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Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness.

ABSTRACT: To assess the incremental value of diffusion-weighted (DW) magnetic resonance (MR) imaging over T2-weighted MR imaging at 3 T for prostate cancer detection and to investigate the use of the apparent diffusion coefficient (ADC) to characterize tumor aggressiveness, with whole-mount step-section pathologic analysis as the reference standard.The Internal Review Board approved this HIPAA-compliant retrospective study and waived informed consent. Fifty-one patients with prostate cancer (median age, 58 years; range, 46-74 years) underwent T2-weighted MR imaging and DW MR imaging (b values: 0 and 700 sec/mm(2) [n = 20] or 0 and 1000 sec/mm(2) [n = 31]) followed by prostatectomy. The prostate was divided into 12 regions; two readers provided a score for each region according to their level of suspicion for the presence of cancer on a five-point scale, first using T2-weighted MR imaging alone and then using T2-weighted MR imaging and the ADC map in conjunction. Areas under the receiver operating characteristic curve (AUCs) were estimated to evaluate performance. Generalized estimating equations were used to test the ADC difference between benign and malignant prostate regions and the association between ADCs and tumor Gleason scores.For tumor detection, the AUCs for readers 1 and 2 were 0.79 and 0.76, respectively, for T2-weighted MR imaging and 0.79 and 0.78, respectively, for T2-weighted MR imaging plus the ADC map. Mean ADCs for both cancerous and healthy prostatic regions were lower when DW MR imaging was performed with a b value of 1000 sec/mm(2) rather than 700 sec/mm(2). Regardless of the b value used, there was a significant difference in the mean ADC between malignant and benign prostate regions. A lower mean ADC was significantly associated with a higher tumor Gleason score (mean ADCs of [1.21, 1.10, 0.87, and 0.69] × 10(-3) mm(2)/sec were associated with Gleason score of 3 + 3, 3 + 4, 4 + 3, and 8 or higher, respectively; P = .017).Combined DW and T2-weighted MR imaging had similar performance to T2-weighted MR imaging alone for tumor detection; however, DW MR imaging provided additional quantitative information that significantly correlated with prostate cancer aggressiveness.

SUBMITTER: Vargas HA

PROVIDER: S-EPMC3099046 | biostudies-other | 2011 Jun

REPOSITORIES: biostudies-other

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Project description:PurposeTo retrospectively determine the accuracy of diffusion-weighted (DW) magnetic resonance (MR) imaging for identifying cancer in the prostate peripheral zone (PZ) and to assess the accuracy of tumor volume measurements made with T2-weighted imaging and combined T2-weighted and DW MR imaging by using surgical pathologic examination as the reference standard.Materials and methodsThe institutional review board issued a waiver of informed consent for this HIPAA-compliant study. Forty-two patients underwent endorectal MR at 1.5 T before undergoing radical prostatectomy for prostate cancer and had at least one PZ tumor larger than 0.1 cm(3) at surgical pathologic examination. On T2-weighted images, an experienced radiologist outlined suspected PZ tumors. Two apparent diffusion coefficient (ADC) cutoff values were identified by using the Youden index and published literature. Image cluster analysis was performed on voxels within the suspected tumor regions. Associations between volume measurements from imaging and from pathologic examination were assessed by using concordance correlation coefficients (CCCs). The sensitivity and specificity of ADCs for identifying malignant PZ voxels were calculated.ResultsIn identifying malignant voxels, respective ADC cutoff values of 0.0014 and 0.0016 mm(2)/sec yielded sensitivity of 82% and 95% and specificity of 85% and 65%, respectively. Sixty PZ cancer lesions larger than 0.1 cm(3) were found at pathologic examination; 43 were detected by the radiologist. CCCs between imaging and pathologic tumor volume measurements were 0.36 for T2-weighted imaging, and 0.46 and 0.60 for combined T2-weighted and DW MR imaging with ADC cutoffs of 0.0014 and 0.0016 mm(2)/sec, respectively; the CCC of combined T2-weighted and DW MR imaging (ADC cutoff, 0.0016 mm(2)/sec) was significantly higher (P = .006) than that of T2-weighted imaging alone.ConclusionAdding DW MR to T2-weighted imaging can significantly improve the accuracy of prostate PZ tumor volume measurement.Supplemental materialhttp://radiology.rsnajnls.org/cgi/content/full/252/2/449/DC1.

Project description:BackgroundDiffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease.PurposeTo compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms.Study typeProspective.PopulationThirty-three patients prospectively imaged prior to prostatectomy.Field strength/sequence3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence.AssessmentDatasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC).Statistical testLevene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant.ResultsThe DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size.Data conclusionWe found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer.Level of evidence1 TECHNICAL EFFICACY: Stage 3.

Project description:The purpose of this work was (1) to develop a magnetic resonance elastography (MRE) system for imaging of the ex vivo human prostate and (2) to assess the diagnostic power of mono-frequency and multi-frequency MRE and diffusion weighted imaging (DWI) alone and combined as correlated with histopathology in a patient study. An electromagnetic driver was designed specifically for MRE studies in small-bore MR scanners. Ex vivo prostate specimens (post-fixation) of 14 patients who underwent radical prostatectomy were imaged with MRE at 7?T (nine cases had DWI). In six patients, the MRE examination was performed at three frequencies (600, 800, 1000?Hz) to extract the power-law exponent Gamma. The images were registered to wholemount pathology slides marked with the Gleason score. The areas under the receiver-operator-characteristic curves (AUC) were calculated. The methods were validated in a phantom study and it was demonstrated that (i) the driver does not interfere with the acquisition process and (ii) the driver can generate amplitudes greater than 100?µm for frequencies less than 1?kHz. In the quantitative study, cancerous tissue with Gleason score at least 3?+?3 was distinguished from normal tissue in the peripheral zone (PZ) with an average AUC of 0.75 (Gd ), 0.75 (Gl ), 0.70 (Gamma-Gd ), 0.68 (apparent diffusion coefficient, ADC), and 0.82 (Gd ?+?Gl ?+?ADC). The differentiation between PZ and central gland was modest for Gd (p?<?0.07), Gl (p?<?0.06) but not significant for Gamma (p?<?0.2). A correlation of 0.4 kPa/h was found between the fixation time of the prostate specimen and the stiffness of the tissue, which could affect the diagnostic power results. DWI and MRE may provide complementary information; in fact MRE performed better than ADC in distinguishing normal from cancerous tissue in some cases. Multi-frequency (Gamma) analysis did not appear to improve the results. However, in light of the effect of tissue fixation, the clinical implication of our results may be inconclusive and more experiments are needed.

Project description:PurposeTo quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas.Materials and methodsThis study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations.ResultsADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05).ConclusionWater molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.

Project description:PurposeTo analyze the diffusion and perfusion parameters of central gland (CG) prostate cancer, stromal hyperplasia (SH), and glandular hyperplasia (GH) and to determine the role of these parameters in the differentiation of CG cancer from benign CG hyperplasia.Materials and methodsIn this institutional review board-approved (with waiver of informed consent), HIPAA-compliant study, 38 foci of carcinoma, 38 SH nodules, and 38 GH nodules in the CG were analyzed in 49 patients (26 with CG carcinoma) who underwent preoperative endorectal magnetic resonance (MR) imaging and radical prostatectomy. All carcinomas and hyperplastic foci on MR images were localized on the basis of histopathologic correlation. The apparent diffusion coefficient (ADC), the contrast agent transfer rate between blood and tissue (K(trans)), and extravascular extracellular fractional volume values for all carcinoma, SH, and GH foci were calculated. The mean, standard deviation, 95% confidence interval (CI), and range of each parameter were calculated. Receiver operating characteristic (ROC) and multivariate logistic regression analyses were performed for differentiation of CG cancer from SH and GH foci.ResultsThe average ADCs (× 10(-3) mm(2)/sec) were 1.05 (95% CI: 0.97, 1.11), 1.27 (95% CI: 1.20, 1.33), and 1.73 (95% CI: 1.64, 1.83), respectively, in CG carcinoma, SH foci, and GH foci and differed significantly, yielding areas under the ROC curve (AUCs) of 0.99 and 0.78, respectively, for differentiation of carcinoma from GH and SH. Perfusion parameters were similar in CG carcinomas and SH foci, with K(trans) yielding the greatest AUCs (0.75 and 0.58, respectively). Adding K(trans) to ADC in ROC analysis to differentiate CG carcinoma from SH increased sensitivity from 38% to 57% at 90% specificity without noticeably increasing the AUC (0.79).ConclusionADCs differ significantly between CG carcinoma, SH, and GH, and the use of them can improve the differentiation of CG cancer from SH and GH. Combining K(trans) with ADC can potentially improve the detection of CG cancer.Supplemental materialhttp://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100021/-/DC1.

Project description:Objectives: The application of magnetic resonance-guided focused ultrasound (MRgFUS) for the treatment of neurological conditions has been of increasing interest. Conventional MR imaging can provide structural information about the effect of MRgFUS, where differences in ablated tissue can be seen, but it lacks information about the status of the cellular environment or neural microstructure. We investigate in vivo acute changes in water diffusion and white matter tracts in the brain of a piglet model after MRgFUS treatment using diffusion-weighted imaging (DWI) with histological verification of treatment-related changes. Methods: MRgFUS was used to treat the anterior body of the fornix in four piglets. T1 and diffusion-weighted images were collected before and after treatment. Mean diffusion-weighted imaging (MDWI) images were generated to measure lesion volumes via signal intensity thresholds. Histological data were collected for volume comparison and assessment of treatment effect. DWI metric maps of fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were generated for quantitative assessment. Fornix-related fiber tracts were generated before and after treatment for qualitative assessment. Results: The volume of treated tissue measured via MDWI did not differ significantly from histological measurements, and both were significantly larger than the treatment cell volume. Diffusion metrics in the treatment region were significantly decreased following MRgFUS treatment, with the peak change seen at the lesion core and decreasing radially. Histological analysis confirmed an area of coagulative necrosis in the targeted region with sharp demarcation zone with surrounding brain. Tractography from the lesion core and the fornix revealed fiber disruptions following treatment. Conclusions: Diffusion maps and fiber tractography are an effective method for assessing lesion volumes and microstructural changes in vivo following MRgFUS treatment. This study demonstrates that DWI has the potential to advance MRgFUS by providing convenient in vivo microstructural lesion and fiber tractography assessment after treatment.

Project description:PurposeTo compare diagnostic accuracy of T2-weighted magnetic resonance (MR) imaging with that of multiparametric (MP) MR imaging combining T2-weighted imaging with diffusion-weighted (DW) MR imaging, dynamic contrast material-enhanced (DCE) MR imaging, or both in the detection of locally recurrent prostate cancer (PCa) after radiation therapy (RT).Materials and methodsThis retrospective HIPAA-compliant study was approved by the institutional review board; informed consent was waived. Fifty-three men (median age, 70 years) suspected of having post-RT recurrence of PCa underwent MP MR imaging, including DW and DCE sequences, within 6 months after biopsy. Two readers independently evaluated the likelihood of PCa with a five-point scale for T2-weighted imaging alone, T2-weighted imaging with DW imaging, T2-weighted imaging with DCE imaging, and T2-weighted imaging with DW and DCE imaging, with at least a 4-week interval between evaluations. Areas under the receiver operating characteristic curve (AUC) were calculated. Interreader agreement was assessed, and quantitative parameters (apparent diffusion coefficient [ADC], volume transfer constant [K(trans)], and rate constant [k(ep)]) were assessed at sextant- and patient-based levels with generalized estimating equations and the Wilcoxon rank sum test, respectively.ResultsAt biopsy, recurrence was present in 35 (66%) of 53 patients. In detection of recurrent PCa, T2-weighted imaging with DW imaging yielded higher AUCs (reader 1, 0.79-0.86; reader 2, 0.75-0.81) than T2-weighted imaging alone (reader 1, 0.63-0.67; reader 2, 0.46-0.49 [P ≤ .014 for all]). DCE sequences did not contribute significant incremental value to T2-weighted imaging with DW imaging (reader 1, P > .99; reader 2, P = .35). Interreader agreement was higher for combinations of MP MR imaging than for T2-weighted imaging alone (κ = 0.34-0.63 vs κ = 0.17-0.20). Medians of quantitative parameters differed significantly (P < .0001 to P = .0233) between benign tissue and PCa (ADC, 1.64 × 10(-3) mm(2)/sec vs 1.13 × 10(-3) mm(2)/sec; K(trans), 0.16 min(-1) vs 0.33 min(-1); k(ep), 0.36 min(-1) vs 0.62 min(-1)).ConclusionMP MR imaging has greater accuracy in the detection of recurrent PCa after RT than T2-weighted imaging alone, with no additional benefit if DCE is added to T2-weighted imaging and DW imaging.

Project description:Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10-3, 2.8 × 10-3, and >3.0 ×10-2 mm2/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

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Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness.

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