The Role of Magnetic Resonance Imaging and Positron Emission Tomography/Computed Tomography in the Primary Staging of Newly Diagnosed Prostate Cancer: A Systematic Review of the Literature

Abrams-Pompe, Raisa S.; Fanti, Stefano; Schoots, Ivo G.; Moore, Caroline M.; Türkbey, Barış; Walz, Jochen; Steuber, Thomas; Eastham, James A.

doi:10.1016/j.euo.2020.11.002

Cited by 29 publications

(17 citation statements)

References 146 publications

(203 reference statements)

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“…within their systematic review, who noted that SE for EPE improved from 53%, to 62%, to 69% for T2WI, to T2WI + one functional technique, to T2WI + two functional techniques, respectively, with no decrease in SP (9). Additionally, similar to our results, incorporation of clinical information is known to improve diagnostic accuracy compared to studies where mpMRI images alone are used (14).…”

Section: Discussionsupporting

confidence: 87%

“…This review included 75 studies and demonstrated high SP (91%) with poor and heterogeneous SE (51%) (9). Since this review a further 48 studies have been published with significant ongoing variation in diagnostic accuracy reported (14). For instance, Davis et Possible explanations for this broad variation in the literature include differences in study design and clinical practice.…”

Section: Discussionmentioning

confidence: 99%

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Negative mpMRI Rules Out Extra-Prostatic Extension in Prostate Cancer Before Robot-Assisted Radical Prostatectomy

Dinneen¹,

Allen²,

Strange³

et al. 2022

Preprint

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The accuracy of multi-parametric MRI (mpMRI) in pre-operative staging of prostate cancer (PCa) remains controversial. Objective: To evaluate the ability of mpMRI to accurately predict PCa extra-prostatic extension (EPE) on a side-specific basis using a risk-stratified 5-point Likert scale. This study also aimed to assess the influence of mpMRI scan quality on diagnostic accuracy. Patients and Methods: We included 124 men who underwent robot-assisted RP (RARP) as part of the NeuroSAFE PROOF study at our centre. Three radiologists retrospectively reviewed mpMRI blinded to RP pathology and assigned a Likert score (1-5) for EPE on each side of the prostate. Each scan was also ascribed a Prostate Imaging Quality (PI-QUAL) score for assessing the quality of the mpMRI scan, where 1 represents poorest and 5 represents best diagnostic quality. Outcome measurements and statistical analyses: Diagnostic performance is presented for binary classification of EPE including 95% confidence intervals and area under the receiver operating characteristic curve (AUC). Results: A total of 231 lobes from 121 men (mean age 56.9 years) were evaluated. 39 men (32.2%), or 43 lobes (18.6%) had EPE. Likert score ≥3 had sensitivity (SE), specificity (SP), NPV, PPV of 90.4%, 52.3%, 96%, 29.9%, respectively, and AUC was 0.82 (95% CI: 0.77-0.86). AUC was 0.63 (95% CI: 0.37-0.9), 0.77 (0.71-0.84) and 0.92 (0.88-0.96) for biparametric scans, PI-QUAL 1-3 and PI-QUAL 4-5 scans, respectively. Conclusions: MRI can be used effectively by genitourinary radiologists to rule out EPE and help inform surgical planning for men undergoing RARP. EPE prediction was more reliable when the MRI scan was a) multi-parametric and b) of a higher image quality according to the PI-QUAL scoring system.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Negative mpMRI Rules Out Extra-Prostatic Extension in Prostate Cancer Before Robot-Assisted Radical Prostatectomy

Dinneen¹,

Allen²,

Strange³

et al. 2022

Preprint

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“…A variety of similar studies show wide variation in sensitivity and specificity of PI-RADS scoring system and 68 Ga PSMA PET-CT in identification of CSPCa. [ 17 18 19 22 23 24 25 26 27 28 29 ] In these studies, we observe that, for detection of CSPCa, PI-RADS v2 sensitivity ranged between 44% and 93% and specificity ranged between 38% and 94%, and 68 Ga PSMA PET-CT sensitivity ranged between 49% and 78.4%, and specificity ranged between 81% and 95%. Wide variation in sensitivity and specificity can be attributed to different acquisition protocols, different cutoffs used, different reference standards used, biopsy inaccuracies, and varied experience of users with PI-RADS v2.…”

Section: Discussionmentioning

confidence: 68%

Multiparametric magnetic resonance imaging, ⁶⁸Ga prostate-specific membrane antigen positron emission tomography–Computed tomography, and respective quantitative parameters in detection and localization of clinically significant prostate cancer in intermediate- and high-risk group patients: An Indian demographic study

et al. 2021

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Objectives: The objective of this study was to evaluate the diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) and 68 Ga prostate-specific membrane antigen positron emission tomography–computed tomography (PSMA PET-CT) and respective quantitative parameters (K trans – influx rate contrast, K ep – efflux rate constant, ADC – apparent diffusion coefficient, and SUVmax ratio – prostate SUVmax to background SUVmax ratio) in detection and localization of clinically significant prostate cancer (CSPCa) in D’Amico intermediate- and high-risk group patients (prostate-specific antigen [PSA] >10 ng/ml). Methodology: The study included thirty-three consecutive adult men with serum prostate specific antigen >10ng/ml, and systematic 12 core prostate biopsy proven prostate cancer. All the 33 patients, were evaluated with mpMRI, and 68 Ga PSMA PET-CT. The biopsy specimens and imaging were evaluated for 12 sectors per prostate by a predetermined scheme. Results: MpMRI Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score ≥3 showed higher sensitivity than 68 Ga PSMA PET-CT (96.3% vs. 82.4%), with similar specificity (54.5% vs. 54.5%) ( n = 33 patients, 396 sectors). Combined use of MRI and 68 Ga PSMA PET-CT in parallel increased sensitivity (99.5%) and NPV (98.7%) for detection of CSPCa and combined use of MRI and 68 Ga PSMA PET-CT in series increased specificity (71.8%) and PPV (71.5%) ( n = 33 patients, 396 sectors). ADC showed a strong negative correlation with Gleason score (r = −0.77), and the highest discriminative ability for detection and localization of CSPCa (area under curve [AUC]: 0.91), followed by K trans ( r = 0.74; AUC: 0.89), PI-RADS (0.73; 0.86), SUVmax ratio (0.49; 0.74), and K ep (0.24; 0.66). Conclusion: MpMRI PI-RADS v2 score and 68 Ga PSMA PET-CT (individually as well as in combination) are reliable tool for detection and localization of CSPCa. Quantitative MRI and 68 Ga PSMA PET-CT parameters have potential to predict Gleason score and detect CSPCa.

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“…Many cancer types spread though the lymphatic system and metastasize in regional lymph nodes 3 – 8 . Sufficiently large metastases can be identified using computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) 9 – 11 . However, current in-vivo imaging techniques are not able to detect microscopic metastases, which would require pathological examination of the tissue 12 , 13 .…”

Section: Introductionmentioning

confidence: 99%

A hidden Markov model for lymphatic tumor progression in the head and neck

Ludwig

Pouymayou

Balermpas

et al. 2021

Sci Rep

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Currently, elective clinical target volume (CTV-N) definition for head and neck squamous cell carcinoma (HNSCC) is mostly based on the prevalence of nodal involvement for a given tumor location. In this work, we propose a probabilistic model for lymphatic metastatic spread that can quantify the risk of microscopic involvement in lymph node levels (LNL) given the location of macroscopic metastases and T-category. This may allow for further personalized CTV-N definition based on an individual patient’s state of disease. We model the patient's state of metastatic lymphatic progression as a collection of hidden binary random variables that indicate the involvement of LNLs. In addition, each LNL is associated with observed binary random variables that indicate whether macroscopic metastases are detected. A hidden Markov model (HMM) is used to compute the probabilities of transitions between states over time. The underlying graph of the HMM represents the anatomy of the lymphatic drainage system. Learning of the transition probabilities is done via Markov chain Monte Carlo sampling and is based on a dataset of HNSCC patients in whom involvement of individual LNLs was reported. The model is demonstrated for ipsilateral metastatic spread in oropharyngeal HNSCC patients. We demonstrate the model's capability to quantify the risk of microscopic involvement in levels III and IV, depending on whether macroscopic metastases are observed in the upstream levels II and III, and depending on T-category. In conclusion, the statistical model of lymphatic progression may inform future, more personalized, guidelines on which LNL to include in the elective CTV. However, larger multi-institutional datasets for model parameter learning are required for that.

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The Role of Magnetic Resonance Imaging and Positron Emission Tomography/Computed Tomography in the Primary Staging of Newly Diagnosed Prostate Cancer: A Systematic Review of the Literature

Cited by 29 publications

References 146 publications

Negative mpMRI Rules Out Extra-Prostatic Extension in Prostate Cancer Before Robot-Assisted Radical Prostatectomy

Negative mpMRI Rules Out Extra-Prostatic Extension in Prostate Cancer Before Robot-Assisted Radical Prostatectomy

A hidden Markov model for lymphatic tumor progression in the head and neck

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