evaluation.

Multiparametric magnetic resonance imaging (MP-MRI) has emerged as a promising method for the detection of prostate cancer. The functional MRI components of the MP-MRI consist of the diffusion weighted MRI, dynamic contrast enhanced MRI, and magnetic resonance spectroscopic imaging. The purpose of this paper is to review the existing literature about the use of functional MRI in prostate cancer detection.

Background and aims. Multiparametric-magnetic resonance imaging (mp-MRI) is the main imaging modality used for prostate cancer detection. The aim of this study is to evaluate the diagnostic performance of mp-MRI at 1.5-Tesla (1.5-T) for the detection of clinically significant prostate cancer.Methods. In this ethical board approved prospective study, 39 patients with suspected prostate cancer were included. Patients with a history of positive prostate biopsy and patients treated for prostate cancer were excluded. All patients were examined at 1.5-T MRI, before standard transrectal ultrasonography–guided biopsy.Results. The overall sensitivity, specificity, positive predictive value and negative predictive value for mp-MRI were 100%, 73.68%, 80% and 100%, respectively.Conclusion. Our results showed that 1.5 T mp-MRI has a high sensitivity for detection of clinically significant prostate cancer and high negative predictive value in order to rule out significant disease.

The increased use of axial imaging in various fields of medicine has led to an increased frequency of incidental findings, specifically incidental cancer lesions. Hence, as the use of multiparametric magnetic resonance imaging (MP-MRI) for prostate cancer detection, staging, and management becomes more widespread, the potential for additional incidental findings in the pelvis increases. Herein, we report the case of a man on active surveillance for low-grade, early-staged prostate cancer who underwent MP-MRI and was incidentally found to have a high-grade bladder cancer lesion.

Abstract Objectives To assess the ability of multiparametric MRI (mp-MRI) of the prostate to exclude prostate cancer (PCa) progression during monitoring patients on active surveillance (AS). Methods One hundred forty-seven consecutive patients on AS with mp-MRI (T2WI, DWI, DCE-MRI) at 3T were initially enrolled. Fifty-five received follow-up mp-MRI after a minimum interval of 12 months and subsequent targeted MR/US fusion-guided biopsy (FUS-GB) plus concurrent systematic transrectal ultrasound-guided (TRUS-GB) biopsy as reference standard. Primary endpoint was the negative predictive value (NPV) of the follow-up mp-MRI to exclude histopathologic tumor progression using PRECISE recommendations. Secondary endpoints were the positive predictive value (PPV), sensitivity, specificity, Gleason score (GS) upgrades, and comparison of biopsy method. Results Of 55 patients, 29 (53%) had a GS upgrade on re-biopsy. All 29 patients showed a tumor progression on follow-up mp-MRI. Fifteen of 55 patients (27%) displayed signs of tumor progression, but had stable GS on re-biopsy. None of the 11 patients (20%) without signs of progression on follow-up mp-MRI had a GS upgrade on re-biopsy. The NPV was 100%, PPV was 66%, sensitivity was 100%, and specificity 42%. FUS-GB resulted in GS upgrade significantly more often (n = 28; 51%) compared with TRUS-GB (n = 12; 22%; p < 0.001). Conclusions (Follow-up) Mp-MRI can reliably exclude PCa progression in patients on AS. Standard serial re-biopsies might be waived if follow-up mp-MRIs are stable. Over 60% of patients with signs of tumor progression on mp-MRI during AS had a GS upgrade on re-biopsy. Targeted re-biopsies should be performed if cancer progression or higher-grade PCa is suspected on mp-MRI. Key Points • None of the patients with unsuspicious mp-MRI had a GS upgrade in re-biopsy and mp-MRI might replace serial biopsies in these cases • More than 60% of patients with mp-MRI signs of tumor progression had subsequent Gleason score (GS) upgrades • Targeted re-biopsies should be performed in case of higher GS cancer suspicion on mp-MRI

Background: Traditionally, the diagnosis of prostate cancer was based on increased prostate-specific antigen level or an abnormal digital rectal examination and confirmed histologically following biopsy. Consequently, a proportion of men without cancer or with clinically insignificant disease undergo unwarranted prostate biopsies and experience resultant complications. Pre-biopsy multiparametric magnetic resonance imaging (MP-MRI) is vital in determining those with clinically significant cancer who need biopsy and those with a negative MRI who can safely avoid unnecessary biopsy. Methods: The diagnostic accuracy of MP-MRI using transrectal ultrasound-guided biopsy as the reference test was established for 133 men who had undergone MRI and biopsy. The MRI images were reviewed and reported by two independent consultant radiologists. Clinically significant cancer was defined as Prostate Imaging Reporting and Data System score ≥3 on multiparametric MRI and Gleason score ≥3 + 4 (grade group ≥2) on histology. Results: MP-MRI of the prostate was found to have 92% sensitivity, 47.8% specificity, 86.8% negative predictive value (NPV) and 62% positive predictive value for the diagnosis of prostate cancer. Conclusion: MP-MRI has a high sensitivity and a high NPV, validating its use in pre-biopsy evaluation of men at risk of prostate cancer to safely avoid unnecessary prostate biopsy and to guide biopsy of suspicious lesions.

BACKGROUND: An accurate diagnosis is essential for the effective treatment of prostate cancer (PCa) and for the patients’ well-being. AIM: Thе main purpose of this study was to assess the utility of multiparametric magnetic resonance imaging (mp-MRI) for initial detection of PCa among the Bulgarian population of men with prostate diseases. MATERIALS AND METHODS: Fifty-three patients, aged 44 to 82 years, were evaluated for clinically significant PCa. Assessment methods included prostate-specific antigen (PSA) serum levels, transrectal ultrasonography (TRUS), GE Discovery 3T MRI, and 12-core TRUS biopsy. RESULTS: mp-MRI showed 83.20% concordance with TRUS biopsy: sensitivity of 91.43% (76.90–98.20), specificity of 75.00% (34.90–96.80), positive predictive values 94.10% (82.80–98.20) and negative predictive values 66.70% (38.70–86.40). Of the patients classified in prostate imaging–reporting and data system (PI-RADS) levels 4 and 5, 94.12% had positive TRUS biopsy, as well as 44.40% of PI-RADS had level 3. Irrespective of the patients’ age and PSA, PI-RADS was found to be a significant predictor of a positive TRUS biopsy (p = 0.009). PSA serum levels showed a low concordance with TRUS biopsy (area under the curve = 0.539; 95% confidence interval [CI]: 0.363–0.712) and a low, although significant, correlation with PI-RADS (rs = 0.416; 95% CI: 0.164–0.617). CONCLUSION: According to our findings, mp-MRI and TRUS biopsy have a high level of concordance for the initial detection of PCa. The incorporation of mp-MRI into the diagnostic pathway for PCa can significantly reduce the number of incorrect diagnoses based on PSA serum levels and/or suspicious physical and digital examinations.

Objective: We determined the sensitivity and specificity of multiparametric magnetic resonance imaging (MP-MRI) in detection of locally recurrent prostate cancer and extra prostatic extension in the post-radical radiotherapy setting. Histopathological reference standard was whole-mount prostatectomy specimens. We also assessed for any added value of the dynamic contrast enhancement (DCE) sequence in detection and staging of local recurrence. Methods: This was a single centre retrospective study. Participants were selected from a database of males treated with salvage prostatectomy for locally recurrent prostate cancer following radiotherapy. All underwent pre-operative prostate-specific antigen assay, positron emission tomography CT, MP-MRI and transperineal template prostate mapping biopsy prior to salvage prostatectomy. MP-MRI performance was assessed using both Prostate Imaging-Reporting and Data System v. 2 and a modified scoring system for the post-treatment setting. Results: 24 patients were enrolled. Using Prostate Imaging-Reporting and Data System v. 2, sensitivity, specificity, positive predictive value and negative predictive value was 64%, 94%, 98% and 36%. MP-MRI under staged recurrent cancer in 63%. A modified scoring system in which DCE was used as a co-dominant sequence resulted in improved diagnostic sensitivity (61%–76%) following subgroup analysis. Conclusion: Our results show MP-MRI has moderate sensitivity (64%) and high specificity (94%) in detecting radio-recurrent intraprostatic disease, though disease tends to be under quantified and under staged. Greater emphasis on dynamic contrast images in overall scoring can improve diagnostic sensitivity. Advances in knowledge: MP-MRI tends to under quantify and under stage radio-recurrent prostate cancer. DCE has a potentially augmented role in detecting recurrent tumour compared with the de novo setting. This has relevance in the event of any future modified MP-MRI scoring system for the irradiated gland.

Objectives: To compare the cost-effectiveness of a short biparametric MRI (BP-MRI) with that of contrast-enhanced multiparametric MRI (MP-MRI) for the detection of prostate cancer in men with elevated prostatespecific antigen (PSA) levels. Materials and methods: We compared two diagnostic procedures for detection of prostate cancer (Pca), BP-MRI and MP-MRI, in terms of quality-adjusted life years (QALY), incremental costeffectiveness ratio (ICER) and net monetary benefit (NMB) for a hypothetical cohort of 10,000 patients. We compared two scenarios in which different protocols would be used for the early diagnosis of prostate cancer in relation to PSA values. Scenario 1. BP-MRI/MP-MRI yearly if > 3.0 ng/ml, every 2 years otherwise; Scenario 2. BP-MRI/MP-MRI yearly with age-dependent threshold 3.5 ng/ml (50-59 years), 4.5 ng/ml (60-69 years), 6.5 ng/ml (70-79 years). Results: BP-MRI was more effective than the comparator in terms of cost (160.10 € vs 249.99€) QALYs (a mean of 9.12 vs 8.46), ICER (a mean of 232.45) and NMB (a mean of 273.439 vs 251.863). BP-MRI was dominant, being more effective and less expensive, with a lower social cost. Scenario 2 was more cost-effective compared to scenario 1. Conclusions: Our results confirmed the hypothesis that a short bi-parametric MRI protocol represents a cost-efficient procedure, optimizing resources in a policy perspective.

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck cancer ranked as the 5th most common in Hong Kong. We aimed to study the role of dynamic contrast-enhanced MRI (DCE-MRI) and dynamic 2-deoxy-2-[fluorine-18]fluoro -D-glucose positron emission tomography (FDG-PET) for characterizing NPC tumors in newly-diagnosed patients, and to quantitatively evaluate the intratumoral heterogeneity of NPC. In Chapter 2 we employed semi-quantitative analysis of DCE-MRI to study the dynamic enhancement pattern by analyzing the time-intensity curves in 25 NPC patients. Our findings suggested that high blood flow caused a high initial intensity enhancement rate (ER), and that neovasculature due to tumor angiogenesis in tumors of larger volume or higher T-stage caused more accumulation of contrast agent which can be detected by DCE-MRI. PET and semi-quantitative DCE-MRI parameters were not correlated and may reflect different physiological/molecular processes in the microenvironment of NPC tumor. However the major limitation of semi-quantitative analysis was that the physiological correlates of these parameters were unclear. In Chapter 3 we applied quantitative analysis of DCE-MRI to study the permeability and perfusion characteristics in the same cohort as in Chapter 2. Our findings implied that the permeability may be high compared to blood flow in NPC tumor. We also observed significant correlations between iAUC (the initial area under the time-intensity curve) by semi-quantitative analysis and ve (the volume fraction of extravascular extracellular space) by quantitative analysis, and between the two rate constants (kep’s) from these two methods, which showed that semi-quantitative analysis was a feasible alternative in reflecting the physiological characteristics of NPC. However, we did not observe any significant correlation between PET and DCE-MRI quantitative parameters, also suggesting that PET and DCE-MRI reflected different physiological information in NPC. In Chapter 4 we applied dynamic PET scan to study the glucose metabolism in 18 NPC tumors (16 included in DCE-MRI cohort). Our findings showed that the overall FDG uptake was mainly composed of the FDG in tissue compartment (Ki), which was governed by the phosphorylation (k3) but not the transport of FDG (K1). This finding may further indicate a potential role of the phosphorylation rate k3 in NPC. Dynamic PET parameters did not correlate with DCE-MRI, indicating that the two modalities reflect different molecular information in NPC. In Chapter 5, intratumoral heterogeneity in NPC tumors of 40 patients was studied using 18F-FDG PET scan. Our findings showed that as tumors grew to a larger volume and higher T-stage, they showed more heterogeneous glucose metabolism. It was found that more heterogeneous tumor was associated with worse disease-free survival, indicating that tumor metabolic heterogeneity may play an important role for NPC patient prognosis. To summarize, these results showed that DCE-MRI and dynamic PET improved our understanding about the physiological/molecular process of NPC, and, these two modalities reflected different physiological information in the microenvironment of NPC tumors. This indicated that the relationship between supply of nutrients such as glucose and blood flow/permeability is complex and not directly related. Moreover, intratumoral heterogeneity by PET scan was also of importance in prognostication.
published_or_final_version
Diagnostic Radiology
Doctoral
Doctor of Philosophy

A better understanding of tumour heterogeneity is central for accurate diagnosis, targeted therapy and personalised treatment of glioblastoma patients. This thesis aims to investigate whether pre-operative multi-parametric magnetic resonance imaging (MRI) can provide a useful tool for evaluating inter-tumoural and intra-tumoural heterogeneity of glioblastoma. For this purpose, we explored: 1) the utilities of habitat imaging in combining multi-parametric MRI for identifying invasive sub-regions (I & II); 2) the significance of integrating multi-parametric MRI, and extracting modality inter-dependence for patient stratification (III & IV); 3) the value of advanced physiological MRI and radiomics approach in predicting epigenetic phenotypes (V). The following observations were made: I. Using a joint histogram analysis method, habitats with different diffusivity patterns were identified. A non-enhancing sub-region with decreased isotropic diffusion and increased anisotropic diffusion was associated with progression-free survival (PFS, hazard ratio [HR] = 1.08, P < 0.001) and overall survival (OS, HR = 1.36, P < 0.001) in multivariate models. II. Using a thresholding method, two low perfusion compartments were identified, which displayed hypoxic and pro-inflammatory microenvironment. Higher lactate in the low perfusion compartment with restricted diffusion was associated with a worse survival (PFS: HR = 2.995, P = 0.047; OS: HR = 4.974, P = 0.005). III. Using an unsupervised multi-view feature selection and late integration method, two patient subgroups were identified, which demonstrated distinct OS (P = 0.007) and PFS (P < 0.001). Features selected by this approach showed significantly incremental prognostic value for 12-month OS (P = 0.049) and PFS (P = 0.022) than clinical factors. IV. Using a method of unsupervised clustering via copula transform and discrete feature extraction, three patient subgroups were identified. The subtype demonstrating high inter-dependency of diffusion and perfusion displayed higher lactate than the other two subtypes (P = 0.016 and P = 0.044, respectively). Both subtypes of low and high inter-dependency showed worse PFS compared to the intermediate subtype (P = 0.046 and P = 0.009, respectively). V. Using a radiomics approach, advanced physiological images showed better performance than structural images for predicting O6-methylguanine-DNA methyltransferase (MGMT) methylation status. For predicting 12-month PFS, the model of radiomic features and clinical factors outperformed the model of MGMT methylation and clinical factors (P = 0.010). In summary, pre-operative multi-parametric MRI shows potential for the non-invasive evaluation of glioblastoma heterogeneity, which could provide crucial information for patient care.

Dissertação de Mestrado Integrado em Medicina Veterinária
Objective: To investigate the effect of 0.2 and 0.3 mg/kg of intravenous (IV) butorphanol as pre-medication in client owned dogs with suspected intracranial pathology undergoing brain magnetic resonance imaging (MRI). Study design: prospective, randomized, blinded, clinical trial. Animals: Thirty-two client-owned dogs with suspected intracranial pathology, 17 males, 15 females. Methods: Each dog was randomly assigned to receive IV either 0.2 mg/kg (group L) or 0.3 mg/kg (group H) of butorphanol 10 to 15 minutes prior to general anesthesia (GA) induction. Following tracheal intubation, subjects were mechanically ventilated to maintain normocapnia (35-45 mmHg FE’CO2) and GA was maintained with isoflurane in oxygen and air. Scores for mentation, neurological status and sedation were recorded prior to GA; quality of induction, ease of intubation and recovery quality scores were assigned to each subject. Heart rate end expiratory fraction or pressure of expired and inspired gases, arterial blood pressure were recorded and compared between groups. Pulse oximetry, and body temperature were recorded at beginning of the procedure. Once the administration of isoflurane was discontinued, time to tracheal extubation, to first head lift and time to standing were recorded and recovery score was obtained. Results: No differences were observed regarding demographic data and ASA status. Mentation and neurological status were similar between groups. Sedation score was different between groups, with higher sedation in group H (p=0.017). Propofol induction dose was similar between groups. Monitored physiologic variables were not significantly different. Recovery times were similar in both groups. No perioperative complications were observed. Conclusion: The administration of 0.3 mg/kg IV butorphanol as pre-medication promoted higher sedation when compared with 0.2 mg/kg but does not confer any other clinical advantages or sparing effect on propofol induction dose in dogs with suspected intracranial pathology undergoing brain MRI.
RESUMO - AVALIAÇÃO MULTIPARAMÉTRICA DOS EFEITOS DE DUAS DOSES DIFERENTES DE BUTORFANOL EM CÃES SUBMETIDOS A EXAME IMAGIOLÓGICO DE RESSONÂNCIA MAGNÉTICA - Objectivo: Investigar o efeito de duas doses de butorfanol, 0.2 e 0.3 mg/kg, administradas via endovenosa (EV) como pre-medicação para cães com suspeita de patologia intracraniana, submetidos a exame imagiológico através de ressonância magnética (MRI). Desenho do estudo: prospetivo, aleatório, cego, estudo clínico. Animais: trinta e dois cães com cuidadores, 17 machos, 15 fêmeas. Métodos: para cada cão, de forma aleatória, foi designado para receber 0.2 mg/kg (grupo L) ou 0.3 mg/kg (grupo h) de butorfanol EV, 10 a 15 minutos antes de serem induzidos em anestesia geral (GA). Após intubação endotraqueal, os animais foram ventilados mecanicamente, de forma a manterem-se em normocapnia (35-45 mmHg FE’CO2), com uma mistura de isoflurano, oxigénio e ar. Antes de serem induzidos em anestesia geral, os cães foram classificados em relação ao estado de alerta, exame neurológico e sedação; qualidade de indução, facilidade de intubação, qualidade da recuperação da anestesia geral também foram classificados. Foram registados e comparados entre grupos os valores de frequência cardíaca, fração expirada de gases e valores de pressão arterial. Saturação de oxigénio na hemoglobina e temperatura foram medidas ao início da anestesia geral. Quando a administração de isoflurano foi interrompida, tempo até extubação, tempo até erguer a cabeça e tempo até estação foram registados. Resultados: não foram detetadas diferenças entre grupos em relação aos dados demográficos e classificação ASA. Classificação de sedação foi superior no grupo H comparado com o grupo L (p=0.017). Dose de indução de anestesia geral com propofol não diferiu entre grupos. Não foram detetadas diferenças significativas nas constantes fisiológicas medidas durante a anestesia geral. Tempos de recuperação foram similares entre grupos. Não foram registadas complicações peri-anestésicas em nenhum animal. Conclusão: A administração de 0.3 mg/kg de butorfanol EV como pré-medicação promoveu um maior grau de sedação quando comparada com a dose de 0.2 mg/kg em cães com suspeita de patologia intra-craniana submetidos para ressonância magnética.
N/A

Objectives To test upgrading rates in patients on Active Surveillance (AS) for prostate cancer (PCa) after serial multiparametric magnetic resonance imaging (mpMRI) scans. Materials and methods Retrospective analysis of 558 patients. Five different criteria of mpMRI progression were used: 1) PI-RADS score increase; 2) lesion size increase; 3) EPE score increase; 4) overall mpMRI progression; 5) number of criteria for mpMRI progression (0 vs. 1 vs. 2-3). Moreover, two definitions of PCa upgrading were evaluated:1) ISUP GG≥2 with >10% of pattern 4; 2) ISUP GG≥3. The estimated annual percent changes (EAPC) methodology depicted temporal trends of mpMRI progression criteria. Sensitivity, specificity, positive predictive (PPV) and negative predictive value (NPV) of mpMRI progression criteria were analysed. Multivariable logistic regression models tested PCa upgrading rates. Results Lower rates over time of all mpMRI progression criteria were observed. The NPV of serial mpMRIs spans from 90.5 to 93.5% (ISUP GG≥2 with >10% of pattern 4 PCa upgrading) and from 98 to 99% (ISUP GG≥3 PCa upgrading), according to the different mpMRI progression criteria. A PSA-D cut-off of 0.15 ng/ml/ml sub stratified those patients who could skip a prostate biopsy. In multivariable logistic regression models testing PCa upgrading rates, all five mentioned mpMRI progression criteria achieved independent predictor status. Conclusions: During AS, approximately 27% of patients experience mpMRI progression at first repeated scan. However, the rates of mpMRI progression decrease over time at subsequent mpMRIs. Patients with stable mpMRI findings and with PSA-D<0.15 ng/ml/ml could safely skip surveillance biopsies. Conversely, patients who experience mpMRI progression should undergo a prostate biopsy.

Objectives: The study aimed to evaluate the prediction of Prostate Imaging Reporting and Data System (PI-RADS) with respect to the prostate cancer (PCa) detection rate and tumor aggressiveness in magnetic resonance imaging (MRI)/ultrasound-fusion-biopsy (fusPbx) and in systematic biopsy (sysPbx). Materials and Methods: Six hundred and twenty five patients undergoing multiparametric MRI were investigated. MRI findings were classified using PI-RADS v1 or v2. All patients underwent fusPbx combined with sysPbx (comPbx). The lesion with the highest PI-RADS was defined as maximum PI-RADS (maxPI-RADS). Gleason Score ≥ 7 (3 + 4) was defined as significant PCa. Results: The overall PCa detection rate was 51% ( n = 321; 39% significant PCa). The detection rate was 43% in fusPbx ( n = 267; 34% significant PCa) and 36% in sysPbx ( n = 223; 27% significant PCa). Nine percentage of significant PCa were detected by sysPbx alone. A total of 1,162 lesions were investigated. The detection rate of significant PCa in lesions with PI-RADS 2, 3, 4, and 5 were 9% (18/206), 12% (56/450), 27% (98/358), and 61% (90/148) respectively. maxPI-RADS ≥ 4 was the strongest predictor for the detection of significant PCa in comPbx (OR 2.77; 95% CI 1.81–4.24; p < 0.005). Conclusions: maxPI-RADS is the strongest predictor for the detection of significant PCa in comPbx. Due to a high detection rate of additional significant PCa in sysPbx, fusPbx should still be combined with sysPbx.

L'hétérogénéité tumorale est un facteur important de progression et de résistance au traitement. L'imagerie multiparamétrique TEP-IRM offre des opportunités uniques de caractérisation biologique cellulaire, mais n’a jamais été évalué à l’échelle régionale intra-tumorale dans le cancer du poumon non à petites cellules (CBNPC), première cause de décès oncologique. Une approche multiparamétrique dynamique simultanée TEP-IRM au 18F-FDG a été développée en ce sens. Cette approche a nécessité l’implémentation « maison » de la méthode de référence de quantification TEP du métabolisme glucidique (modèle tri-compartimental de Sokoloff); le développement d’une méthode de correction inédite des distorsions géométriques en imagerie de diffusion, validée sur fantôme et testée cliniquement ; la validation sur fantôme de méthodes d’IRM quantitative (relaxométrie T1/T2), également testées cliniquement; et l’implémentation « maison » du modèle compartimental de Tofts (version étendue) pour l’évaluation de la vascularisation tumorale en IRM dynamique de perfusion. Les résultats de nos travaux expérimentaux effectués à l’échelle intra-tumorale régionale illustrent l’hétérogénéité des rapports entre métabolisme glucidique et vascularisation dans le CBNPC, deux caractéristiques biologiques fondamentales de progression tumorale, et montrent qu’un partitionnement tumoral non supervisé par modèle de mélange gaussien, intégrant l’ensemble des biomarqueurs TEP-IRM de ce projet, individualise 3 types de supervoxels, dont la signature biologique peut être prédite avec une exactitude de 97% par 4 biomarqueurs TEP-IRM dominants, révélés par méthodes métaheuristiques d'apprentissage machine
Tumor heterogeneity is an important factor of progression and resistance to treatment. Multiparametric PET-MRI imaging offers unique opportunities to characterize biological cellular processes, but has never been evaluated at the regional level in Non-Small Cell Lung Cancer (NSCLC), the leading cause of oncological death. A simultaneous dynamic multiparametric 18F-FDG PET-MRI approach has been developed to this end. This approach required the “in-house” implementation of the reference absolute PET quantitative method of glucose metabolism (Sokoloff's tri-compartmental model); the development of a method for correcting geometric distortions in diffusion weighted imaging, validated on phantom and clinically tested; the phantom validation of quantitative MRI methods (T1/T2 relaxometry), also clinically tested; and the "in-house" implementation of the Tofts compartmental model (extended version) for the evaluation of tumor vascularization by dynamic perfusion MRI. The results of our work, performed at the regional intra-tumor level, illustrate the heterogeneity of the regional interlinks between glucose metabolism and vascularization in NSCLC, two fundamental biological hallmarks of tumor progression, and show that an unsupervised tumor partitioning by Gaussian mixture model, integrating all the PET-MRI biomarkers of this project, individualizes 3 types of supervoxels, whose biological signature can be predicted with 97% accuracy by 4 dominant PET-MRI biomarkers, revealed by metaheuristic machine learning methods

Nous avons développé un système de diagnostic assisté par ordinateur (CAD) basé sur des régions d'intérêt pour caractériser le cancer de la prostate avec un grade de l'International Society of Urological Pathology (ISUP) ≥2 lors d'une IRM multiparamétrique (IRM-mp). Les paramètres de l'image provenant de 2 jeux de données multi-constructeurs de 265 IRM pré-prostatectomie et 112 IRM pré-biopsie ont été combinés en utilisant la régression logistique. Les meilleurs modèles contenaient le 2e percentile d’ADC (ADC2) et le taux de rehaussement normalisé (WI) dans la zone périphérique (ZP) et le 25e percentile d'ADC (ADC25) dans la zone de transition (ZT). Ils ont été associés dans le système CAD. Le CAD a été évalué rétrospectivement sur 2 jeux de données multi-constructeurs contenant respectivement 158 et 105 IRM pré-biopsie de notre institution (test interne) et d'une autre institution (test externe). Deux radiologues ont indépendamment décrit les lésions ciblées par la biopsie. Le score PI-RADSv2 (Prostate Imaging-Reporting and Data System version 2) attribué prospectivement lors de la biopsie et le score CAD ont été comparés aux résultats de la biopsie. A l’échelle des patients, les aires sous la courbe Receiver Operating Characteristic (AUC) du score PI-RADSv2 étaient de 82% (IC 95% : 74-87) et 85% (IC 95% : 79-91) dans les jeux de données de test interne et externe respectivement. Pour les deux radiologues, le score CAD avait des AUC similaires dans les jeux de données interne (82%, IC 95% : 76-89, p=1 ; 84%, IC 95% : 78-91, p=1) et externe (82%, IC 95% : 76-89, p=0.82 ; 86%, IC 95% : 79-93, p=1). La combinaison du PI-RADSv2 et du CAD aurait pu éviter 41 à 52% des biopsies tout en manquant 6 à 10% des cancers ISUP≥2. Le système CAD a confirmé sa robustesse dans une étude multicentrique impliquant 22 scanners et des protocoles d'imagerie très hétérogènes. Dans l'analyse par patient, le CAD et le PI-RADSv2 avaient des performances similaires en termes d’AUC (76%, IC 95% : 70-82 contre 79%, IC 95% : 73-86 ; p=0.34) et de sensibilité (86%, IC 95% : 76-96 contre 89%, IC 95% : 79-98 pour le PI-RADSv2≥4). La spécificité du CAD (62%, IC 95% : 53-70 contre 49% ; IC 95% : 39-59 pour le PI-RADSv2≥4) permettait une complémentarité avec le score PI-RADSv2 pour potentiellement éviter 50% des biopsies, tout en manquant 13% des cancers ISUP≥2. Ces résultats étaient similaires à ceux rapportés dans les cohortes de test issues d’un unique centre et ont ouvert la voie à de nouvelles applications du CAD. Le CAD a d’abord permis une bonne discrimination des cancers ISUP≥2 chez des patients placés en surveillance active. Son AUC (80% ; IC 95% : 74-86) était similaire à celle du score PI-RADSv2 attribué prospectivement par des uro-radiologues spécialisés (81%, IC 95% : 74-87 ; p=0.96). Le CAD était plus spécifique que les scores PI-RADS≥3 (p<0.001) et PI-RADS≥4 (p<0.001). Il pourrait offrir une solution pour sélectionner les patients pouvant éviter sans risque une biopsie de confirmation ou de suivi dans le cadre de leur surveillance active (25%). Il manquerait alors 5% des cancers ISUP≥2. Le CAD a enfin été confronté aux IRM-mp pré-prostatectomie de 56 patients japonais, issus d’une population qui est géographiquement éloignée de sa population d’entraînement et qui intéresse de par ses faibles taux d’incidence et de mortalité du cancer de la prostate. Son AUC était alors similaire au score PI-RADSv2 attribué par un radiologue expérimenté dans la ZP (80%, IC 95% : 71-90 contre 80%, IC 95% : 71-89 ; p=0.886) et dans la ZT (79%, IC 95% : 66-90 contre 93%, 95%CI : 82-96 ; p=0.051). Ces résultats prometteurs et robustes sur des jeux de données hétérogènes suggèrent que le CAD pourrait être utilisée dans la routine clinique quotidienne comme un second lecteur pour aider à sélectionner les patients pouvant éviter la biopsie en toute sécurité. Ce CAD pourrait aider les lecteurs moins expérimentés à caractériser les lésions de la prostate
We developed a region of interest-based (ROIs) computer-aided diagnosis system (CAD) to characterize International Society of Urological Pathology grade (ISUP) ≥2 prostate cancers at multiparametric MRI (mp-MRI). Image parameters from two multi-vendor datasets of 265 pre-prostatectomy and 112 pre-biopsy MRIs were combined using logistic regression. The best models used the ADC 2nd percentile (ADC2) and normalized wash-in rate (WI) in the peripheral zone (PZ) and the ADC 25th percentile (ADC25) in the transition zone (TZ). They were combined in the CAD system. The CAD was retrospectively assessed on two multi-vendor datasets containing respectively 158 and 105 pre-biopsy MRIs from our institution (internal test dataset) and another institution (external test dataset). Two radiologists independently outlined lesions targeted at biopsy. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) score prospectively assigned at biopsy and the CAD score were compared to biopsy findings. At patient level, the areas under the Receiver Operating Characteristic curve (AUC) of the PI-RADSv2 score were 82% (95% CI: 74-87) and 85% (95% CI: 79-91) in the internal and external test datasets respectively. For both radiologists, the CAD score had similar AUC results in the internal (82%, 95% CI: 76-89, p=1; 84%, 95% CI: 78-91, p=1) and external (82%, 95% CI: 76-89, p=0.82; 86%, 95% CI: 79-93, p=1) test datasets. Combining PI-RADSv2 and CAD findings could have avoided 41-52% of biopsies while missing 6-10% of ISUP≥2 cancers. The CAD system confirmed its robustness showing good discrimination of ISUP ≥2 cancers in a multicentric study involving 22 different scanners with highly heterogeneous image protocols. In per patient analysis, the CAD and the PI-RADSv2 had similar AUC values (76%, 95% CI: 70-82 vs 79%, 95% CI: 73-86; p=0.34) and sensitivities (86%, 95% CI: 76-96 vs 89%, 95% CI: 79-98 for PI-RADSv2 ≥4). The specificity of the CAD (62%, 95% CI: 53-70 vs 49%, 95% CI: 39-59 for PI-RADSv2 ≥4) could be used to complement the PI-RADSv2 score and potentially avoid 50% of biopsies, while missing 13% of ISUP ≥2 cancers. These findings were very similar to those reported in the single center test cohorts. Given its robustness, the CAD could then be exploited in more specific applications. The CAD first provided good discrimination of ISUP ≥2 cancers in patients under Active Surveillance. Its AUC (80%, 95% CI: 74-86) was similar to that of the PI-RADS score prospectively assigned by specialized uro-radiologists at the time of biopsy (81%, 95% CI: 74-87; p=0.96). After dichotomization, the CAD was more specific than the PI-RADS ≥3 (p<0.001) and the PI-RADS ≥4 scores (p<0.001). It could offer a solution to select patients who could safely avoid confirmatory or follow-up biopsy during Active Surveillance (25%), while missing 5% of ISUP≥2 cancers. Finally, the CAD was tested with the pre-prostatectomy mp-MRIs of 56 Japanese patients, from a population which is geographically distant from its training population and which is of interest because of its low prostate cancer incidence and mortality. The CAD obtained an AUC similar to the PI-RADSv2 score assigned by an experience radiologist in the PZ (80%, 95% CI: 71-90 vs 80%, 95% CI: 71-89; p=0.886) and in the TZ (79%, 95% CI: 66-90 vs 93%, 95%CI: 82-96; p=0.051). These promising and robust results across heterogeneous datasets suggest that the CAD could be used in clinical routine as a second opinion reader to help select the patients who could safely avoid biopsy. This CAD may assist less experience readers in the characterization of prostate lesions

Le cancer de la prostate (CaP) est le cancer le plus diagnostiqué dans plus de la moitié des pays du monde et le cinquième cancer le plus meurtrier chez les hommes en 2020. Le diagnostic du CaP inclut l'acquisition d'une imagerie par résonance magnétique multiparamétrique (IRM-mp) - qui combine une séquence T2-pondérée (T2-w), une imagerie pondérée en diffusion (DWI) et une séquence dynamique de contraste amélioré (DCE) - avant la réalisation de biopsies. L'analyse jointe de ces images multimodales est fastidieuse et chronophage, en particulier lorsque les séquences mènent à des conclusions différentes. En outre, la sensibilité de l'IRM reste faible pour les cancers peu agressifs et la variabilité inter-observateur élevée. De plus, l'analyse visuelle ne permet pas aujourd'hui de déterminer l'agressivité des cancers, caractérisée par le score de Gleason (GS). C'est pourquoi des systèmes d'aide au diagnostic (CAD) basés sur des modèles statistiques par apprentissage ont été proposés ces dernières années, pour d'assister les radiologues dans leur diagnostic. Toutefois, la majorité de ces systèmes se concentrent sur une tâche de détection binaire des lésions cliniquement significatives (CS). L'objectif de cette thèse est d'élaborer un système CAD pour détecter les CaP sur des IRM-mp, mais aussi de caractériser leur agressivité en prédisant le GS associé. Dans une première partie, nous présentons un système CAD supervisé permettant de segmenter le CaP par agressivité à partir des cartes T2-w et ADC. Ce réseau de neurones multiclasse segmente simultanément la prostate et les lésions par agressivité. Le modèle a été entraîné et évalué en validation croisée à 5 plis sur une base de données hétérogène de 219 examens IRM acquis avant prostatectomie. Pour la tâche de classification par GS, le kappa de Cohen quadratiquement pondéré (κ) est de 0.418 ± 0.138, ce qui représente le meilleur kappa par lésions pour une tâche de segmentation par GS à notre connaissance. Le modèle présente également des capacités de généralisation encourageantes sur le jeu de données public PROSTATEx-2. Dans une deuxième partie, nous nous penchons sur un modèle faiblement supervisé, permettant l'inclusion de données où les lésions sont identifiées par des points seulement, pour un gain de temps conséquent et l'inclusion de bases de données établies sur la biopsie. Concernant la tâche de classification par GS, les performances approchent celles obtenues avec le modèle totalement supervisé de référence, en n'ayant que 6% de voxels annotés pour l'entraînement. Dans une dernière partie, nous étudions l'apport de l'imagerie DCE, séquence souvent omise en entrée des modèles profonds, pour la détection et la caractérisation du CaP. Plusieurs stratégies d'encodage de la perfusion dans une architecture U-Net sont étudiées. Nous montrons que les cartes paramétriques dérivées des examens IRM DCE ont un impact positif sur les performances de segmentation et de classification du CaP
Prostate cancer (PCa) is the most frequently diagnosed cancer in men in more than half the countries in the world and the fifth leading cause of cancer death among men in 2020. Diagnosis of PCa includes multiparametric magnetic resonance imaging acquisition (mp-MRI) - which combines T2 weighted (T2-w), diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) sequences - prior to any biopsy. The joint analysis of these multimodal images is time demanding and challenging, especially when individual MR sequences yield conflicting findings. In addition, the sensitivity of MRI is low for less aggressive cancers and inter-reader reproducibility remains moderate at best. Moreover, visual analysis does not currently allow to determine the cancer aggressiveness, characterized by the Gleason score (GS). This is why computer-aided diagnosis (CAD) systems based on statistical learning models have been proposed in recent years, to assist radiologists in their diagnostic task, but the vast majority of these models focus on the binary detection of clinically significant (CS) lesions. The objective of this thesis is to develop a CAD system to detect and segment PCa on mp-MRI images but also to characterize their aggressiveness, by predicting the associated GS. In a first part, we present a supervised CAD system to segment PCa by aggressiveness from T2-w and ADC maps. This end-to-end multi-class neural network jointly segments the prostate gland and cancer lesions with GS group grading. The model was trained and validated with a 5-fold cross-validation on a heterogeneous series of 219 MRI exams acquired on three different scanners prior prostatectomy. Regarding the automatic GS group grading, Cohen’s quadratic weighted kappa coefficient (κ) is 0.418 ± 0.138, which is the best reported lesion-wise kappa for GS segmentation to our knowledge. The model has also encouraging generalization capacities on the PROSTATEx-2 public dataset. In a second part, we focus on a weakly supervised model that allows the inclusion of partly annotated data, where the lesions are identified by points only, for a consequent saving of time and the inclusion of biopsy-based databases. Regarding the automatic GS group grading on our private dataset, we show that we can approach performance achieved with the baseline fully supervised model while considering 6% of annotated voxels only for training. In the last part, we study the contribution of DCE MRI, a sequence often omitted as input to deep models, for the detection and characterization of PCa. We evaluate several ways to encode the perfusion from the DCE MRI information in a U-Net like architecture. Parametric maps derived from DCE MR exams are shown to positively impact segmentation and grading performance of PCa lesions

Research Doctorate - Doctor of Philosophy (PhD)
In the last few decades, new imaging techniques based on magnetic resonance imaging (MRI) have been developed to improve early-stage detection and diagnosis of prostate cancer. MRI plays an important role in improving the current strategies for detection, delineation and risk stratification for prostate cancer. T2-weighted imaging (T2WI) is the primary imaging technique to evaluate anatomy and pathology in the prostate. However MRI images are expressed in arbitrary units and the absolute values contained within those images can vary due to differences between: MRI scanners; scanning techniques or other technical influences resulting in variations between patients or for the same patient when rescanned at different time points. In this thesis, statistically-based scale standardisation methods for two different centres have been used to address these problems. The results demonstrated a robust and reliable standardisation method for quantitative image assessment. The combination of conventional anatomical and advanced MRI is known as multiparametric MRI (mp-MRI). Mp-MRI is considered to have great potential in accurate prostate cancer diagnosis and characterization. Advanced MRI techniques provide physiological information about tissue to improve prostate cancer diagnosis and characterization. A recent advanced MRI technique is diffusion tensor imaging (DTI). Quantitative analysis of DTI could improve the detection and characterization of prostate cancer by providing additional information. However, difficulties in the processing and interpretation of DTI has limited the role of this imaging in clinical mp-MRI procedures. To evaluate the diagnostic performance of DTI, quantitative DTI and DTI tractography parameters with a focus on their impact in diagnostic and managing prostate cancer patients were extracted and evaluated. A fast imaging technique was utilised to decrease motion artefacts throughout the acquisition of prostate cancer patient data in an ethics approved MRI imaging study. The results demonstrated that DTI and DTI tractography have the potential to provide imaging biomarkers in the detection and characterization of prostate cancer in the peripheral zone. In addition, the utility of DTI in addition to T2-weighted imaging (T2WI) and diffusion weighted imaging (DWI) was assessed for the voxel based detection and prediction of peripheral zone dominant prostate tumours using supervised machine learning technique. Machine learning is a method of data analysis that automates analytical model building. These results demonstrated that DTI in combination with T2WI and DWI can improve the accuracy of prostate cancer detection and delineation. However, T2WI, DWI and DTI have limitations for central gland prostate cancer detection. It is well established that magnetic resonance spectroscopic imaging (MRSI) can provide valuable metabolic information for the non-invasive assessment of central gland prostate cancer. However, MRSI has been excluded from routine clinical mp-MRI in the most recently updated Prostate Imaging Reporting and Data System PI-RADS V2 guideline, probably due to moderate metabolite signal-to-noise ratio (SNR), relatively long acquisition times, the need for a high level of operator expertise, low spectral resolution (especially at 1.5T) and non-standardised acquisition and postprocessing techniques. In the most recent years, MRSI have undergone several technical improvements and show renewed promise for prostate tumour detection and localization. The most recently developed MRSI acquisition technique is known as a gradient-modulated offset-independent adiabatic (GOIA) semi-localized adiabatic selective refocusing (sLASER) (GOIA-sLASER) pulse sequence, which enables acquisition of metabolic data with a high spectral and spatial resolution without an endorectal coil at 3T in a clinically feasible scanning time (8-10 minutes). This thesis investigated the efficacy of in vivo MRSI using the GOIA-sLASER pulse sequence without an endorectal coil for detection and characterization of central gland prostate cancer. This results showed that the GOIA-sLASER sequence with an external phased-array coil allows for an accurate assessment of central gland prostate cancer. In addition, the diagnostic performance of mp-MRI, including T2WI, DWI and dynamic contrast with and without MRSI was assessed. These results demonstrated that MRSI using GOIA-sLASER can be a promising technique for non-invasive and accurate diagnosis of prostate cancer in the central zone. The performance of DTI and MRSI shown in this thesis illustrates potential advantages of non-invasive mp-MRI imaging in the course of prostate cancer detection and diagnosis.

This chapter provides a summary of the landmark PRECISION trial, which investigated how magnetic resonance imaging (MRI) with or without targeted biopsy compared to standard transrectal ultrasonography-guided biopsy in detecting clinically significant prostate cancer. The study provided high-quality evidence to support the use of multiparametric MRI in men with an elevated prostate-specific antigen level as a triage test to help determine the need for a biopsy.

Cardiac magnetic resonance imaging (CMR) has rapidly evolved to become the modality of choice in the evaluation of a wide spectrum of cardiovascular disorders. This is mostly related to its multiparametric approach where the different features such as morphology (including deep tissue characterization), function, perfusion can be non-invasively studied using a series of (different) pulse sequences. Therefore, CMR may provide a ‘one stop shop’ approach to cardiac patients offering a complete cardiac evaluation by a single modality without the use of ionizing radiation. However, to maximize its clinical use, not all pulse sequences should be used in every patient. Moreover, minimizing time spent in the magnetic resonance imaging (MRI) machine is desirable in critically ill, unstable patients. Therefore, experienced cardiac imagers from radiology and cardiology should be present to provide on-site real-time assessment of the images and to determine which pulse sequences are necessary each patient. In this fashion, a complete CMR exam should be obtainable in less than 30 minutes for the vast majority of patients. The aim of this chapter is to describe the physics and practical aspects of CMR and then explore the available pulse sequences, so that the clinical utility of CMR can be maximized.

Purpose: The purpose of this study was to validate the second version of the Prostate Imaging Reporting and Data System (PI-RADSv2) scores in predicting positive in-bore MRI-guided targeted prostate biopsy results across different non-university related institutions. The study focuses on PI-RADS v2 scoring because during the study period, PI-RADS v2.1 had not been released. Materials and Methods: This was a retrospective review of 147 patients who underwent multiparametric magnetic resonance imaging (mpMRI) of the pelvis followed by in-bore MRI-guided targeted prostate biopsy from December 2014 to May 2018. All lesions on mpMRI were rated according to PI-RADS v2 criteria. PI-RADS v2 scores were then compared to MR-guided biopsy results and pre-biopsy PSA values. Results: Prostate Cancer (PCa) was detected in 54% (80/147) of patients, with more prostate cancer being detected with each subsequent increase in PI-RADS scores. Specifically, biopsy results in patients with PI-RADS 3, 4, and 5 lesions resulted in PCa in 25.6% (10/39), 58.1% (33/55), and 86.0% (37/43) respectively. Clinically significant PCa (Gleason score ≥7) was detected in 17.9% (7/39), 52.7% (29/55), and 72% (31/43) of cases for PI-RADS 3, 4, and 5 lesions respectively. When the PI-RADS scoring and biopsy results were compared across different institutions, there was no difference in the PI-RADS scoring of lesions or in the positive biopsy rates of the lesions. The sensitivity, specificity, PPV, and NPV for PI-RADS 3-4 lesions were also not statistically different across the institutions for detecting Gleason 7 or greater lesions. Conclusion: Our results agree with prior studies that higher PI-RADS scores are associated with the presence of clinically significant PCa and suggest prostate lesions with PI-RADS scores 3-5 have sufficient evidence to warrant targeted biopsy. The comparison of PI-RADS score across different types of non-university practices revealed no difference in scoring and biopsy outcome, suggesting that PI-RADS v2 can be easily applied outside of the university medical center setting. Clinical Relevance: PI-RADS v2 can be applied homogeneously in the non-university setting without significant difference in outcome.