Endorectal MRI for prediction of tumor site, tumor size, and local extension of prostate cancer

Optimal size threshold for PIRADSv2 category 5 upgrade and its positive predictive value: is it predictive of "very high" likelihood of clinically-significant cancer?

AIM

To identify the optimal size metric and threshold for Prostate Imaging Reporting and Data System (PIRADS) 5 upgrade, calculate its positive predictive value (PPV) for clinically-significant prostate cancer (csPCA), and determine if it is indicative of a "very high" likelihood of csPCA.

MATERIALS AND METHODS

One hundred and forty-three PIRADS 4 or 5 lesions were evaluated. Lesion diameters were used to calculate lesion volume (LV). Pearson correlation between maximum lesion diameter (MLD) and LV was calculated. Area under the curve (AUC) for discriminating csPCA (Gleason grade ≥ 3 + 4) was calculated using MLD and LV. Optimal size thresholds (using Youden index) and highly predictive size thresholds were identified for the whole prostate (WP), peripheral zone (PZ), and transitional zone (TZ).

RESULTS

There was high correlation between MLD and LV (r=0.77-0.81), with comparable AUCs for MLD and LV in the identification of csPCA in the WP (0.73, 0.72), PZ (0.73, 0.73), and TZ (0.79, 0.75). Optimal MLD thresholds were 1.4, 1.4, and 1.6 cm in the WP, PZ, and TZ respectively, with PPVs of 76%, 81%, and 69%, respectively. An MLD threshold of 2.7 cm would be needed in the WP to achieve a PPV approaching 90%, with sensitivity decreasing to 10%.

CONCLUSIONS

There is high correlation between MLD and LV with comparable discrimination of csPCA using each. PIRADSv2's 1.5 cm MLD threshold is near the optimal threshold for PIRADS 5 upgrade but has moderate PPV. A much higher threshold would be needed to increase its PPV, with significant sacrifice in sensitivity.

Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 1: Raman spectroscopy fiber-optics system and in situ tissue characterization

SIGNIFICANCE

The diagnosis of prostate cancer (PCa) and focal treatment by brachytherapy are limited by the lack of precise intraoperative information to target tumors during biopsy collection and radiation seed placement. Image-guidance techniques could improve the safety and diagnostic yield of biopsy collection as well as increase the efficacy of radiotherapy.

AIM

To estimate the accuracy of PCa detection using in situ Raman spectroscopy (RS) in a pilot in-human clinical study and assess biochemical differences between in vivo and ex vivo measurements.

APPROACH

A new miniature RS fiber-optics system equipped with an electromagnetic (EM) tracker was guided by trans-rectal ultrasound-guided imaging, fused with preoperative magnetic resonance imaging to acquire 49 spectra in situ (in vivo) from 18 PCa patients. In addition, 179 spectra were acquired ex vivo in fresh prostate samples from 14 patients who underwent radical prostatectomy. Two machine-learning models were trained to discriminate cancer from normal prostate tissue from both in situ and ex vivo datasets.

RESULTS

A support vector machine (SVM) model was trained on the in situ dataset and its performance was evaluated using leave-one-patient-out cross validation from 28 normal prostate measurements and 21 in-tumor measurements. The model performed at 86% sensitivity and 72% specificity. Similarly, an SVM model was trained with the ex vivo dataset from 152 normal prostate measurements and 27 tumor measurements showing reduced cancer detection performance mostly attributable to spatial registration inaccuracies between probe measurements and histology assessment. A qualitative comparison between in situ and ex vivo measurements demonstrated a one-to-one correspondence and similar ratios between the main Raman bands (e.g., amide I-II bands, phenylalanine).

CONCLUSIONS

PCa detection can be achieved using RS and machine learning models for image-guidance applications using in situ measurements during prostate biopsy procedures.

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

Background

A more accurate preoperative prediction of lymph node involvement (LNI) in prostate cancer (PCa) would improve clinical treatment and follow-up strategies of this disease. We developed a predictive model based on machine learning (ML) combined with big data to achieve this.

Methods

Clinicopathological characteristics of 2,884 PCa patients who underwent extended pelvic lymph node dissection (ePLND) were collected from the U.S. National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Eight variables were included to establish an ML model. Model performance was evaluated by the receiver operating characteristic (ROC) curves and calibration plots for predictive accuracy. Decision curve analysis (DCA) and cutoff values were obtained to estimate its clinical utility.

Results

Three hundred and forty-four (11.9%) patients were identified with LNI. The five most important factors were the Gleason score, T stage of disease, percentage of positive cores, tumor size, and prostate-specific antigen levels with 158, 137, 128, 113, and 88 points, respectively. The XGBoost (XGB) model showed the best predictive performance and had the highest net benefit when compared with the other algorithms, achieving an area under the curve of 0.883. With a 5%~20% cutoff value, the XGB model performed best in reducing omissions and avoiding overtreatment of patients when dealing with LNI. This model also had a lower false-negative rate and a higher percentage of ePLND was avoided. In addition, DCA showed it has the highest net benefit across the whole range of threshold probabilities.

Conclusions

We established an ML model based on big data for predicting LNI in PCa, and it could lead to a reduction of approximately 50% of ePLND cases. In addition, only ≤3% of patients were misdiagnosed with a cutoff value ranging from 5% to 20%. This promising study warrants further validation by using a larger prospective dataset.

Characteristics and risk differences of different tumor size on localized prostate cancer: A retrospective cohort study in the SEER database

Objective

We aimed to evaluate the role of tumor size in predicting tumor risk for localized prostate cancer (PCa) patients undergoing radical prostatectomy (RP).

Methods

Twenty‐five thousand, one hundred twenty‐seven men with PCa receiving RP from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results database. Kaplan–Meier plots and multivariable Cox regression analyses were used to illustrate overall survival (OS) according to the tumor size. The tumor size was confirmed by postoperative pathology after RP.

Results

Among overall localized PCa, 84.6% were high‐risk PCa, 9.2% were intermediate‐risk PCa, and 6.2% were low‐risk PCa. Multivariate analyses demonstrated that tumor size ≥21 mm was an independent risk predict factor of low‐risk PCa (odds ratio [OR]: 11.940; 95% CI, 9.404–15.161; p < 0.001) and intermediate‐risk PCa (OR: 1.887; 95% CI, 1.586–2.245; p < 0.001). Tumor sizes ≤5 mm significantly correlated with high‐risk PCa (p < 0.001). Tumor size ≤5 mm had the worst OS in overall localized PCa and high‐risk PCa (p < 0.001).

Conclusions

In localized PCa, tumor sizes ≥21 mm may help predict low or intermediate‐risk PCa, while tumor sizes ≤5 mm might help predict high‐risk PCa. In clinical practice, we should be on high alert for patients with tumors size ≤5 mm due to its poor prognosis after RP.

Algorithms applied to spatially registered multi-parametric MRI for prostate tumor volume measurement

Background

Prostate tumor volume correlates with critical components of cancer staging such as Gleason score (GS) grade, predicted disease progression, and metastasis. Therefore, non-invasive tumor volume measurement may elevate clinical management. Radiology assessments of multi-parametric MRI (MP-MRI) commonly visually examine individual images to determine possible tumor presence. This study combines registered MP-MRI into a single image that display normal tissue and possible lesions. This study tests and exploits the vector nature of spatially registered MP-MRI by using supervised target detection algorithms (STDA) and color display and psychovisual analysis (CIELAB) to non-invasively estimate prostate tumor volume.

Methods

MRI, including T1, T2, diffusion [apparent diffusion coefficient (ADC)], dynamic contrast enhanced (DCE) images, were resampled, rescaled, translated, and stitched to form spatially registered Multi-parametric cubes. The multi-parametric or multi-spectral signatures (7-component or T1, T2, ADC, etc.) that characterize the prostate tumors were inserted into target detection algorithms with conical decision surfaces (adaptive cosine estimator, ACE). Various detection thresholds were applied to discriminate tumor from normal tissue. In addition, tumor appeared as yellow in color images that were created by assigning red to washout from DCE, green to high B from diffusion, and blue to autonomous diffusion image. The yellow voxels in the three-channel hypercube were visually identified by a reader and recording voxels that exceed a threshold in the b* component of the CIELAB algorithm. The number of reported tumor voxels were converted to volume based on spatial resolution and slice separation. The tumor volume measurements were quantitatively validated by comparing the tumor volume computations to the pathologist's assessment of the histology of sectioned whole mount prostates from 26 consecutive patients with prostate adenocarcinoma who underwent radical prostatectomy. This study analyzed tumors exceeding 1 cc and that also took up contrast material (18 patients).

Results

High correlation coefficients for tumor volume measurements using supervised target detection and color analysis vs. histology from wholemount prostatectomy were computed (R=0.83 and 0.91, respectively). A linear fit for tumor volume measurements using for supervised target detection and color analysis vs. tumor measurements from radical prostatectomy (after correcting for shrinkage from the radical prostatectomy) results in a slope of 1.02 and 3.02, respectively. A polynomial fit for the color analysis to the histology found (R=0.95). Voxels exceeding a threshold in the b* part of the CIELAB algorithm yielded correlation coefficients (0.71, 0.80) offsets (0.01 cc, -0.63 cc) and slopes (1.99, 0.89) against the wholemount prostatectomy and color analysis, respectively.

Conclusions

Supervised target detection and color display and analysis applied to registered MP-MRI non-invasively estimates prostate tumor volumes >1 cc and displaying angiogenesis.

Prostate cancer local staging using biparametric MRI: assessment and comparison with multiparametric MRI

PURPOSE

The value of adding dynamic contrast-enhanced (DCE) imaging to T2-weighted (T2W) magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) to improve the detection and staging of prostate cancer (PCa) is unclear. The aim of this retrospective study was to compare the diagnostic performance of non-contrast biparametric MRI (bpMRI) with multiparametric MRI (mpMRI), for local staging of PCa.

METHODS

Ninety-two patients who underwent prostate MRI on a 3-Tesla MRI system before radical prostatectomy for PCa were included retrospectively. Four readers independently assigned a Likert score (ranging from 1 to 5) for predicting extra-prostatic extension (EPE) on T2W + DWI (bpMRI) and then on T2W + DWI + DCE imaging (mpMRI). MRI-based staging results were compared with radical prostatectomy histology. A prediction of EPE generalized linear mixed model was used to assess the added-value of DCE and discriminative power of staging accuracy by area under the receiver-operating curve (AUC ROC).

RESULTS

AUC was not significantly improved by DCE (mpMRI, AUC = 0.73 [95%CI: 0.655‒0.827] vs. bpMRI, AUC = 0.76 [95%CI: 0.681‒0.846]). After applying a selection procedure, only MRI criteria were retained in a multivariate model. The following criteria were significantly associated with local extension: localization in the peripheral zone (p < 0.001), maximal diameter of the lesion (<0.0001), curvilinear capsular contact on T2W (p < 0.0001), capsular irregularity on T2W (p < 0.0001), bulging on T2W (p < 0.001) and seminal vesicle hypo-signal (p < 0.001).

CONCLUSION

Use of bpMRI did not result in a decrease in local staging accuracy.

Use of Imaging to Optimise Prostate Cancer Tumour Volume Assessment for Focal Therapy Planning

PURPOSE OF REVIEW

Rapid advances in imaging of the prostate have facilitated the development of focal therapy and provided a non-invasive method of estimating tumour volume. Focal therapy relies on an accurate estimate of tumour volume for patient selection and treatment planning so that the optimal energy dose can be delivered to the target area(s) of the prostate while minimising toxicity to surrounding structures. This review provides an overview of different imaging modalities which may be used to optimise tumour volume assessment and critically evaluates the published evidence for each modality.

RECENT FINDINGS

Multi-parametric MRI (mp-MRI) has become the standard tool for patient selection and guiding focal therapy treatment. The current evidence suggests that mp-MRI may underestimate tumour volume, although there is a large variability in results. There remain significant methodological challenges associated with pathological processing and accurate co-registration of histopathological data with mp-MRI. Advances in different ultrasound modalities are showing promise but there has been limited research into tumour volume estimation. The role of PSMA PET/CT is still evolving and further investigation is needed to establish if this is a viable technique for prostate tumour volumetric assessment. mp-MRI provides the necessary tumour volume information required for selecting patients and guiding focal therapy treatment. The potential for underestimation of tumour volume should be taken into account and an additional margin applied to ensure adequate treatment coverage. At present, there are no other viable image-based alternatives although advances in new technologies may refine volume estimations in the future.

Evaluating the size criterion for PI-RADSv2 category 5 upgrade: is 15 mm the best threshold?

PURPOSE

The purpose of the study was to determine if the ≥ 15 mm threshold currently used to define PIRADS 5 lesions is the optimal size threshold for predicting high likelihood of clinically significant (CS) cancers.

MATERIALS

Three hundred and fifty-eight lesions that may be changed from category 4 to 5 or vice versa on the basis of the size criterion (category 4: n = 288, category 5: n = 70) from 255 patients were evaluated. Kendall's tau-b statistic accounting for inter-lesion correlation, generalized estimation equation logistic regression, and receiver operating curve analysis evaluated two lesion size-metrics (lesion diameter and relative lesion diameter-defined as lesion diameter/prostate volume) for ability to identify CS (Gleason grade ≥ 3 + 4) cancer at targeted biopsy. Optimal cut-points were identified using the Youden index. Analyses were performed for the whole prostate (WP) and zone-specific sub-cohorts of lesions in the peripheral and transition zones (PZ and TZ).

RESULTS

Lesion diameter showed a modest correlation with Gleason grade (WP: τB = 0.21, p < 0.0001; PZ: τB = 0.13, p = 0.02; TZ: τB = 0.32, p = 0.001), and association with CS cancer detection (WP: AUC = 0.63, PZ: AUC = 0.59, TZ: AUC = 0.74). Empirically derived thresholds (WP: 14 mm, PZ: 13 mm, TZ: 16 mm) performed similarly to the current ≥ 15 mm standard. Lesion relative lesion diameter improved identification of CS cancers compared to lesion diameter alone (WP: τB = 0.30, PZ: τB = 0.24, TZ: τB = 0.42, all p < 0.0001). AUC also improved for WP and PZ lesions (WP: AUC = 0.70, PZ: AUC = 0.68, and TZ: AUC = 0.74).

CONCLUSIONS

The current ≥ 15 mm diameter threshold is a reasonable delineator of PI-RADS category 4 and category 5 lesions in the absence of extraprostatic extension to predict CS cancers. Additionally, relative lesion diameter can improve identification of CS cancers and may serve as another option for distinguishing category 4 and 5 lesions.

The natural history of prostate cancer on MRI: lessons from an active surveillance cohort

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) is being used increasingly in the setting of active surveillance (AS) for prostate cancer. We investigated changes in the mpMRI appearance of lesions on AS, to show the variability of volume measurements in visible lesions and assess change in lesion size according to grade.

METHODS

We retrospectively retrieved 86 men on AS (NICE guidelines) with more than one mpMRI (the first before 2013). Two radiologists, in consensus, were blinded to patient demographics and date of scan. The scans were randomly reported to reduce any bias. For visible lesions, we measured volume by planimetry on the sequence best showing the most conspicuous (index) tumour and attributed a 5-point Likert score.

RESULTS

43/86 men did not have a visible lesion on the initial mpMRI (≤2/5). Of these, 5/43 had developed a lesion scoring ≥3/5 at a median of 3.6 years of follow up. 40/86 had a lesion scoring ≥3/5 on two or more scans. There was a significant increase in volume over 3.6 years by a median of 10% (p < 0.01)-by a median of 6% for Gleason 3+3 and 18% for 3+4 (p = 0.058). Thirty-five men had a visible lesion on two scans separated by <2 years; of these, 21/35 showed a 78% median increase in tumour size between the two scans and 11/35 showed an apparent 25% median decrease in lesion size.

CONCLUSIONS

A total of 17% of men with no visible lesion developed a visible lesion at a median follow up of 3.6 years. It is possible to show significant growth in patients with a visible lesion, but variability in volume measurements between scans means that it is difficult to reliably detect increases of this order. This variability may inform the design of mpMRI protocols in AS and the time between follow up scans.

What Are We Missing? False-Negative Cancers at Multiparametric MR Imaging of the Prostate

Purpose To characterize clinically important prostate cancers missed at multiparametric (MP) magnetic resonance (MR) imaging. Materials and Methods The local institutional review board approved this HIPAA-compliant retrospective single-center study, which included 100 consecutive patients who had undergone MP MR imaging and subsequent radical prostatectomy. A genitourinary pathologist blinded to MP MR findings outlined prostate cancers on whole-mount pathology slices. Two readers correlated mapped lesions with reports of prospectively read MP MR images. Readers were blinded to histopathology results during prospective reading. At histopathologic examination, 80 clinically unimportant lesions (<5 mm; Gleason score, 3+3) were excluded. The same two readers, who were not blinded to histopathologic findings, retrospectively reviewed cancers missed at MP MR imaging and assigned a Prostate Imaging Reporting and Data System (PI-RADS) version 2 score to better understand false-negative lesion characteristics. Descriptive statistics were used to define patient characteristics, including age, prostate-specific antigen (PSA) level, PSA density, race, digital rectal examination results, and biopsy results before MR imaging. Student t test was used to determine any demographic differences between patients with false-negative MP MR imaging findings and those with correct prospective identification of all lesions. Results Of the 162 lesions, 136 (84%) were correctly identified with MP MR imaging. Size of eight lesions was underestimated. Among the 26 (16%) lesions missed at MP MR imaging, Gleason score was 3+4 in 17 (65%), 4+3 in one (4%), 4+4 in seven (27%), and 4+5 in one (4%). Retrospective PI-RADS version 2 scores were assigned (PI-RADS 1, n = 8; PI-RADS 2, n = 7; PI-RADS 3, n = 6; and PI-RADS 4, n = 5). On a per-patient basis, MP MR imaging depicted clinically important prostate cancer in 99 of 100 patients. At least one clinically important tumor was missed in 26 (26%) patients, and lesion size was underestimated in eight (8%). Conclusion Clinically important lesions can be missed or their size can be underestimated at MP MR imaging. Of missed lesions, 58% were not seen or were characterized as benign findings at second-look analysis. Recognition of the limitations of MP MR imaging is important, and new approaches to reduce this false-negative rate are needed. ^© RSNA, 2017 Online supplemental material is available for this article.

Multi-parametric MRI imaging of the prostate-implications for focal therapy

The primary goal of a focal therapy treatment paradigm is to achieve cancer control through targeted tissue destruction while simultaneously limiting deleterious effects on peri-prostatic structures. Focal therapy approaches are employed in several oncologic treatment protocols, and have been shown to provide equivalent cancer control for malignancies such as breast cancer and renal cell carcinoma. Efforts to develop a focal therapy approach for prostate cancer have been challenged by several concepts including the multifocal nature of the disease and limited capability of prostate ultrasound and systematic biopsy to reliably localize the site(s) and aggressiveness of disease. Multi-parametric MRI (mpMRI) of the prostate has significantly improved disease localization, spatial demarcation and risk stratification of cancer detected within the prostate. The accuracy of this imaging modality has further enabled the urologist to improve biopsy approaches using targeted biopsy via MRI-ultrasound fusion. From this foundation, an improved delineation of the location of disease has become possible, providing a critical foundation to the development of a focal therapy strategy. This chapter reviews the accuracy of mpMRI for detection of “aggressive“ disease, the accuracy of mpMRI in determining the tumor volume, and the ability of mpMRI to accurately identify the index lesion. While mpMRI provides a critical, first step in developing a strategy for focal therapy, considerable questions remain regarding the relationship between MR identified tumor volume and pathologic tumor volume, the accuracy and utility of mpMRI for treatment surveillance and the optimal role and timing of follow-up mpMRI.

Volumetry of the dominant intraprostatic tumour lesion: intersequence and interobserver differences on multiparametric MRI

OBJECTIVE

To establish the interobserver reproducibility of tumour volumetry on individual multiparametric (mp) prostate MRI sequences, validate measurements with histology and determine whether functional to morphological volume ratios reflect Gleason score.

METHODS

41 males with prostate cancer treated with prostatectomy (Cohort 1) or radical radiotherapy (Cohort 2), who had pre-treatment mpMRI [T2 weighted (T2W) MRI, diffusion-weighted (DW)-MRI and dynamic contrast-enhanced (DCE)-MRI], were studied retrospectively. Dominant intraprostatic lesions (DIPLs) were manually delineated on each sequence and volumes were compared between observers (n = 40 analyzable) and with radical prostatectomy (n = 20). Volume ratios of DW-MRI and DCE-MRI to T2W MRI were documented and compared between Gleason grade 3 + 3, 3 + 4 and 4 + 3 or greater categories.

RESULTS

Limits of agreement of DIPL volumes between observers were: T2W MRI 0.9, -1.1 cm3, DW-MRI 1.3, -1.7 cm3 and DCE-MRI 0.74, -0.89 cm3. In Cohort 1, T2W volumes overestimated fixed specimen histological volumes (+33% Observer 1, +16% Observer 2); DW- and DCE-MRI underestimated histological volume, the latter markedly so (-32% Observer 1, -79% Observer 2). Differences between T2W, DW- and DCE-MRI volumes were significant (p < 10-8). The ratio of DW-MRI volume (73.9 ± 18.1% Observer 1, 72.5 ± 21.9% Observer 2) and DCE-MRI volume (42.6 ± 24.6% Observer 1, 34.3 ± 24.9% Observer 2) to T2W volume was significantly different (p < 10-8), but these volume ratios did not differ between the Gleason grades.

CONCLUSION

The low variability of the DIPL volume on T2W MRI between Observers and agreement with histology indicates its suitability for delineation of gross tumour volume for radiotherapy planning. The volume of cellular tumour represented by DW-MRI is greater than the vascular (DCE) abnormality; ratios of both to T2W volume are independent of Gleason score. Advances in knowledge: (1) Manual volume measurement of tumour is reproducible within 1 cm3 between observers on all sequences, confirming suitability across observers for radiotherapy planning. (2) Volumes derived on T2W MRI most accurately represent in vivo lesion volumes. (3) The proportion of cellular (DW-MRI) or vascular (DCE-MRI) volume to morphological (T2W MRI) volume is not affected by Gleason score.

Incremental value of high b value diffusion-weighted magnetic resonance imaging at 3-T for prediction of extracapsular extension in patients with prostate cancer: preliminary experience

PURPOSE

To investigate whether high b value diffusion-weighted imaging (DWI) contributes to the improvement of diagnostic ability of extracapsular extension (ECE) in prostate cancer (PC).

MATERIALS AND METHODS

Forty-three patients with PC underwent multiparametric MRI including DWI (b values: 0, 2000 s/mm²) at 3-T. Two radiologists assessed the presence of ECE and the diagnostic certainty degree using conventional diagnostic method by consensus. Tumor apparent diffusion coefficient (ADC, ×10^-3 mm²/s) was also measured. Independent predictors of ECE were identified among PSA, tumor ADC, Gleason score, and conventional MRI. ECE in patients with low diagnostic certainty by conventional MRI was further reevaluated using ADC cutoff value, and the results were combined with those of patients with high diagnostic certainty by conventional MRI (MRI + ADC method).

RESULTS

Tumor ADC was an independent predictor of ECE, and the ADC cutoff value was 0.72. The sensitivity, specificity, and accuracy of conventional MRI and MRI + ADC method in the diagnosis of ECE were 44, 92, and 72%, and 78, 96, and 88%, respectively. Among MRI findings leading to the judgement of low diagnostic certainty, broad tumor contact was most common (72% of the patients).

CONCLUSIONS

The addition of ADC obtained with high b value DWI at 3-T to conventional MRI improved the diagnostic ability of ECE.

Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model

Diffusion weighted magnetic resonance imaging (DW-MR) is a powerful tool in imaging-based prostate cancer screening and detection. Endorectal coils are commonly used in DW-MR imaging to improve the signal-to-noise ratio (SNR) of the acquisition, at the expense of significant intensity inhomogeneities (bias field) that worsens as we move away from the endorectal coil. The presence of bias field can have a significant negative impact on the accuracy of different image analysis tasks, as well as prostate tumor localization, thus leading to increased inter- and intra-observer variability. Retrospective bias correction approaches are introduced as a more efficient way of bias correction compared to the prospective methods such that they correct for both of the scanner and anatomy-related bias fields in MR imaging. Previously proposed retrospective bias field correction methods suffer from undesired noise amplification that can reduce the quality of bias-corrected DW-MR image. Here, we propose a unified data reconstruction approach that enables joint compensation of bias field as well as data noise in DW-MR imaging. The proposed noise-compensated, bias-corrected (NCBC) data reconstruction method takes advantage of a novel stochastically fully connected joint conditional random field (SFC-JCRF) model to mitigate the effects of data noise and bias field in the reconstructed MR data. The proposed NCBC reconstruction method was tested on synthetic DW-MR data, physical DW-phantom as well as real DW-MR data all acquired using endorectal MR coil. Both qualitative and quantitative analysis illustrated that the proposed NCBC method can achieve improved image quality when compared to other tested bias correction methods. As such, the proposed NCBC method may have potential as a useful retrospective approach for improving the consistency of image interpretations.

Postediting prostate magnetic resonance imaging segmentation consistency and operator time using manual and computer-assisted segmentation: multiobserver study

Prostate segmentation on T2w MRI is important for several diagnostic and therapeutic procedures for prostate cancer. Manual segmentation is time-consuming, labor-intensive, and subject to high interobserver variability. This study investigated the suitability of computer-assisted segmentation algorithms for clinical translation, based on measurements of interoperator variability and measurements of the editing time required to yield clinically acceptable segmentations. A multioperator pilot study was performed under three pre- and postediting conditions: manual, semiautomatic, and automatic segmentation. We recorded the required editing time for each segmentation and measured the editing magnitude based on five different spatial metrics. We recorded average editing times of 213, 328, and 393 s for manual, semiautomatic, and automatic segmentation respectively, while an average fully manual segmentation time of 564 s was recorded. The reduced measured postediting interoperator variability of semiautomatic and automatic segmentations compared to the manual approach indicates the potential of computer-assisted segmentation for generating a clinically acceptable segmentation faster with higher consistency. The lack of strong correlation between editing time and the values of typically used error metrics ([Formula: see text]) implies that the necessary postsegmentation editing time needs to be measured directly in order to evaluate an algorithm's suitability for clinical translation.

Are magnetic resonance imaging undetectable prostate tumours clinically significant? Results of histopathological analyses

OBJECTIVE

To investigate whether tumours at threshold values for detection on magnetic resonance imaging (MRI) represent clinically significant tumours or not, and therefore the utility of MRI in active surveillance (AS) protocols.

PATIENTS AND METHODS

A retrospective analysis of a single institution database was performed after Institutional Review Board approval. Between 2010 and 2013, 1633 patients underwent robot-assisted laparoscopic prostatectomy (RALP) at a single institution by a single surgeon. Of these, 1361 had complete clinical data and were included in analysis. Multivariate logistic regression was used to assess histopathological grade compared to tumour size whilst controlling for biopsy Gleason score, prostate-specific antigen level, body mass index, race, and age.

RESULTS

Of 120 tumours <5 mm in size, four were Gleason score 4 + 3. Of 276 tumours of 5-10 mm, 22 (8.1%) were Gleason score 4 + 3 and one (0.2%) was Gleason score 8. On multivariate regression analyses, tumours of <5 mm were much less likely to be high grade (Gleason score >3 + 4) at RALP compared to larger tumours (3.3% vs 25.1%, P < 0.001), or Gleason score ⩾8 (0.0% vs 7.6%, P < 0.001). Size was further shown to significantly correlate with grade on multivariate regression (P < 0.001).

CONCLUSIONS

Prostate tumours below the detection threshold for MRI (5 mm) most probably represent clinically insignificant tumours, which alone would not necessitate leaving AS in favour of more aggressive therapy. These findings point to a possible role of MRI in modern AS protocols.

Deflection Analysis of Different Needle Designs for Prostate Biopsy and Focal Therapy

OBJECTIVE

The biopsy needles currently used were designed for a transrectal biopsy and are known to experience significant deflection from the point of entry into the gland to the needle tip.

METHODS

Five designs were selected for testing: 18-gauge Bard, 15-gauge lancet tip needle with 12° vet-point cannula, and trocar tip needle with 12°, 15°, and 20° vet-point cannulas. The 15-gauge needle was designed to take a variable specimen sample between 20 and 60 mm, whereas the Bard needle specimen bed was fixed at 20 mm. The needles were bench tested on a spring-loaded platform and fired into gelatin matrix with modulus of elasticity similar to human prostate.

RESULTS

The Bard device with lancet tip needle deflected an average of 0.9 mm (range 0.3-1.3 mm) and 1.9° (range 0.6°-2.8°). Increasing needle diameter from 18-gauge Bard to 15-gauge variable with the same lancet tip needle design resulted in an average deflection across the 3 test lengths of 0.9 mm (range 0-2.0 mm) and 0.9° (range 0°-2.0°) with no significant difference. On the contrary, the use of the 3-point trocar tip needles with 12°, 15°, and 20° vet-point cannulas demonstrated significant reduction in the extent of deflection in both millimeters and degrees. There was no deflection at the 2- and 4-cm shots for both spring loads and preloads for the 3 vet tip angles tested. At 6 cm, the 20° vet tip performed the best.

CONCLUSION

We proposed a mechanism that provides more accurate prostate sampling by combining a 3-point trocar tip on the needle with a 20° vet tip on the cutting cannula. Using the phantom, mimicking prostate gland tissue density, no deflection was revealed between 20- and 60-mm biopsy lengths, which should permit a straight sample in the majority of prostate glands and improve cancer localization for focal therapy planning.

4D MR imaging using robust internal respiratory signal

The purpose of this study is to investigate the feasibility of using internal respiratory (IR) surrogates to sort four-dimensional (4D) magnetic resonance (MR) images. The 4D MR images were constructed by acquiring fast 2D cine MR images sequentially, with each slice scanned for more than one breathing cycle. The 4D volume was then sorted retrospectively using the IR signal. In this study, we propose to use multiple low-frequency components in the Fourier space as well as the anterior body boundary as potential IR surrogates. From these potential IR surrogates, we used a clustering algorithm to identify those that best represented the respiratory pattern to derive the IR signal. A study with healthy volunteers was performed to assess the feasibility of the proposed IR signal. We compared this proposed IR signal with the respiratory signal obtained using respiratory bellows. Overall, 99% of the IR signals matched the bellows signals. The average difference between the end inspiration times in the IR signal and bellows signal was 0.18 s in this cohort of matching signals. For the acquired images corresponding to the other 1% of non-matching signal pairs, the respiratory motion shown in the images was coherent with the respiratory phases determined by the IR signal, but not the bellows signal. This suggested that the IR signal determined by the proposed method could potentially correct the faulty bellows signal. The sorted 4D images showed minimal mismatched artefacts and potential clinical applicability. The proposed IR signal therefore provides a feasible alternative to effectively sort MR images in 4D.

Prostate cancer risk stratification with magnetic resonance imaging

In recent years, multiparametric magnetic resonance imaging (mpMRI) has shown promise for prostate cancer (PCa) risk stratification. mpMRI, often followed by targeted biopsy, can be used to confirm low-grade disease before enrollment in active surveillance. In patients with intermediate or high-risk PCa, mpMRI can be used to inform surgical management. mpMRI has sensitivity of 44% to 87% for detection of clinically significant PCa and negative predictive value of 63% to 98% for exclusion of significant disease. In addition to tumor identification, mpMRI has also been shown to contribute significant incremental value to currently used clinical nomograms for predicting extraprostatic extension. In combination with conventional clinical criteria, accuracy of mpMRI for prediction of extraprostatic extension ranges from 92% to 94%, significantly higher than that achieved with clinical criteria alone. Supplemental sequences, such as diffusion-weighted imaging and dynamic contrast-enhanced imaging, allow quantitative evaluation of cancer-suspicious regions. Apparent diffusion coefficient appears to be an independent predictor of PCa aggressiveness. Addition of apparent diffusion coefficient to Epstein criteria may improve sensitivity for detection of significant PCa by as much as 16%. Limitations of mpMRI include variability in reporting, underestimation of PCa volume and failure to detect clinically significant disease in a small but significant number of cases.

Current role of multiparametric magnetic resonance imaging for prostate cancer

Multiparametric magnetic resonance imaging (mp-MRI) has shown promising results in diagnosis, localization, risk stratification and staging of clinically significant prostate cancer, and targeting or guiding prostate biopsy. mp-MRI consists of T2-weighted imaging (T2WI) combined with several functional sequences including diffusion-weighted imaging (DWI), perfusion or dynamic contrast-enhanced imaging (DCEI) and spectroscopic imaging. Recently, mp-MRI has been used to assess prostate cancer aggressiveness and to identify anteriorly located tumors before and during active surveillance. Moreover, recent studies have reported that mp-MRI is a reliable imaging modality for detecting local recurrence after radical prostatectomy or external beam radiation therapy. Because assessment on mp-MRI can be subjective, use of the newly developed standardized reporting Prostate Imaging and Reporting Archiving Data System (PI-RADS) scoring system and education of specialist radiologists are essential for accurate interpretation. This review focuses on the current place of mp-MRI in prostate cancer and its evolving role in the management of prostate cancer.

Image Guided Focal Therapy for Magnetic Resonance Imaging Visible Prostate Cancer: Defining a 3-Dimensional Treatment Margin Based on Magnetic Resonance Imaging Histology Co-Registration Analysis

PURPOSE

We compared prostate tumor boundaries on magnetic resonance imaging and radical prostatectomy histological assessment using detailed software assisted co-registration to define an optimal treatment margin for achieving complete tumor destruction during image guided focal ablation.

MATERIALS AND METHODS

Included in study were 33 patients who underwent 3 Tesla magnetic resonance imaging before radical prostatectomy. A radiologist traced lesion borders on magnetic resonance imaging and assigned a suspicion score of 2 to 5. Three-dimensional reconstructions were created from high resolution digitalized slides of radical prostatectomy specimens and co-registered to imaging using advanced software. Tumors were compared between histology and imaging by the Hausdorff distance and stratified by the magnetic resonance imaging suspicion score, Gleason score and lesion diameter. Cylindrical volume estimates of treatment effects were used to define the optimal treatment margin.

RESULTS

Three-dimensional software based registration with magnetic resonance imaging was done in 46 histologically confirmed cancers. Imaging underestimated tumor size with a maximal discrepancy between imaging and histological boundaries for a given tumor of an average ± SD of 1.99 ± 3.1 mm, representing 18.5% of the diameter on imaging. Boundary underestimation was larger for lesions with an imaging suspicion score 4 or greater (mean 3.49 ± 2.1 mm, p <0.001) and a Gleason score of 7 or greater (mean 2.48 ± 2.8 mm, p = 0.035). A simulated cylindrical treatment volume based on the imaging boundary missed an average 14.8% of tumor volume compared to that based on the histological boundary. A simulated treatment volume based on a 9 mm treatment margin achieved complete histological tumor destruction in 100% of patients.

CONCLUSIONS

Magnetic resonance imaging underestimates histologically determined tumor boundaries, especially for lesions with a high imaging suspicion score and a high Gleason score. A 9 mm treatment margin around a lesion visible on magnetic resonance imaging would consistently ensure treatment of the entire histological tumor volume during focal ablative therapy.

Multiparametric-MRI in diagnosis of prostate cancer

Multiparametric-magnetic resonance imaging (mp-MRI) has shown promising results in diagnosis, localization, risk stratification and staging of clinically significant prostate cancer. It has also opened up opportunities for focal treatment of prostate cancer. Combinations of T2-weighted imaging, diffusion imaging, perfusion (dynamic contrast-enhanced imaging) and spectroscopic imaging have been used in mp-MRI assessment of prostate cancer, but T2 morphologic assessment and functional assessment by diffusion imaging remains the mainstay for prostate cancer diagnosis on mp-MRI. Because assessment on mp-MRI can be subjective, use of the newly developed standardized reporting Prostate Imaging and Reporting Archiving Data System scoring system and education of specialist radiologists are essential for accurate interpretation. This review focuses on the present status of mp-MRI in prostate cancer and its evolving role in the management of prostate cancer.

Detection of the index tumour and tumour volume in prostate cancer using T2-weighted and diffusion-weighted magnetic resonance imaging (MRI) alone

OBJECTIVE

To examine the performance of T2-weighted (T2W) and diffusion-weighted (DW) magnetic resonance imaging (MRI) for detecting the index tumour in patients with prostate cancer and to examine the agreement between MRI and histology when assessing tumour volume (TV) and overall tumour burden.

PATIENTS AND METHODS

The study included 199 consecutive patients with biopsy confirmed prostate cancer randomised to MRI before radical prostatectomy from December 2009 to July 2012. MRI-detected tumours (MRTs) were ranked from 1 to 3 according to decreasing volume and were compared with histologically detected tumours (HTs) ranked from 1 to 3, with HT 1 = index tumour. Whole-mount section histology was used as a reference standard. The TVs of true-positive MRTs (MRTVs 1-3) were compared with the TVs found by histology (HTVs 1-3). All tumours were registered on a 30-sector map and by classifying each sector as positive/negative, the rate of true-positive and -negative sectors was calculated.

RESULTS

The detection rate for the HT 1 (index tumour) was 92%; HT 2, 45%; and HT 3, 37%. The MRTV 1-3 vs the HTV 1-3 were 2.8 mL vs 4.0 mL (index tumour, P < 0.001), 1.0 mL vs 0.9 mL (tumour 2, P = 0.413), and 0.6 mL vs 0.5 mL (tumour 3, P = 0.492). The rate of true-positive and -negative sectors was 50% and 88%, κ = 0.39.

CONCLUSION

A combination of T2W and DW MRI detects the index tumour in 92% of cases, although MRI underestimates both TV and tumour burden compared with histology.

Computer aided-diagnosis of prostate cancer on multiparametric MRI: a technical review of current research

Prostate cancer (PCa) is the most commonly diagnosed cancer among men in the United States. In this paper, we survey computer aided-diagnosis (CADx) systems that use multiparametric magnetic resonance imaging (MP-MRI) for detection and diagnosis of prostate cancer. We review and list mainstream techniques that are commonly utilized in image segmentation, registration, feature extraction, and classification. The performances of 15 state-of-the-art prostate CADx systems are compared through the area under their receiver operating characteristic curves (AUC). Challenges and potential directions to further the research of prostate CADx are discussed in this paper. Further improvements should be investigated to make prostate CADx systems useful in clinical practice.

How accurate is multiparametric MR imaging in evaluation of prostate cancer volume?

PURPOSE

To assess the factors influencing multiparametric (MP) magnetic resonance (MR) imaging accuracy in estimating prostate cancer histologic volume (Vh).

MATERIALS AND METHODS

A prospective database of 202 patients who underwent MP MR imaging before radical prostatectomy was retrospectively used. Institutional review board approval and informed consent were obtained. Two independent radiologists delineated areas suspicious for cancer on images (T2-weighted, diffusion-weighted, dynamic contrast material-enhanced [DCE] pulse sequences) and scored their degree of suspicion of malignancy by using a five-level Likert score. One pathologist delineated cancers on whole-mount prostatectomy sections and calculated their volume by using digitized planimetry. Volumes of MR true-positive lesions were measured on T2-weighted images (VT2), on ADC maps (VADC), and on DCE images [VDCE]). VT2, VADC, VDCE and the greatest volume determined on images from any of the individual MR pulse sequences (Vmax) were compared with Vh (Bland-Altman analysis). Factors influencing MP MR imaging accuracy, or A, calculated as A = Vmax/Vh, were evaluated using generalized linear mixed models.

RESULTS

For both readers, Vh was significantly underestimated with VT2 (P < .0001, both), VADC (P < .0001, both), and VDCE (P = .02 and P = .003, readers 1 and 2, respectively), but not with Vmax (P = .13 and P = .21, readers 1 and 2, respectively). Mean, 25th percentile, and 75th percentile, respectively, for Vmax accuracy were 0.92, 0.54, and 1.85 for reader 1 and 0.95, 0.57, and 1.77 for reader 2. At generalized linear mixed (multivariate) analysis, tumor Likert score (P < .0001), Gleason score (P = .009), and Vh (P < .0001) significantly influenced Vmax accuracy (both readers). This accuracy was good in tumors with a Gleason score of 7 or higher or a Likert score of 5, with a tendency toward underestimation of Vh; accuracy was poor in small (<0.5 cc) or low-grade (Gleason score ≤6) tumors, with a tendency toward overestimation of Vh.

CONCLUSION

Vh can be estimated by using Vmax in aggressive tumors or in tumors with high Likert scores.

Prostate tumour volumes: evaluation of the agreement between magnetic resonance imaging and histology using novel co-registration software

OBJECTIVE

To evaluate the agreement between prostate tumour volume determined using multiparametric magnetic resonance imaging (MRI) and that determined by histological assessment, using detailed software-assisted co-registration.

MATERIALS AND METHODS

A total of 37 patients who underwent 3T multiparametric MRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC], dynamic contrast-enhanced [DCE] imaging) were included. A radiologist traced the borders of suspicious lesions on T2WI and ADC and assigned a suspicion score of between 2 and 5, while a uropathologist traced the borders of tumours on histopathological photographs. Software was used to co-register MRI and three-dimensional digital reconstructions of radical prostatectomy specimens and to compute imaging and histopathological volumes. Agreement in volumes between MRI and histology was assessed using Bland-Altman plots and stratified by tumour characteristics.

RESULTS

Among 50 tumours, the mean differences (95% limits of agreement) in MRI relative to histology were -32% (-128 to +65%) on T2WI and -47% (-143 to +49%) on ADC. For all tumour subsets, volume underestimation was more marked on ADC maps (mean difference ranging from -57 to -16%) than on T2WI (mean difference ranging from -45 to +2%). The 95% limits of agreement were wide for all comparisons, with the lower 95% limit ranging between -77 and -143% across assessments. Volume underestimation was more marked for tumours with a Gleason score ≥7 or a MRI suspicion score 4 or 5.

CONCLUSION

Volume estimates of prostate cancer using MRI tended to substantially underestimate histopathological volumes, with a wide variability in extent of underestimation across cases. These findings have implications for efforts to use MRI to guide risk assessment.

Defining the radiobiology of prostate cancer progression: An important question in translational prostate cancer research

Prostate cancer is one of the most common malignancies affecting men worldwide. High mortality rates from advanced and metastatic prostate cancer in the United States are contrasted by a relatively indolent course in the majority of cases. This gives hope for finding methods that could direct personalized diagnostic, preventative, and treatment approaches to patients with prostate cancer. Recent advances in multiparametric magnetic resonance imaging (MP-MRI) offer a noninvasive diagnostic intervention which allows correlation of prostate tumor image characteristics with underlying biologic evidence of tumor progression. The power of MP-MRI includes examination of both local invasion and nodal disease and might overcome the challenges of analyzing the multifocal nature of prostate cancer. Future directions include a careful analysis of the genomic signature of individual prostatic lesions utilizing image-guided biopsies. This review examines the diagnostic potential of MRI in prostate cancer.

Multiparametric MRI in prostate cancer management

Prostate cancer is the second most common cancer in men worldwide. The clinical behaviour of prostate cancer ranges from low-grade indolent tumours that never develop into clinically significant disease to aggressive, invasive tumours that may progress rapidly to metastatic disease and death. Therefore, there is an urgent clinical need to detect high-grade cancers and to differentiate them from the indolent, slow-growing tumours. Conventional methods of cancer detection-such as levels of prostate-specific antigen (PSA) in serum, digital rectal examination, and random biopsies-are limited in their sensitivity, specificity, or both. The combination of conventional anatomical MRI and functional magnet resonance sequences-known as multiparametric MRI (mp-MRI)-is emerging as an accurate tool for identifying clinically relevant tumours owing to its ability to localize them. In this Review, we discuss the value of mp-MRI in localized and metastatic prostate cancer, highlighting its role in the detection, staging, and treatment planning of prostate cancer.

Influence of magnetic resonance imaging in the decision to preserve or resect neurovascular bundles at robotic assisted laparoscopic radical prostatectomy

PURPOSE

We evaluated the accuracy of preoperative multiparametric 3.0-T magnetic resonance imaging for local staging of prostate cancer and its influence in the decision to preserve neurovascular bundles at robotic assisted laparoscopic radical prostatectomy.

MATERIALS AND METHODS

The study included 353 patients who had confirmed prostate cancer and underwent preoperative magnetic resonance imaging and robotic assisted laparoscopic radical prostatectomy between 2008 and 2011. The extent of neurovascular bundle sparing was initially determined on the basis of the clinical information and the nerve sparing surgical plan was reevaluated after review of the magnetic resonance imaging report. The value of preoperative magnetic resonance imaging in the prediction of extracapsular extension and in the decision of surgical plan according to D'Amico risk classification was analyzed.

RESULTS

The magnetic resonance imaging performed correct staging, over staging and under staging in 261 (73.9%), 43 (12.2%), and 49 (13.9%) patients, respectively. After review of the magnetic resonance imaging reports, the initial surgical plan was not changed in 260 patients (74%) and was changed in 93 patients (26%). Robotic assisted laparoscopic radical prostatectomy was changed to a more preservable neurovascular bundle sparing procedure in 53 patients (57%) and changed to a more aggressive neurovascular bundle resecting procedure in 40 patients (43%). For the patients with a change to more conservative surgery, the appropriateness was 91%. The sensitivity of magnetic resonance imaging in predicting extracapsular extension showed a tendency to increase from low to high risk groups (33%, 46%, 80%, respectively, p <0.001). In intermediate and high risk groups, there was a surgical plan change in 40 patients (of 129, 31%) and 27 patients (of 67, 40%), respectively.

CONCLUSIONS

Preoperative magnetic resonance imaging significantly improves the decision making to preserve or resect the neurovascular bundle at robotic assisted laparoscopic radical prostatectomy, which lacks haptic feedback.

The role of magnetic resonance imaging in the diagnosis and management of prostate cancer

BACKGROUND

The diagnosis of prostate cancer has long been plagued by the absence of an imaging tool that reliably detects and localises significant tumours. Recent evidence suggests that multi-parametric MRI could improve the accuracy of diagnostic assessment in prostate cancer. This review serves as a background to a recent USANZ position statement. It aims to provide an overview of MRI techniques and to critically review the published literature on the clinical application of MRI in prostate cancer.

TECHNICAL ASPECTS

The combination of anatomical (T2-weighted) MRI with at least two of the three functional MRI parameters - which include diffusion-weighted imaging, dynamic contrast-enhanced imaging and spectroscopy - will detect greater than 90% of significant (moderate to high risk) tumours; however MRI is less reliable at detecting tumours that are small (<0.5 cc), low grade (Gleason score 6) or in the transitional zone. The higher anatomical resolution provided by 3-Tesla magnets and endorectal coils may improve the accuracy, particularly in primary tumour staging.

SCREENING

The use of mpMRI to determine which men with an elevated PSA should undergo biopsy is currently the subject of two large clinical trials in Australia. MRI should be used with caution in this setting and then only in centres with established uro-radiological expertise and quality control mechanisms in place. There is sufficient evidence to justify using MRI to determine the need for repeat biopsy and to guide areas in which to focus repeat biopsy.

IMAGE-DIRECTED BIOPSY

MRI-directed biopsy is an exciting concept supported by promising early results, but none of the three proposed techniques have so far been proven superior to standard biopsy protocols. Further evidence of superior accuracy and core-efficiency over standard biopsy is required, before their costs and complexities in use can be justified.

TREATMENT SELECTION AND PLANNING

When used for primary-tumour staging (T-staging), MRI has limited sensitivity for T3 disease, but its specificity of greater than 95% may be useful in men with intermediate-high risk disease to identify those with advanced T3 disease not suitable for nerve sparing or for surgery at all. MRI appears to be of value in planning dosimetry in men undergoing radiotherapy, and in guiding selection for and monitoring on active surveillance.

Can 3T multiparametric magnetic resonance imaging accurately detect prostate cancer extracapsular extension?

BACKGROUND

Accurate staging is essential to determine the correct management of patients diagnosed with prostate cancer. We assess the accuracy of 3T multiparametric magnetic resonance imaging (MRI) with endorectal coil (3TemMRI) in detecting prostate cancer local extension.

METHODS

We retrospectively reviewed charts from January 2008 to July 2012 from all patients undergoing radical prostatectomy. Patients were only included if 3TemMRI and radical prostatectomy were performed at our institution. Based on the presence of extracapsular extension (ECE) at 3TemMRI, prostate cancer was dichotomized into locally advanced or organ-confined disease. The accuracy of 3TemMRI local staging was then evaluated using definitive pathology as a reference.

RESULTS

Overall, 177 radical prostatectomies were performed within the timeframe. After applying exclusion criteria, 60 patients were included in the final analysis. The mean patient age was 67 ± 7 (standard deviation) years. Mean prostate-specific antigen value was 12.7 ± 12.7 ng/L. Based on preoperative characteristics, we considered 38 of the 60 patients (63%) patients high risk. 3TemMRI identified an organ-confined tumour in 46 patients and locally advanced disease in 14 patients. When correlated to final pathology, 3TemMRI specificity, sensitivity, negative and positive predictive values, and accuracy in detecting locally advanced prostate cancer were 90%, 35%, 57%, 79% and 62%, respectively.

INTERPRETATION

This study shows that the use of preoperative 3TemMRI can be used to identify organ-confined prostate cancer when locally advanced disease is suspected.

MRI scans significantly change target coverage decisions in radical radiotherapy for prostate cancer

INTRODUCTION

Conventional clinical staging for prostate cancer has many limitations. This study evaluates the impact of adding MRI scans to conventional clinical staging for guiding decisions about radiotherapy target coverage.

METHODS

This was a retrospective review of 115 patients who were treated between February 2002 and September 2005 with radical radiotherapy for prostate cancer. All patients had MRI scans approximately 2 weeks before the initiation of radiotherapy. The T stage was assessed by both conventional clinical methods (cT-staging) as well as by MRI (mT-staging). The radiotherapy target volumes were determined first based on cT-staging and then taking the additional mT staging into account. The number of times extracapsular extension or seminal vesicle invasion was incorporated into target volumes was quantified based on both cT-staging and the additional mT-staging.

RESULTS

Extracapsular extension was incorporated into target volumes significantly more often with the addition of mT-staging (46 patients (40%) ) compared with cT-staging alone (37 patients (32%) ) (P = 0.002). Seminal vesicle invasion was incorporated into target volumes significantly more often with the addition of mT-staging (21 patients (18%) ) compared with cT-staging alone (three patients (3%) ) (P < 0.001). A total of 23 patients (20%) had changes to their target coverage based on the mT-staging.

CONCLUSIONS

MRI scans can significantly change decisions about target coverage in radical radiotherapy for prostate cancer.

Functional and molecular imaging: applications for diagnosis and staging of localised prostate cancer

Prostate cancer is currently the most common solid organ cancer type among men in the Western world. Currently, all decision-making algorithms and nomograms rely on demographics, clinicopathological data and symptoms. Such an approach can easily miss significant cancers while detecting many insignificant cancers. In this review, novel functional and molecular imaging techniques used in the diagnosis and staging of localised prostate cancer and their effect on treatment decisions are discussed.