Diffusion-weighted magnetic resonance imaging: a potential non-invasive marker of tumour aggressiveness in localized prostate cancer

Texture analysis of apparent diffusion coefficient maps: can it identify nonresponse to neoadjuvant chemotherapy for additional radiation therapy in rectal cancer patients?

Background

Neoadjuvant chemotherapy (NCT) alone can achieve comparable treatment outcomes to chemoradiotherapy in locally advanced rectal cancer (LARC) patients. This study aimed to investigate the value of texture analysis (TA) in apparent diffusion coefficient (ADC) maps for identifying non-responders to NCT.

Methods

This retrospective study included patients with LARC after NCT, and they were categorized into nonresponse group (pTRG 3) and response group (pTRG 0-2) based on pathological tumor regression grade (pTRG). Predictive texture features were extracted from pre- and post-treatment ADC maps to construct a TA model using RandomForest. The ADC model was developed by manually measuring pre- and post-treatment ADC values and calculating their changes. Simultaneously, subjective evaluations based on magnetic resonance imaging assessment of TRG were performed by two experienced radiologists. Model performance was compared using the area under the curve (AUC) and DeLong test.

Results

A total of 299 patients from two centers were divided into three cohorts: the primary cohort (center A; n = 194, with 36 non-responders and 158 responders), the internal validation cohort (center A; n = 49, with 9 non-responders) and external validation cohort (center B; n = 56, with 33 non-responders). The TA model was constructed by post_mean, mean_change, post_skewness, post_entropy, and entropy_change, which outperformed both the ADC model and subjective evaluations with an impressive AUC of 0.997 (95% confidence interval [CI], 0.975-1.000) in the primary cohort. Robust performances were observed in internal and external validation cohorts, with AUCs of 0.919 (95% CI, 0.805-0.978) and 0.938 (95% CI, 0.840-0.985), respectively.

Conclusions

The TA model has the potential to serve as an imaging biomarker for identifying nonresponse to NCT in LARC patients, providing a valuable reference for these patients considering additional radiation therapy.

The impact of the apparent diffusion coefficient for the early prediction of the treatment response after definitive radiotherapy in prostate cancer patients

PURPOSE

We assessed early changes in apparent diffusion coefficient (ADC) and serum prostate specific antigen (PSA) values after definitive radiotherapy (RT) without androgen deprivation treatment in low- and intermediate-risk prostate cancer (PC) patients.

MATERIALS AND METHODS

The clinical data and ADC parameters of 229 PC patients were retrospectively evaluated. Pre-treatment and post-treatment serum PSA and primary tumor ADC values were calculated. Post-treatment DW-MRI was performed median 4.1 months after completion of definitive RT. The prognostic factors predicting freedom from biochemical failure (FFBF) and progression-free survival (PFS) were analyzed using univariable and multivariable analyses.

RESULTS

With a median follow-up time of 80.8 months, the 5-year FFBF and PFS rates were 95.9% and 89.3%, respectively. Eleven patients (4.8%) had PSA relapse, with a median of 34.4 months after the completion of RT. A statistically significant difference in post-treatment ADC values was noted between patients with and without recurrence (0.94 ± 0.07 vs. 1.10 ± 0.20 × 10^-3 mm²/sec; p < 0.001). Patients with a Gleason score (GS) of 6 and low-risk disease had significantly higher post-treatment tumor ADC and PSA levels than patients with a GS of 7 and intermediate-risk disease. The 5-year FFBF rate in patients with tumor ADC ≤ 0.96 × 10^-3 mm²/sec was significantly lower than patients with tumor ADC > 0.96 × 10^-3 mm²/sec (85.5% vs. 100; p < 0.001). In the multivariable analysis, a lower ADC value, GS 4 + 3 and intermediate-risk disease were independent predictors of worse FFBF. In the multivariate analysis, a lower post-treatment ADC value and a GS of 4+3 were significant prognostic factors for a lower PFS.

CONCLUSION

These findings suggest that the post-treatment tumor ADC value could be used for early treatment response evaluation after definitive RT in PC patients.

The prognostic value of mean apparent diffusion coefficient measured with diffusion-weighted magnetic resonance image in patients with prostate cancer treated with definitive radiotherapy

PURPOSE

To assess the correlation between initial tumor apparent diffusion coefficient (ADC) values and clinicopathological parameters in prostate cancer (PCa) patients treated with definitive radiotherapy (RT). Additionally, the prognostic factors for freedom from biochemical failure (FFBF) and progression-free survival (PFS) in this patient cohort were analyzed.

MATERIALS AND METHODS

The clinical data of 503 patients with biopsy-confirmed PCa were evaluated retrospectively. All patients had clearly evident tumors on diffusion-weighted magnetic resonance imaging (DW-MRI) for ADC values. Univariable and multivariable analyses were used to determine prognostic factors for FFBF and PFS.

RESULTS

The median follow-up was 72.9 months. The 5-year FFBF and PFS rates were 93.2% and 86.2%, respectively. Significantly lower ADC values were found in patients with a high PSA level; advanced clinical stage; higher ISUP score, and higher risk group than their counterparts. Receiver operating characteristic (ROC) curve analysis revealed an ADC cut-off value of 0.737 × 10^-3 mm²/sec for tumor recurrence. Patients who progressed had a lower mean ADC value than those who did not (0.712±0.158 vs. 1.365±0.227 × 10^-3 mm²/sec; p<0.001). There was a significant difference in 5-year FFBF (96.3% vs. 90%; p<0.001) and PFSrates (83.8% vs. 73.5%; p=0.002) between patients with higher and lower mean ADC values. The FFBF and PFS were found to be correlated with tumor ADC value and ISUP grades in multivariable analysis. Additionally, older age was found to be a significant predictor of worse PFS.

CONCLUSIONS

Lower ADC values were found in patients with high-risk characteristics such as a high serum PSA level, stage or grade of tumor, or high-risk disease, implying that ADC values could be used to predict prognosis. Lower ADC values and higher ISUP grades were associated with an increased risk of BF and progression, implying that treatment intensification may be required in these patients.

Feasibility of diffusion weighting with a local inside-out nonlinear gradient coil for prostate MRI

PURPOSE

Prostate cancer remains the 2nd leading cancer killer of men, yet it is also a disease with a high rate of overtreatment. Diffusion weighted imaging (DWI) has shown promise as a reliable, grade-sensitive imaging method, but it is limited by low image quality. Currently, DWI quality image is directly related to low gradient amplitudes, since weak gradients must be compensated with long echo times.

METHODS

We propose a new type of MRI accessory, an "inside-out" and nonlinear gradient, whose sole purpose is to deliver diffusion encoding to a region of interest. Performance was simulated in OPERA and the resulting fields were used to simulate DWI with two compartment and kurtosis models. Experiments with a nonlinear head gradient prove the accuracy of DWI and ADC maps diffusion encoded with nonlinear gradients.

RESULTS

Simulations validated thermal and mechanical safety while showing a 5 to 10-fold increase in gradient strength over prostate. With these strengths, lesion CNR in ADC maps approximately doubled for a range of anatomical positions. Proof-of-principle experiments show that spatially varying b-values can be corrected for accurate DWI and ADC.

CONCLUSIONS

Dedicated nonlinear diffusion encoding hardware could improve prostate DWI.

Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone

PURPOSE

To compare various models of diffusion-weighted imaging including mono-exponential, bi-exponential, diffusion kurtosis (DK) and fractional-order calculus (FROC) models in diagnosing prostate cancer (PCa) in transition zone (TZ) and distinguish the high-grade PCa [Gleason score (GS) ≥ 7] lesions from the total of low-grade PCa (GS ≤ 6) lesions and benign prostatic hyperplasia (BPH) in TZ.

METHODS

80 Patients with 103 lesions were included in this study. Nine metrics [including apparent diffusion coefficient (ADC) derived from mono-exponential model, slow diffusion coefficient (D_s), fast diffusion coefficient (D_f),, and f (the fraction of fast diffusion) from bi-exponential model; mean diffusivity (MD) and mean kurtosis (MK) from DK model; diffusion coefficient (D), fractional-order derivative in space (β), and spatial metric (μ) from FROC model] were calculated. Comparisons between BPH and PCa lesions as well as between clinically significant PCa (CsPCa) (GS ≥ 7, n = 31) and clinically insignificant lesions (Cins) (GS ≤ 6 and BPH, n = 72) of these metrics were conducted. Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were used for statistical evaluations.

RESULTS

The areas under the ROC curve (AUC) values of β derived from FROC model were 0.778 and 0.853 in differentiating PCa from BPH and in differentiating CS (GS ≥ 7) from Cins (GS ≤ 6 and BPH), both were the highest compared to other metrics. The AUC value of β was significantly higher than that of ADC (P = 0.009) in differentiating CS from Cins, while the differentiation between BPH and PCa did not reach the statistical significance when comparing with ADC (P = 0.089).

CONCLUSION

Although no significant difference was found in distinguishing PCa from BPH, the metric β derived from FROC model was superior to other diffusion metrics in differentiation between CS and Cins in TZ.

Gleason Grade Group Concordance between Preoperative Targeted Biopsy and Radical Prostatectomy Histopathologic Analysis: A Comparison Between In-Bore MRI-guided and MRI-Transrectal US Fusion Prostate Biopsies

Purpose

To determine and compare rates of grade group (GG) discrepancies between different targeted biopsy techniques (in-bore vs fusion) after propensity score weighting using whole-mount radical prostatectomy (RP) histopathologic analysis as the reference standard.

Materials and Methods

This retrospective study evaluated men who underwent targeted (fusion or in-bore) biopsy between April 2017 and January 2019 followed by prostatectomy. The primary endpoint of the study was a change in GG from biopsy to RP at a patient level. For downgrade and upgrade analysis, men with biopsy GG1 (downgrade not possible) and GG5 (upgrade not possible) were excluded, respectively. GG upgrade, downgrade, and concordance rates of each targeting approach were compared using propensity score weighting and logistic regression with inverse probability of treatment weighting. Significance level was set at .05. Index lesion GG on RP specimen served as the reference standard.

Results

A total of 191 men (90 in the in-bore [mean age, 63 years ± 7 (standard deviation)] and 101 in the fusion biopsy group [mean age, 65 years ± 7]) were eligible and included. Fewer GG upgrades were noted in the in-bore biopsy group (14%; 12 of 85) compared with the fusion plus systematic biopsy group (30%; 28 of 93) (P = .012). The incidence of GG downgrade in the in-bore group (25%; 21 of 84) was higher than in the fusion group (17%; 16 of 93); however, the difference was not statistically significant (P = .2). Of the 77 men misclassified by both biopsy techniques, the majority (56%, n = 43) had a change in GG of 2 to 3 or 3 to 2.

Conclusion

Superior sampling accuracy with MRI-guided in-bore biopsies offers a lower incidence of GG upgrades compared with MRI-transrectal US fusion biopsies upon RP.Keywords: Biopsy/Needle Aspiration, MR-Imaging, Oncology, Pathology, Prostate Supplemental material is available for this article.© RSNA, 2021.

Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mappings - what is the potential to increase the tumor control probability?

BACKGROUND AND PURPOSE

The aim of this study was to evaluate the potential to increase the tumor control probability (TCP) with 'dose painting by numbers' (DPBN) plans optimized in a treatment planning system (TPS) compared to uniform dose plans. The DPBN optimization was based on our earlier published formalism for prostate cancer that is driven by dose-responses of Gleason scores mapped from apparent diffusion coefficients (ADC).

MATERIAL AND METHODS

For 17 included patients, a set of DPBN plans were optimized in a TPS by maximizing the TCP for an equal average dose to the prostate volume (CTVT) as for a conventional uniform dose treatment. For the plan optimizations we applied different photon energies, different precisions for the ADC-to-Gleason mappings, and different CTVT positioning uncertainties. The TCP increasing potential was evaluated by the DPBN efficiency, defined as the ratio of TCP increases for DPBN plans by TCP increases for ideal DPBN prescriptions (optimized without considering radiation transport phenomena, uncertainties of the CTVT positioning, and uncertainties of the ADC-to-Gleason mapping).

RESULTS

The median DPBN efficiency for the most conservative planning scenario optimized with a low precision ADC-to-Gleason mapping, and a positioning uncertainty of 0.6 cm was 10%, meaning that more than half of the patients had a TCP gain of at least 10% of the TCP for an ideal DPBN prescription. By increasing the precision of the ADC-to-Gleason mapping, and decreasing the positioning uncertainty the median DPBN efficiency increased by up to 40%.

CONCLUSIONS

TCP increases with DPBN plans optimized in a TPS were found more likely with a high precision mapping of image data into dose-responses and a high certainty of the tumor positioning. These findings motivate further development to ensure precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor positioning when implementing DPBN clinically.

Comparison of single-scanner single-protocol quantitative ADC measurements to ADC ratios to detect clinically significant prostate cancer

BACKGROUND

Mean ADC has high predictive value for the presence of clinically significant prostate cancer (sPC). Measurement variability is introduced by different scanners, protocols, intra-and inter-patient variation. Internal calibration by ADC ratios can address such fluctuations however can potentially lower the biological value of quantitative ADC determination by being sensitive to deviations in reference tissue signal.

PURPOSE

To better understand the predictive value of quantitative ADC measurements in comparison to internal reference ratios when measured in a single scanner, single protocol setup.

MATERIALS AND METHODS

284 consecutive patients who underwent 3 T MRI on a single scanner followed by MRI-transrectal ultrasound fusion biopsy were included. A board-certified radiologist retrospectively reviewed all MRIs blinded to clinical information and placed regions of interest (ROI) on all focal lesions and the following reference regions: normal-appearing peripheral zone (PZNL) and transition zone (TZNL), the urinary bladder (BLA), and right and left internal obturator muscle (RIOM, LIOM). ROI-based mean ADC and ADC ratios to the reference regions were compared regarding their ability to predict the aggressiveness of prostate cancer. Spearman's rank correlation coefficient was used to estimate the correlation between ADC parameters, Gleason score (GS) and ADC ratios. The primary endpoint was presence of sPC, defined as a GS ≥ 3 + 4. Univariable and multivariable logistic regression models were constructed to predict sPC. Receiver operating characteristics curves (ROC) were used for visualization; DeLong test was used to evaluate the differences of the area under the curve (AUC). Bias-corrected AUC values and corresponding 95 %-CI were calculated using bootstrapping with 100 bootstrap samples.

RESULTS

After exclusion of patients who received prior treatment, 259 patients were included in the final cohort of which 220 harbored 351 MR lesions. Mean ADC and ADC ratios demonstrated a negative correlation with the GS. Mean ADC had the strongest correlation with ρ of -0.34, followed by ADCratioPZNL (ρ=-0.32). All ADC parameters except ADCratioLIOM (p = 0.07) were associated with sPC p<0.05). Mean ADC and ADCratioPZNL had the highest ROC AUC of all parameters (0.68). Multivariable models with mean ADC improve predictive performance.

CONCLUSIONS

A highly standardized single-scanner mean ADC measurement could not be improved upon using any of the single ADC ratio parameters or combinations of these parameters in predicting the aggressiveness of prostate cancer.

Phantom Studies of Fused-Data TREIT Using Only Biopsy-Probe Electrodes

Transrectal electrical impedance tomography (TREIT) is a novel imaging modality being developed for prostate biopsy guidance and cancer characterization. We describe a novel fused-data TREIT (fd-TREIT) system and approach developed to improve imaging robustness and evaluate it on challenging clinically-representative phantoms. The new approach incorporates 8 electrodes (in 2 rows) on a biopsy probe (BP) and 12 electrodes on the face of a transrectal ultrasound (TRUS) probe and includes a biopsy gun, instrument tracking, 3D-printed needle guide, and EIT hardware and software. The approach was evaluated via simulation, a series of prostate-shaped gel phantoms, and an ex vivo bovine tissue sample using only absolute reconstructions. The simulations surprisingly found that using only biopsy-probe electrode measurements, i.e. omitting TRUS-probe electrode measurements, significantly improves robustness to noise thus leading to simpler modeling and significant decreases in computational times (~13x speed-up/reconstructions in ~27 minutes). The gel phantom experiments resulted in reconstructions with area under the curve (AUC) values extracted from receiver operator characteristic curves of >0.85 for 4 out of the 5 tests, and when incorporating inclusion boundaries resulted in absolute reconstructions yielding 1.9% and 12.2% average percent errors for 3 consistent tests and all 5 tests, respectively. Ex vivo bovine tests revealed qualitatively that the fd-TREIT approach can largely discriminate a complex adipose and muscle interface in a realistic setting using data from 9 biopsy probe states (biopsy core locations). The algorithms developed here on challenging phantoms suggest strong promise for this technology to aid in imaging during routine 12-core biopsies.

Active Surveillance of Prostate Cancer Using Multiparametric Magnetic Resonance Imaging: A Review of the Current Role and Future Perspectives

Clinically, active surveillance involves continuous monitoring of patients who may be at risk for disease. Patients with low-grade and early-stage prostate cancer may benefit from active surveillance, rather than undergoing surgical and medical treatments that are associated with side effects. In these cases, the role of active surveillance is to ensure that there is no progression of the disease. However, active surveillance may be associated with a risk of under-diagnosis. Previously, the assignment of risk categories and patient monitoring were based on digital rectal examination, transrectal prostate biopsy, and monitoring of serum levels of prostate-specific antigen (PSA). Multiparametric magnetic resonance imaging (MRI) of the prostate gland has an estimated negative predictive value of 95% for the detection of prostate cancer, which makes this an effective imaging method for targeting biopsies and for monitoring patients over time. Also, multiparametric MRI-guided biopsy at the initial stage of the risk stratification for patients who are newly diagnosed with prostate cancer may reduce the number of underdiagnosed patients, improve long-term patient prognosis, and reduce the number of patients who are overtreated, which may reduce healthcare costs and reduce treatment morbidity. For these reasons, multiparametric MRI has become an accepted monitoring tool in patients who are enrolled in active surveillance programs. This review aims to present the current status of the use of multiparametric MRI in active surveillance of prostate cancer and to discuss future perspectives, supported by recent literature.

DWI and PRECISE criteria in men on active surveillance for prostate cancer: A multicentre preliminary experience of different ADC calculations

PURPOSE

The PRECISE score estimates the likelihood of radiological progression in patients on active surveillance (AS) for prostate cancer (PCa) with serial multiparametric magnetic resonance imaging (mpMRI). A PRECISE score of 1 or 2 denotes radiological regression, PRECISE 3 indicates stability and PRECISE 4 or 5 implies progression. We evaluated the inter-reader reproducibility of different apparent diffusion coefficient (ADC) calculations and their relationship to the PRECISE score.

MATERIAL AND METHODS

Baseline and follow-up scans (on the same MR systems) of 30 patients with visible lesions from two different institutions (University College London and Sapienza University of Rome) were analysed by two radiologists (one from each site). The PRECISE score was initially assessed in consensus. At least six weeks later, to reduce the likelihood of being influenced by the consensus PRECISE reading, each radiologist independently calculated ADC for the following: lesion, non-cancerous tissue and urine in the bladder. Normalised ADC ratios were calculated with respect to normal prostatic tissue (npADC) and urine. Spearman's correlation (ρ), intraclass correlation coefficients (ICC), differences in ADC and ROC curves were computed.

RESULTS

Interobserver reproducibility was very good (ρ > 0.8; ICC > 0.90). Lesion ADC (0.91 vs 0.73 × 10-3 mm2/s; p=0.025) and npADC ratio (0.68 vs 0.53; p=0.012) at follow-up mpMRI were different between patients with radiological regression or stability vs progression. Cut-offs of 0.77 × 10-3 mm2/s (lesion ADC) and 0.59 (npADC ratio) could differentiate the two groups (area under the curve: 0.74 and 0.77, respectively).

CONCLUSION

The ADC, npADC ratio and the PRECISE score should be recorded for MRI-based AS.

Validation of T2- and diffusion-weighted magnetic resonance imaging for mapping intra-prostatic tumour prior to focal boost dose-escalation using intensity-modulated radiotherapy (IMRT)

BACKGROUND AND PURPOSE

To assess the diagnostic accuracy and inter-observer agreement of T2-weighted (T2W) and diffusion-weighted (DW) magnetic resonance imaging (MRI) for mapping intra-prostatic tumour lesions (IPLs) for the purpose of focal dose-escalation in prostate cancer radiotherapy.

MATERIALS AND METHODS

Twenty-six men selected for radical treatment with radiotherapy were recruited prospectively and underwent pre-treatment T2W+DW-MRI and 5 mm spaced transperineal template-guided mapping prostate biopsies (TTMPB). A 'traffic-light' system was used to score both data sets. Radiologically suspicious lesions measuring ≥0.5 cm3 were classified as red; suspicious lesions 0.2-0.5 cm3 or larger lesions equivocal for tumour were classified as amber. The histopathology assessment combined pathological grade and tumour length on biopsy (red = ≥4 mm primary Gleason grade 4/5 or ≥6 mm primary Gleason grade 3). Two radiologists assessed the MRI data and inter-observer agreement was measured with Cohens' Kappa co-efficient.

RESULTS

Twenty-five of 26 men had red image-defined IPLs by both readers, 24 had red pathology-defined lesions. There was a good correlation between lesions ≥0.5 cm3 classified "red" on imaging and "red" histopathology in biopsies (Reader 1: r = 0.61, p < 0.0001, Reader 2: r = 0.44, p = 0.03). Diagnostic accuracy for both readers for red image-defined lesions was sensitivity 85-86%, specificity 93-98%, positive predictive value (PPV) 79-92% and negative predictive value (NPV) 96%. Inter-observer agreement was good (Cohen's Kappa 0.61).

CONCLUSIONS

MRI is accurate for mapping clinically significant prostate cancer; diffusion-restricted lesions ≥0.5 cm3 can be confidently identified for radiation dose boosting.

Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis

The importance of Diffusion Weighted Imaging (DWI) in prostate cancer (PCa) diagnosis have been widely handled in literature. In the last decade, due to the mono-exponential model limitations, several studies investigated non-Gaussian DWI models and their utility in PCa diagnosis. Since their results were often inconsistent and conflicting, we performed a systematic review of studies from 2012 examining the most commonly used Non-Gaussian DWI models for PCa detection and characterization. A meta-analysis was conducted to assess the ability of each Non-Gaussian model to detect PCa lesions and distinguish between low and intermediate/high grade lesions. Weighted mean differences and 95% confidence intervals were calculated and the heterogeneity was estimated using the I² statistic. 29 studies were selected for the systematic review, whose results showed inconsistence and an unclear idea about the actual usefulness and the added value of the Non-Gaussian model parameters. 12 studies were considered in the meta-analyses, which showed statistical significance for several non-Gaussian parameters for PCa detection, and to a lesser extent for PCa characterization. Our findings showed that Non-Gaussian model parameters may potentially play a role in the detection and characterization of PCa but further studies are required to identify a standardized DWI acquisition protocol for PCa diagnosis.

Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging

Colorectal cancer (CRC) represents one of the leading causes of tumor-related deaths worldwide. Among the various tools at physicians’ disposal for the diagnostic management of the disease, tomographic imaging (e.g., CT, MRI, and hybrid PET imaging) is considered essential. The qualitative and subjective evaluation of tomographic images is the main approach used to obtain valuable clinical information, although this strategy suffers from both intrinsic and operator-dependent limitations. More recently, advanced imaging techniques have been developed with the aim of overcoming these issues. Such techniques, such as diffusion-weighted MRI and perfusion imaging, were designed for the “in vivo” evaluation of specific biological tissue features in order to describe them in terms of quantitative parameters, which could answer questions difficult to address with conventional imaging alone (e.g., questions related to tissue characterization and prognosis). Furthermore, it has been observed that a large amount of numerical and statistical information is buried inside tomographic images, resulting in their invisibility during conventional assessment. This information can be extracted and represented in terms of quantitative parameters through different processes (e.g., texture analysis). Numerous researchers have focused their work on the significance of these quantitative imaging parameters for the management of CRC patients. In this review, we aimed to focus on evidence reported in the academic literature regarding the application of parametric imaging to the diagnosis, staging and prognosis of CRC while discussing future perspectives and present limitations. While the transition from purely anatomical to quantitative tomographic imaging appears achievable for CRC diagnostics, some essential milestones, such as scanning and analysis standardization and the definition of robust cut-off values, must be achieved before quantitative tomographic imaging can be incorporated into daily clinical practice.

VCAM-1 Density and Tumor Perfusion Predict T-cell Infiltration and Treatment Response in Preclinical Models

Cancer immunotherapies have demonstrated durable responses in a range of different cancers. However, only a subset of patients responds to these therapies. We set out to test if non-invasive imaging of tumor perfusion and vascular inflammation may be able to explain differences in T-cell infiltration in pre-clinical tumor models, relevant for treatment outcomes. Tumor perfusion and vascular cell adhesion molecule (VCAM-1) density were quantified using magnetic resonance imaging (MRI) and correlated with infiltration of adoptively transferred and endogenous T-cells. MRI biomarkers were evaluated for their ability to detect tumor rejection 3 days after T-cell transfer. Baseline levels of these markers were used to assess their ability to predict PD-L1 treatment response. We found correlations between MRI-derived VCAM-1 density and infiltration of endogenous or adoptively transferred T-cells in some preclinical tumor models. Blocking T-cell binding to endothelial cell adhesion molecules (VCAM-1/ICAM) prevented T-cell mediated tumor rejection. Tumor rejection could be detected 3 days after adoptive T-cell transfer prior to tumor volume changes by monitoring the extracellular extravascular volume fraction. Imaging tumor perfusion and VCAM-1 density before treatment initiation was able to predict the response of MC38 tumors to PD-L1 blockade. These results indicate that MRI based assessment of tumor perfusion and VCAM-1 density can inform about the permissibility of the tumor vasculature for T-cell infiltration which may explain some of the observed variance in treatment response for cancer immunotherapies.

Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping

OBJECTIVE

This study aims for targeted biopsy validation of magnetic resonance fingerprinting (MRF) and diffusion mapping for characterizing peripheral zone (PZ) prostate cancer and noncancers.

MATERIALS AND METHODS

One hundred four PZ lesions in 85 patients who underwent magnetic resonance imaging were retrospectively analyzed with apparent diffusion coefficient (ADC) mapping, MRF, and targeted biopsy (cognitive or in-gantry). A radiologist blinded to pathology drew regions of interest on targeted lesions and visually normal peripheral zone on MRF and ADC maps. Mean T1, T2, and ADC were analyzed using linear mixed models. Generalized estimating equations logistic regression analyses were used to evaluate T1 and T2 relaxometry combined with ADC in differentiating pathologic groups.

RESULTS

Targeted biopsy revealed 63 cancers (low-grade cancer/Gleason score 6 = 10, clinically significant cancer/Gleason score ≥7 = 53), 15 prostatitis, and 26 negative biopsies. Prostate cancer T1, T2, and ADC (mean ± SD, 1660 ± 270 milliseconds, 56 ± 20 milliseconds, 0.70 × 10 ± 0.24 × 10 mm/s) were significantly lower than prostatitis (mean ± SD, 1730 ± 350 milliseconds, 77 ± 36 milliseconds, 1.00 × 10 ± 0.30 × 10 mm/s) and negative biopsies (mean ± SD, 1810 ± 250 milliseconds, 71 ± 37 milliseconds, 1.00 × 10 ± 0.33 × 10 mm/s). For cancer versus prostatitis, ADC was sensitive and T2 specific with comparable area under curve (AUC; (AUCT2 = 0.71, AUCADC = 0.79, difference between AUCs not significant P = 0.37). T1 + ADC (AUCT1 + ADC = 0.83) provided the best separation between cancer and negative biopsies. Low-grade cancer T2 and ADC (mean ± SD, 75 ± 29 milliseconds, 0.96 × 10 ± 0.34 × 10 mm/s) were significantly higher than clinically significant cancers (mean ± SD, 52 ± 16 milliseconds, 0.65 ± 0.18 × 10 mm/s), and T2 + ADC (AUCT2 + ADC = 0.91) provided the best separation.

CONCLUSIONS

T1 and T2 relaxometry combined with ADC mapping may be useful for quantitative characterization of prostate cancer grades and differentiating cancer from noncancers for PZ lesions seen on T2-weighted images.

Usefulness of diffusion-weighted MRI in the initial assessment of osseous sarcomas in children and adolescents

BACKGROUND

Concern regarding gadolinium deposition in the brain after repeated administration of intravenous gadolinium-based contrast agents has prompted evaluation of imaging alternatives.

OBJECTIVE

The study purpose was to determine if magnetic resonance imaging (MRI) using conventional sequences with diffusion-weighted imaging (DWI) instead of gadolinium-based contrast-enhanced MRI is valid for local staging and guiding biopsies in osseous sarcomas.

MATERIALS AND METHODS

Initial pretreatment MRI with DWI and gadolinium-based contrast-enhanced images in patients ≤ 18 years with histopathologically proven osseous sarcomas were included. Two radiologists blinded to collated demographic and clinical data, independently reviewed conventional/DWI and conventional/gadolinium-based contrast-enhanced MRI then conventional sequences alone, recording tumor size, skip lesions, necrosis, neurovascular invasion, enlarged lymph nodes and diffusion restriction. Discrepancies were resolved by a third reader. A single reader measured apparent diffusion coefficient (ADC) values in non-necrotic tumors, then correlated minimum ADC values -- with and without normalization to skeletal muscle -- with relative enhancement.

RESULTS

Twenty-one patients (mean age: 11.3±4.2 years, 15 [71%] females) had 14 osteosarcomas and 7 Ewing sarcomas, 50% centered in the femur. Conventional/DWI versus conventional/gadolinium-based contrast-enhanced MRI showed agreement for tumor size estimation with significant associations for necrosis (P=0.021), neurovascular involvement (P<0.001) and enlarged lymph nodes (P=0.005). Diagnostic accuracy of conventional/DWI is comparable to conventional/gadolinium-based contrast-enhanced MRI and superior to conventional sequences alone. Comparison between minimum ADC values and relative enhancement showed no correlation (P>0.05).

CONCLUSION

Significant associations of key imaging features in the initial assessment of osseous sarcomas support DWI as an alternative to gadolinium-based contrast-enhanced MRI. The lack of association between ADC values and relative enhancement suggests that they measure independent constructs, DWI dependent upon tumor cellularity and perfusion.

Probing structure of normal and malignant prostate tissue before and after radiation therapy with luminal water fraction and diffusion-weighted MRI

BACKGROUND

Interpretation of diffusion in conjunction with T2 -weighted MRI is essential for assessing prostate cancer; however, the combination of apparent diffusion coefficient (ADC) with quantitative T2 mapping remains unexplored.

PURPOSE

To document the T2 components and ADC of untreated and irradiated nonmalignant prostate tissue as a measure of their glandular luminal and cellular compartments and to compare values with those of tumor.

STUDY TYPE

Prospective.

POPULATION

Twenty-four men with prostate cancer (14 untreated; 10 with biochemical recurrence following radiation therapy).

FIELD STRENGTH/SEQUENCES

Endorectal 3 T MRI including a 32-echo gradient echo and spin echo (GRASE) and an 8 b-value diffusion-weighted sequence.

ASSESSMENT

Regions of interest were drawn on ADC maps and T2 -weighted images around focal lesions in areas of biopsy-positive prostate cancer and in nonmalignant areas of untreated and irradiated peripheral zone (PZ), and untreated transitional zone (TZ). Multiecho T2 data were fitted with mono-/biexponential decay and nonnegative least squares functions. The luminal water fraction (LWF) was derived.

STATISTICAL TESTS

The preference between mono- and biexponential decay was assessed using the Bayesian information criterion. Differences in fitted parameters between tissue types were compared (paired t-test within groups, Kruskal-Wallis and Wilcoxon rank-sum test between groups) and correlations between ADC and T2 components assessed (Spearman rank correlation test).

RESULTS

LWF in tumor (0.09) was significantly lower than in PZ or TZ (0.27 and 0.18, P < 0.01, respectively), but tumor values were comparable to nonmalignant irradiated prostate (0.08). The short T2 relaxation rate was lower in tumor than in nonmalignant untreated or irradiated tissue (significant compared with TZ, P = 0.01). There was a strong correlation between LWF and ADC in normal untreated tissue (r = 0.88, P < 0.001). This relationship was absent in nonmalignant irradiated prostrate (r = -0.35, P = 0.42) and in tumor (r = -0.04, P = 0.88).

DATA CONCLUSION

T2 components in conjunction with ADC can be used to characterize untreated and irradiated nonmalignant prostate and tumor. LWF is most useful at discriminating tumor in the untreated prostate.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:619-627.

Correlations between Apparent Diffusion Coefficient and Gleason Score in Prostate Cancer: A Systematic Review

BACKGROUND

Reported data regarding the associations between apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) and Gleason score in prostate cancer (PC) are inconsistent.

OBJECTIVE

The aim of the present systematic review was to analyze relationships between ADC and Gleason score in PC.

DESIGN, SETTING, AND PARTICIPANTS

MEDLINE library, SCOPUS, and EMBASE databases were screened for relationships between ADC and Gleason score in PC up to April 2018. Overall, 39 studies with 2457 patients were identified. Data on the following parameters were extracted from the literature: number of patients, cancer localization, and correlation coefficients between ADC and Gleason score.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations between ADC and Gleason score were analyzed by the Spearman's correlation coefficient.

RESULTS AND LIMITATIONS

In overall sample, the pooled correlation coefficient between ADC and Gleason score was -0.45 (95% confidence interval [CI]=[-0.50; -0.40]). In PC in the transitional zone, the pooled correlation coefficient was -0.22 (95% CI=[-0.47; 0.03]). In PC in the peripheral zone, the pooled correlation coefficient was -0.48 (95% CI=[-0.54; -0.42]).

CONCLUSIONS

In PC located in the peripheral zone, ADC correlated moderately with Gleason score. In PC located in the transitional zone, ADC correlated weakly with Gleason score.

PATIENT SUMMARY

We reviewed studies using apparent diffusion coefficient for the prediction of Gleason score in prostate cancer patients.

Amide proton transfer imaging to predict tumor response to neoadjuvant chemotherapy in locally advanced rectal cancer

BACKGROUND AND AIM

The amount of proteins and peptides can be estimated with amide proton transfer (APT) imaging. Previous studies demonstrated the usefulness of APT imaging to predict tumor malignancy. We determined whether APT imaging can predict the tumor response to neoadjuvant chemotherapy (NAC) in patients with locally advanced rectal cancer (LARC).

METHODS

Seventeen patients with LARC who underwent a pretherapeutic magnetic resonance examination including APT imaging and NAC (at least two courses) were enrolled. The APT-weighted imaging (WI) signal intensity (SI) (%) was defined as magnetization transfer ratio asymmetry (MTR_asym ) at the offset of 3.5 ppm. Each tumor was histologically evaluated for the degree of degeneration and necrosis and then classified as one of five histological Grades (0, none; 1a, less than 1/3; 1b, 1/3 to 2/3; 2, more than 2/3; 3, all). We compared the mean APTWI SIs of the tumors between the Grade 0/1a/1b (low-response group) and Grade 2/3 (high-response group) by Student's t-test. We used receiver operating characteristics curves to determine the diagnostic performance of the APTWI SI for predicting the tumor response.

RESULTS

The mean APTWI SI of the low-response group (n = 12; 3.05 ± 1.61%) was significantly higher than that of the high-response group (n = 5; 1.14 ± 1.13%) (P = 0.029). The area under the curve for predicting the tumor response using the APTWI SI was 0.87. When ≥2.75% was used as an indicator of low-response status, 75% sensitivity and 100% specificity of the APTWI SI were obtained.

CONCLUSION

Pretherapeutic APT imaging can predict the tumor response to NAC in patients with LARC.

Multiparametric Whole-body MRI with Diffusion-weighted Imaging and ADC Mapping for the Identification of Visceral and Osseous Metastases From Solid Tumors

RATIONALE AND OBJECTIVES

The purpose of this study was to investigate the use of multiparametric, whole-body, diffusion-weighted imaging (WB-DWI) and apparent diffusion coefficient (ADC) maps with T₂-weighted magnetic resonance imaging (MRI) at 3T for the detection and monitoring of metastatic disease in patients.

MATERIALS AND METHODS

Fifty-four participants (32 healthy subjects and 22 patients) were scanned with WB-DWI methods using a 3T MRI scanner. Axial, sagittal, or coronal fat-suppressed T₂-weighted (T₂WI), T₁-weighted (T₁WI), and DWI images were acquired. Total MRI acquisition and set-up time was approximately 45 minutes. Metastatic disease on MRI was confirmed based on T₂WI characteristics. The number of lesions was established on computed tomography (CT) or positron emission tomography (PET-CT). Whole-body ADC maps and T₂WI were constructed, and region-of-interests were drawn in normal and abnormal-appearing tissue for quantitative analysis. Statistical analysis was performed using a paired t tests and P < .05 was considered statistically significant.

RESULTS

There were 91 metastatic lesions detected from the CT or PET-CT with a missed recurrent lesion in the prostate. Multiparametric WB-MRI had excellent sensitivity (96%) for detection of metastatic lesions compared to CT. ADC map values and the ADC ratio in metastatic bone lesions were significantly increased (P < .05) compared to normal bone. In soft tissue, ADC map values and ratios in metastatic lesions were decreased compared to normal soft tissue.

CONCLUSION

We have demonstrated that multiparametric WB-MRI is feasible for oncologic staging to identify bony and visceral metastasis in breast, prostate, pancreatic, and colorectal cancers. WB-MRI can be tailored to fit the patient, such that an "individualized patient sequence" can be developed for a comprehensive evaluation for staging and response during treatment.

Characterization of prostate cancer with MR spectroscopic imaging and diffusion-weighted imaging at 3 Tesla

PURPOSE

To retrospectively measure metabolic ratios and apparent diffusion coefficient (ADC) values from 3-Tesla MR spectroscopic imaging (MRSI) and diffusion-weighted imaging (DWI) in benign and malignant peripheral zone (PZ) prostate tissue, assess the parameters' associations with malignancy, and develop and test rules for classifying benign and malignant PZ tissue using whole-mount step-section pathology as the reference standard.

METHODS

This HIPAA-compliant, IRB-approved study included 67 men (median age, 61 years; range, 41-74 years) with biopsy-proven prostate cancer who underwent preoperative 3 T endorectal multiparametric MRI and had ≥1 PZ lesion >0.1 cm³ at whole-mount histopathology. In benign and malignant PZ regions identified from pathology, voxel-based choline/citrate, polyamines/choline, polyamines/creatine, and (choline + polyamines + creatine)/citrate ratios were averaged, as were ADC values. Patients were randomly split into training and test sets; rules for separating benign from malignant regions were generated with classification and regression tree (CART) analysis and assessed on the test set for sensitivity and specificity. Odds ratios (OR) were evaluated using generalized estimating equations.

RESULTS

CART analysis of all parameters identified only ADC and (choline + polyamines + creatine)/citrate as significant predictors of cancer. Sensitivity and specificity, respectively, were 0.81 and 0.82 with MRSI-derived, 0.98 and 0.51 with DWI-derived, and 0.79 and 0.90 with MRSI + DWI-derived classification rules. Areas under the curves (AUC) in the test set were 0.93 (0.87-0.97) with ADC, 0.82 (0.72-0.91) with MRSI, and 0.96 (0.92-0.99) with MRSI + ADC.

CONCLUSION

We developed statistically-based rules for identifying PZ cancer using 3-Tesla MRSI, DWI, and MRSI + DWI and demonstrated the potential value of MRSI + DWI.

Clinical role of breast MRI now and going forward

Magnetic resonance imaging (MRI) is a well-established method in breast imaging, with manifold clinical applications, including the non-invasive differentiation between benign and malignant breast lesions, preoperative staging, detection of scar versus recurrence, implant assessment, and the evaluation of high-risk patients. At present, dynamic contrast-enhanced MRI is the most sensitive imaging technique for breast cancer diagnosis, and provides excellent morphological and to some extent also functional information. To compensate for the limited functional information, and to increase the specificity of MRI while preserving its sensitivity, additional functional parameters such as diffusion-weighted imaging and apparent diffusion coefficient mapping, and MR spectroscopic imaging have been investigated and implemented into the clinical routine. Several additional MRI parameters to capture breast cancer biology are still under investigation. MRI at high and ultra-high field strength and advances in hard- and software may also further improve this imaging technique. This article will review the current clinical role of breast MRI, including multiparametric MRI and abbreviated protocols, and provide an outlook on the future of this technique. In addition, the predictive and prognostic value of MRI as well as the evolving field of radiogenomics will be discussed.

Dose painting of prostate cancer based on Gleason score correlations with apparent diffusion coefficients

BACKGROUND

Gleason scores for prostate cancer correlates with an increased recurrence risk after radiotherapy (RT). Furthermore, higher Gleason scores correlates with decreasing apparent diffusion coefficient (ADC) data from diffusion weighted MRI (DWI-MRI). Based on these observations, we present a formalism for dose painting prescriptions of prostate volumes based on ADC images mapped to Gleason score driven dose-responses.

METHODS

The Gleason score driven dose-responses were derived from a learning data set consisting of pre-RT biopsy data and post-RT outcomes for 122 patients treated with a homogeneous dose to the prostate. For a test data set of 18 prostate cancer patients with pre-RT ADC images, we mapped the ADC data to the Gleason driven dose-responses by using probability distributions constructed from published Gleason score correlations with ADC data. We used the Gleason driven dose-responses to optimize dose painting prescriptions that maximize the tumor control probability (TCP) with equal average dose as for the learning sets homogeneous treatment dose.

RESULTS

The dose painting prescriptions increased the estimated TCP compared to the homogeneous dose by 0-51% for the learning set and by 4-30% for the test set. The potential for individual TCP gains with dose painting correlated with increasing Gleason score spread and larger prostate volumes. The TCP gains were also found to be larger for patients with a low expected TCP for the homogeneous dose prescription.

CONCLUSIONS

We have from retrospective treatment data demonstrated a formalism that yield ADC driven dose painting prescriptions for prostate volumes that potentially can yield significant TCP increases without increasing dose burdens as compared to a homogeneous treatment dose. This motivates further development of the approach to consider more accurate ADC to Gleason mappings, issues with delivery robustness of heterogeneous dose distributions, and patient selection criteria for design of clinical trials.

Ultrasound Shear Wave Elastography of the Normal Prostate: Interobserver Reproducibility and Comparison with Functional Magnetic Resonance Tissue Characteristics

The purpose of this study was to establish interobserver reproducibility of Young's modulus (YM) derived from ultrasound shear wave elastography (US-SWE) in the normal prostate and correlate it with multiparametric magnetic resonance imaging (mpMRI) tissue characteristics. Twenty men being screened for prostate cancer underwent same-day US-SWE (10 done by two blinded, newly-trained observers) and mpMRI followed by 12-core biopsy. Bland-Altman plots established limits of agreement for YM. Quantitative data from the peripheral zone (PZ) and the transitional zone (TZ) for YM, apparent diffusion coefficient (ADC, mm2/s from diffusion-weighted MRI), and Ktrans (volume transfer coefficient, min-1), Ve (extravascular-extracellular space, %), Kep (rate constant, /min), and initial area under the gadolinium concentration curve (IAUGC60, mmol/L/s) from dynamic contrast-enhanced MRI were obtained for slice-matched prostate sextants. Interobserver intraclass correlation coefficients were fair to good for individual regions (PZ = 0.57, TZ = 0.65) and for whole gland 0.67, (increasing to 0.81 when corrected for systematic observer bias). In the PZ, there were weak negative correlations between YM and ADC ( p = 0.008), and Ve ( p = 0.01) and a weak positive correlation with Kep ( p = 0.003). No significant intermodality correlations were seen in the TZ. Transrectal prostate US-SWE done without controlling manually applied probe pressure has fair/good interobserver reproducibility in inexperienced observers with potential to improve this to excellent by standardization of probe contact pressure. Within the PZ, increase in tissue stiffness is associated with reduced extracellular water (decreased ADC) and space (reduced Ve).

Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling

PURPOSE

To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors.

MATERIALS AND METHODS

Fifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation.

RESULTS

Systematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P < 0.05). Smaller value for MD measures and larger value for FA measures indicate the high risk. The models enrolling the measures achieve good fits and good classification performances (R²_adj = 0.55-0.60, AUC = 0.88-0.91), however the models using the measure ratios perform better (R²_adj = 0.59-0.75, AUC = 0.88-0.95). The model that employs the ratios of minimum MD and maximum FA accomplishes the highest sensitivity, specificity and accuracy (Se = 77.8%, Sp = 96.9% and Acc = 90.0%).

CONCLUSION

Joint evaluation of MD and FA diffusion tensor imaging measures is valuable to detect high GS risk group peripheral zone prostate tumors. However, use of the ratios of the measures improves the accuracy of the detections substantially. Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice.

Magnetic Resonance Imaging-Guided Adaptive Radiation Therapy: A "Game Changer" for Prostate Treatment?

Radiation therapy to the prostate involves increasingly sophisticated delivery techniques and changing fractionation schedules. With a low estimated α/β ratio, a larger dose per fraction would be beneficial, with moderate fractionation schedules rapidly becoming a standard of care. The integration of a magnetic resonance imaging (MRI) scanner and linear accelerator allows for accurate soft tissue tracking with the capacity to replan for the anatomy of the day. Extreme hypofractionation schedules become a possibility using the potentially automated steps of autosegmentation, MRI-only workflow, and real-time adaptive planning. The present report reviews the steps involved in hypofractionated adaptive MRI-guided prostate radiation therapy and addresses the challenges for implementation.

Magnetic resonance imaging in active surveillance-a modern approach

In recent years, active surveillance has been increasingly adopted as a conservative management approach to low and sometimes intermediate risk prostate cancer, to avoid or delay treatment until there is evidence of higher risk disease. A number of studies have investigated the role of multiparametric magnetic resonance imaging (mpMRI) in this setting. MpMRI refers to the use of multiple MRI sequences (T2-weighted anatomical and functional imaging which can include diffusion-weighted imaging, dynamic contrast enhanced imaging, spectroscopy). Each of the parameters investigates different aspects of the prostate gland (anatomy, cellularity, vascularity, etc.). In addition to a qualitative assessment, the radiologist can also extrapolate quantitative imaging biomarkers from these sequences, for example the apparent diffusion coefficient from diffusion-weighted imaging. There are many different types of articles (e.g., reviews, commentaries, consensus meetings, etc.) that address the use of mpMRI in men on active surveillance for prostate cancer. In this paper, we compare original articles that investigate the role of the different mpMRI sequences in men on active surveillance for prostate cancer, in order to discuss the relative utility of the different sequences, and combinations of sequences. We searched MEDLINE/PubMed for manuscripts published from inception to 1^st December 2017. The search terms used were (prostate cancer or prostate adenocarcinoma or prostatic carcinoma or prostate carcinoma or prostatic adenocarcinoma) and (MRI or NMR or magnetic resonance imaging or mpMRI or multiparametric MRI) and active surveillance. Overall, 425 publications were found. All abstracts were reviewed to identify papers with original data. Twenty-five papers were analysed and summarised. Some papers based their analysis only on one mpMRI sequence, while others assessed two or more. The evidence from this review suggests that qualitative assessments and quantitative data from different mpMRI sequences hold promise in the management of men on active surveillance for prostate cancer. Both qualitative and quantitative approaches should be considered when assessing mpMRI of the prostate. There is a need for robust studies assessing the relative utility of different combinations of sequences in a systematic manner to determine the most efficient use of mpMRI in men on active surveillance.

Non-Invasive Prostate Cancer Characterization with Diffusion-Weighted MRI: Insight from In silico Studies of a Transgenic Mouse Model

Diffusion-weighted magnetic resonance imaging (DWI) enables non-invasive, quantitative staging of prostate cancer via measurement of the apparent diffusion coefficient (ADC) of water within tissues. In cancer, more advanced disease is often characterized by higher cellular density (cellularity), which is generally accepted to correspond to a lower measured ADC. A quantitative relationship between tissue structure and in vivo measurements of ADC has yet to be determined for prostate cancer. In this study, we establish a theoretical framework for relating ADC measurements with tissue cellularity and the proportion of space occupied by prostate lumina, both of which are estimated through automatic image processing of whole-slide digital histology samples taken from a cohort of six healthy mice and nine transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. We demonstrate that a significant inverse relationship exists between ADC and tissue cellularity that is well characterized by our model, and that a decrease of the luminal space within the prostate is associated with a decrease in ADC and more aggressive tumor subtype. The parameters estimated from our model in this mouse cohort predict the diffusion coefficient of water within the prostate-tissue to be 2.18 × 10-3 mm2/s (95% CI: 1.90, 2.55). This value is significantly lower than the diffusion coefficient of free water at body temperature suggesting that the presence of organelles and macromolecules within tissues can drastically hinder the random motion of water molecules within prostate tissue. We validate the assumptions made by our model using novel in silico analysis of whole-slide histology to provide the simulated ADC (sADC); this is demonstrated to have a significant positive correlation with in vivo measured ADC (r2 = 0.55) in our mouse population. The estimation of the structural properties of prostate tissue is vital for predicting and staging cancer aggressiveness, but prostate tissue biopsies are painful, invasive, and are prone to complications such as sepsis. The developments made in this study provide the possibility of estimating the structural properties of prostate tissue via non-invasive virtual biopsies from MRI, minimizing the need for multiple tissue biopsies and allowing sequential measurements to be made for prostate cancer monitoring.

An improved model for prostate diffusion incorporating the results of Monte Carlo simulations of diffusion in the cellular compartment

The purpose of this work was to refine a previously published model of prostate diffusion by incorporating improved estimates of cellular diffusivity obtained by Monte Carlo simulation. Stromal and epithelial cell size and intracellular volume fraction in different grades of cancer were determined from histological images. Diffusion in different mixtures of cells, corresponding to different tumor grades, was simulated and cellular apparent diffusion coefficient and kurtosis values determined. These values were incorporated into the previously published model of prostate diffusion and model predictions compared with values found in the literature. Stromal cell radius and intracellular volume fraction were 3.74 ± 0.96 μm and 13 ± 3% respectively in normal peripheral zone (PZ), and were similar in all grades of cancer. Epithelial cell radius and intracellular volume fraction were 3.40 ± 0.15 μm and 45 ± 5% respectively in normal PZ, rising to 4.75 ± 0.20 μm and 70 ± 8% in high grade cancer. Cellular apparent diffusion coefficient and kurtosis were 1.02 μm² ms^-1 and 0.58 respectively in normal PZ, and 0.61 μm² ms^-1 and 1.15 in high grade cancer (variation in simulation values are less than 0.1%). Agreement between model predictions and measurements were good, with a mean square error of 0.22 μm² ms^-1 . Incorporation of cellular diffusion coefficient and kurtosis values obtained by Monte Carlo simulation into a model of prostate diffusion gives good agreement with published results.

Integrated radiomic framework for breast cancer and tumor biology using advanced machine learning and multiparametric MRI

Radiomics deals with the high throughput extraction of quantitative textural information from radiological images that not visually perceivable by radiologists. However, the biological correlation between radiomic features and different tissues of interest has not been established. To that end, we present the radiomic feature mapping framework to generate radiomic MRI texture image representations called the radiomic feature maps (RFM) and correlate the RFMs with quantitative texture values, breast tissue biology using quantitative MRI and classify benign from malignant tumors. We tested our radiomic feature mapping framework on a retrospective cohort of 124 patients (26 benign and 98 malignant) who underwent multiparametric breast MR imaging at 3 T. The MRI parameters used were T1-weighted imaging, T2-weighted imaging, dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted imaging (DWI). The RFMs were computed by convolving MRI images with statistical filters based on first order statistics and gray level co-occurrence matrix features. Malignant lesions demonstrated significantly higher entropy on both post contrast DCE-MRI (Benign-DCE entropy: 5.72 ± 0.12, Malignant-DCE entropy: 6.29 ± 0.06, p = 0.0002) and apparent diffusion coefficient (ADC) maps as compared to benign lesions (Benign-ADC entropy: 5.65 ± 0.15, Malignant ADC entropy: 6.20 ± 0.07, p = 0.002). There was no significant difference between glandular tissue entropy values in the two groups. Furthermore, the RFMs from DCE-MRI and DWI demonstrated significantly different RFM curves for benign and malignant lesions indicating their correlation to tumor vascular and cellular heterogeneity respectively. There were significant differences in the quantitative MRI metrics of ADC and perfusion. The multiview IsoSVM model classified benign and malignant breast tumors with sensitivity and specificity of 93 and 85%, respectively, with an AUC of 0.91.

An automated system for analyzing magnetic resonance imaging (MRI) can differentiate benign from malignant breast tumors with high accuracy. Vishwa S. Parekh and Michael A. Jacobs 
from Johns Hopkins University School of Medicine in Baltimore, Maryland, USA, developed an algorithm for extracting textural information from MRI scans that are not visually perceivable to radiologists using machine learning and Radiomic features. Their model combines different MRI parameters to produce so-called radiomic feature maps. The researchers tested their mapping framework on a retrospective cohort of 124 patients, 26 of whom had benign breast lesions and 98 had malignant tumors. They found statistical differences in certain MRI and radiomic metrics. Moreover, they demonstrated quantitative ADC map values and Dynamic contrast pharmacokinetic modeling to characterize the radiomic features. Overall, the method identified a breast lesion as benign or malignant with 93% sensitivity and 85% specificity, suggesting that radiomic feature mapping could aid in diagnosing and characterizing the disease correctly and tailoring therapy accordingly.

Clinically insignificant prostate cancer suitable for active surveillance according to Prostate Cancer Research International: Active surveillance criteria: Utility of PI-RADS v2

BACKGROUND

Active surveillance (AS) is an important treatment strategy for prostate cancer (PCa). Prostate Imaging-Reporting and Data System (PI-RADS) v2 has been addressed, but few studies have reported the value of PI-RADS v2 for assessing risk stratification in patients with PCa, especially on selecting potential candidates for AS.

PURPOSE

To investigate the utility of PI-RADS v2 and apparent diffusion coefficient (ADC) in evaluating patients with insignificant PCa, who are suitable for AS.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 238 patients with PCa who met the Prostate Cancer Research International: Active Surveillance criteria underwent radical prostatectomy.

FIELD STRENGTH/SEQUENCE

3.0T, including T₂ -weighted, diffusion-weighted, and dynamic contrast-enhanced imaging.

ASSESSMENT

Insignificant cancer was defined histopathologically as an organ-confined disease with a tumor volume <0.5 cm³ without Gleason score 4-5. Patients were divided into two groups based on the PI-RADS v2 and tumor ADC: A, PI-RADS score ≤3 and ADC ≥1.095 × 10^-3 mm² /s; and B, PI-RADS score 4-5 or ADC <1.095 × 10^-3 mm² /s. Preoperative clinical and imaging variables were evaluated regarding the associations with insignificant cancer.

RESULTS

Of the 238 patients, 101 (42.8%) were diagnosed with insignificant cancer on pathological findings. The number of positive cores, prostate-specific antigen density (PSAD), PI-RADS v2 and tumor ADC were significantly associated with insignificant cancer on univariate analysis (P < 0.05). However, multivariate analysis indicated tumor ADC (odds ratio [OR] = 4.57, P < 0.001) and PI-RADS v2 (OR = 3.60, P < 0.001) were independent predictors of insignificant cancer. Area under the receiver operating characteristics curve (AUC) reached 0.803 when PI-RADS v2 (AUC = 0.747) was combined with tumor ADC (AUC = 0.786).

DATA CONCLUSION

The PI-RADS v2 together with tumor ADC may be a useful marker for predicting patients with insignificant PCa when considering AS.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1072-1079.

Diffusion weighted imaging of the prostate-principles, application, and advances

This review article aims to provide an overview on the principles of diffusion-weighted magnetic resonance imaging (DW-MRI) and its applications in the imaging of the prostate. DW-MRI with regards to different applications for prostate cancer (PCa) detection and characterization, local staging as well as for active surveillance (AS) and tumor recurrence after radical prostatectomy (RP) will be discussed. Furthermore, advances in DW-MRI techniques like diffusion kurtosis imaging (DKI) will be presented.

MRI findings in men on active surveillance for prostate cancer: does dutasteride make MRI visible lesions less conspicuous? Results from a placebo-controlled, randomised clinical trial

OBJECTIVES

To investigate changes in the Apparent Diffusion Coefficient (ADC) using diffusion-weighted imaging (DWI) in men on active surveillance for prostate cancer taking dutasteride 0.5 mg or placebo.

METHODS

We analysed 37 men, randomised to 6 months of daily dutasteride (n = 18) or placebo (n = 19), undergoing 3T multi-parametric Magnetic Resonance Imaging (mpMRI) scans at baseline and 6 months. Images were reviewed blind to treatment allocation and clinical information. Mean ADC of peripheral (PZ) and transition (TZ) zones, and MR-suspicious lesions were compared between groups over 6 months. Conspicuity was defined as the PZ divided by tumour ADC, and its change over 6 months was assessed.

RESULTS

A decrease in mean conspicuity in the dutasteride group (but not the controls) was seen over 6 months (1.54 vs 1.38; p = 0.025). Absolute changes in ADC and conspicuity were significantly different between placebo and dutasteride groups at 6 months: (-0.03 vs 0.08, p = 0.033) and (0.11 vs -0.16, p = 0.012), as were percentage changes in the same parameters: (-2.27% vs 8.56% p = 0.048) and (9.25% vs -9.89% p = 0.013).

CONCLUSIONS

Dutasteride was associated with increased tumour ADC and reduced conspicuity. A lower threshold for triggering biopsy might be considered in men on dutasteride undergoing mpMRI for prostate cancer.

KEY POINTS

• Dutasteride increases ADC and reduces conspicuity in small mpMRI-visible prostate cancers. • Knowledge of dutasteride exposure is important in the interpretation of prostate mpMRI. • A lower threshold for triggering biopsy may be appropriate on dutasteride.

Diffusion tensor imaging in abdominal organs

Initially, diffusion tensor imaging (DTI) was mainly applied in studies of the human brain to analyse white matter tracts. As DTI is outstanding for the analysis of tissue´s microstructure, the interest in DTI for the assessment of abdominal tissues has increased continuously in recent years. Tissue characteristics of abdominal organs differ substantially from those of the human brain. Further peculiarities such as respiratory motion and heterogenic tissue composition lead to difficult conditions that have to be overcome in DTI measurements. Thus MR measurement parameters have to be adapted for DTI in abdominal organs. This review article provides information on the technical background of DTI with a focus on abdominal imaging, as well as an overview of clinical studies and application of DTI in different abdominal regions. Copyright © 2015 John Wiley & Sons, Ltd.

The utility of quantitative ADC values for differentiating high-risk from low-risk prostate cancer: a systematic review and meta-analysis

PURPOSE

The purpose of the study is to perform a meta-analysis of studies investigating the diagnostic performance of apparent diffusion coefficient (ADC) values in separating high-risk from low-risk prostate cancer (PCa).

METHODS

MEDLINE and EMBASE databases were searched in December 2015 for studies reporting diagnostic performance of ADC values for discriminating high-risk from low-risk PCa and providing sufficient data to construct 2 × 2 contingency tables. Diagnostic performance was quantitatively pooled using a bivariate random-effects model including subgroup analysis and assessment of study heterogeneity and methodological quality.

RESULTS

13 studies were included, providing 1107 tumor foci in 705 patients. Heterogeneity among studies was moderate (τ² = 0.222). Overall sensitivity was 76.9% (95% CI 68.6-83.6%); overall specificity was 77.0% (95% CI 69.9-82.8%); and summary AUC was 0.67. Inverse correlation between sensitivity and specificity (ρ = -0.58) indicated interstudy heterogeneity was partly due to variation in threshold for test positivity. Primary biases were readers' knowledge of Gleason score during ADC measurement, lack of prespecified ADC thresholds, and lack of prostatectomy as reference in some studies. Higher sensitivity was seen in studies published within the past 2 years and studies not using b value of at least 2000; higher specificity was associated with involvement of one, rather than two, readers measuring ADC. Field strength, coil selection, and advanced diffusion metrics did not significantly impact diagnostic performance.

CONCLUSION

ADC values show moderate accuracy in separating high-risk from low-risk PCa, although important biases may overestimate performance and unexplained sources of heterogeneity likely exist. Further studies using a standardized methodology and addressing identified weaknesses may help guide the use of ADC values for clinical decision-making.

Diffusion-Weighted Genitourinary Imaging

This review article aims to provide an overview on of diffusion-weighted MR imaging (DW-MR imaging) in the urogenital tract. Compared with conventional cross-sectional imaging methods, the additional value of DW-MR imaging in the detection and further characterization of benign and malignant lesions of the kidneys, bladder, prostate, and pelvic lymph nodes is discussed as well as the role of DW-MR imaging in the evaluation of treatment response.