Amita Shukla-Dave

Prostate Cancer: Identification with Combined Diffusion-weighted MR Imaging and 3D 1H MR Spectroscopic Imaging—Correlation with Pathologic Findings1

PURPOSE To retrospectively measure the mean apparent diffusion coefficient (ADC) with diffusion-weighted magnetic resonance (MR) imaging and the mean metabolic ratio (MET) with three-dimensional (3D) hydrogen 1 ((1)H) MR spectroscopic imaging in regions of interest (ROIs) drawn over benign and malignant peripheral zone (PZ) prostatic tissue and to assess ADC, MET, and combined ADC and MET for identifying malignant ROIs, with whole-mount histopathologic examination as the reference standard. MATERIALS AND METHODS The institutional review board approved this HIPAA-compliant retrospective study and issued a waiver of informed consent. From among 61 consecutive patients with prostate cancer, 38 men (median age, 61 years; range, 42-72 years) who underwent 1.5-T endorectal MR imaging before radical prostatectomy and who fulfilled all inclusion criteria of no prior hormonal or radiation treatment and at least one PZ lesion (volume, >0.1 cm(3)) at whole-mount pathologic examination were included. ADC maps were generated from diffusion-weighted MR imaging data, and MET maps of (choline plus polyamine plus creatine)/citrate were calculated from 3D (1)H MR spectroscopic imaging data. ROIs in the PZ identified by matching pathologic slides with T2-weighted images were overlaid on MET and ADC maps. Areas under the receiver operating characteristic curves (AUCs) were used to evaluate accuracy. RESULTS The mean ADC +/- standard deviation, (1.39 +/- 0.23) x 10(-3) mm(2)/sec, and mean MET (0.92 +/- 0.32) for malignant ROIs differed significantly from the mean ADC, (1.69 +/- 0.24) x 10(-3) mm(2)/sec, and mean MET (0.73 +/- 0.18) for benign ROIs (P < .001 for both). In distinguishing malignant ROIs, combined ADC and MET (AUC = 0.85) performed significantly better than MET alone (AUC = 0.74; P = .005) and was also better than ADC alone (AUC = 0.81), although the difference was not statistically significant (P = .09). CONCLUSION The combination of ADC and MET performs significantly better than MET for differentiating between benign and malignant ROIs in the PZ.

Magnetic Resonance Imaging for Predicting Prostate Biopsy Findings in Patients Considered for Active Surveillance of Clinically Low Risk Prostate Cancer

PURPOSE A barrier to the acceptance of active surveillance for men with prostate cancer is the risk of underestimating the cancer burden on initial biopsy. We assessed the value of endorectal magnetic resonance imaging in predicting upgrading on confirmatory biopsy in men with low risk prostate cancer. MATERIALS AND METHODS A total of 388 consecutive men (mean age 60.6 years, range 33 to 89) with clinically low risk prostate cancer (initial biopsy Gleason score 6 or less, prostate specific antigen less than 10 ng/ml, clinical stage T2a or less) underwent endorectal magnetic resonance imaging before confirmatory biopsy. Three radiologists independently and retrospectively scored tumor visibility on endorectal magnetic resonance imaging using a 5-point scale (1-definitely no tumor to 5-definitely tumor). Inter-reader agreement was assessed with weighted kappa statistics. Associations between magnetic resonance imaging scores and confirmatory biopsy findings were evaluated using measures of diagnostic performance and multivariate logistic regression. RESULTS On confirmatory biopsy, Gleason score was upgraded in 79 of 388 (20%) patients. Magnetic resonance imaging scores of 2 or less had a high negative predictive value (0.96-1.0) and specificity (0.95-1.0) for upgrading on confirmatory biopsy. A magnetic resonance imaging score of 5 was highly sensitive for upgrading on confirmatory biopsy (0.87-0.98). At multivariate analysis patients with higher magnetic resonance imaging scores were more likely to have disease upgraded on confirmatory biopsy (odds ratio 2.16-3.97). Inter-reader agreement and diagnostic performance were higher for the more experienced readers (kappa 0.41-0.61, AUC 0.76-0.79) than for the least experienced reader (kappa 0.15-0.39, AUC 0.61-0.69). Magnetic resonance imaging performed similarly in predicting low risk and very low risk (Gleason score 6, less than 3 positive cores, less than 50% involvement in all cores) prostate cancer. CONCLUSIONS Adding endorectal magnetic resonance imaging to the initial clinical evaluation of men with clinically low risk prostate cancer helps predict findings on confirmatory biopsy and assess eligibility for active surveillance.

Prostate Tumor Volume Measurement with Combined T2-weighted Imaging and Diffusion-weighted MR: Correlation with Pathologic Tumor Volume

PURPOSE To 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 METHODS The 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. RESULTS In 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. CONCLUSION Adding DW MR to T2-weighted imaging can significantly improve the accuracy of prostate PZ tumor volume measurement. SUPPLEMENTAL MATERIAL http://radiology.rsnajnls.org/cgi/content/full/252/2/449/DC1.

The utility of magnetic resonance imaging and spectroscopy for predicting insignificant prostate cancer: An initial analysis

To design new models that combine clinical variables and biopsy data with magnetic resonance imaging (MRI) and MR spectroscopic imaging (MRSI) data, and assess their value in predicting the probability of insignificant prostate cancer.

Prostate Cancer Imaging

As prostate cancer is a biologically heterogeneous disease for which a variety of treatment options are available, the major objective of prostate cancer imaging is to achieve more precise disease characterization. Magnetic resonance imaging (MRI) may enhance the staging of prostate cancer compared with clinical evaluation, transrectal ultrasound, or computed tomography (CT), and allows concurrent evaluation of prostatic, periprostatic, and pelvic anatomy. In clinical practice, the fusion of MRI or dynamic contrast-enhanced MRI (DCE-MRI) with MR spectroscopic imaging (MRSI) is improving the evaluation of cancer location, size, and extent, while providing an indication of tumor aggressiveness. Pretreatment knowledge of these prognostic variables is essential for achieving minimally invasive, patient-specific therapy.

Functional Magnetic Resonance Imaging in Prostate Cancer

CONTEXT Magnetic resonance imaging (MRI) combined with magnetic resonance spectroscopy imaging (MRSI), dynamic contrast-enhanced MRI, and diffusion-weighted MRI emerged as promising tests in the diagnosis of prostate cancer, and they show encouraging results. OBJECTIVE This review emphasizes different functional MRI techniques in the diagnosis of prostate cancer and includes information about their clinical value and usefulness. EVIDENCE ACQUISITION The authors searched the Medline, Embase, and Cochrane Library databases. There were no language restrictions. The last search was performed in October 2008. EVIDENCE SYNTHESIS The combination of conventional MRI with functional MRI techniques is more reliable for differentiating benign and malignant prostate tissues than any other diagnostic procedure. At present, no guideline is available that outlines which technique is best in a specific clinical situation. It also remains uncertain whether improved spatial resolution and signal-to-noise ratio of 3-T MRI will improve diagnostic performance. CONCLUSIONS A limited number of small studies suggest that functional MRI may improve the diagnosis and staging of prostate cancer. This finding needs further confirmation in larger studies, and cost-effectiveness needs to be established.

Preoperative Nomograms Incorporating Magnetic Resonance Imaging and Spectroscopy for Prediction of Insignificant Prostate Cancer

Study Type – Prognosis (case series)

Noninvasive Assessment of Tumor Microenvironment Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging and 18F-Fluoromisonidazole Positron Emission Tomography Imaging in Neck Nodal Metastases

PURPOSE To assess noninvasively the tumor microenvironment of neck nodal metastases in patients with head-and-neck cancer by investigating the relationship between tumor perfusion measured using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and hypoxia measured by (18)F-fluoromisonidazole ((18)F-FMISO) positron emission tomography (PET). METHODS AND MATERIALS Thirteen newly diagnosed head-and-neck cancer patients with metastatic neck nodes underwent DCE-MRI and (18)F-FMISO PET imaging before chemotherapy and radiotherapy. The matched regions of interests from both modalities were analyzed. To examine the correlations between DCE-MRI parameters and standard uptake value (SUV) measurements from (18)F-FMISO PET, the nonparametric Spearman correlation coefficient was calculated. Furthermore, DCE-MRI parameters were compared between nodes with (18)F-FMISO uptake and nodes with no (18)F-FMISO uptake using Mann-Whitney U tests. RESULTS For the 13 patients, a total of 18 nodes were analyzed. The nodal size strongly correlated with the (18)F-FMISO SUV (rho = 0.74, p < 0.001). There was a strong negative correlation between the median k(ep) (redistribution rate constant) value (rho = -0.58, p = 0.042) and the (18)F-FMISO SUV. Hypoxic nodes (moderate to severe (18)F-FMISO uptake) had significantly lower median K(trans) (volume transfer constant) (p = 0.049) and median k(ep) (p = 0.027) values than did nonhypoxic nodes (no (18)F-FMISO uptake). CONCLUSION This initial evaluation of the preliminary results support the hypothesis that in metastatic neck lymph nodes, hypoxic nodes are poorly perfused (i.e., have significantly lower K(trans) and k(ep) values) compared with nonhypoxic nodes.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a Predictor of Outcome in Head-and-Neck Squamous Cell Carcinoma Patients With Nodal Metastases

PURPOSE Dynamic contrast-enhanced MRI (DCE-MRI) can provide information regarding tumor perfusion and permeability and has shown prognostic value in certain tumors types. The goal of this study was to assess the prognostic value of pretreatment DCE-MRI in head and neck squamous cell carcinoma (HNSCC) patients with nodal disease undergoing chemoradiation therapy or surgery. METHODS AND MATERIALS Seventy-four patients with histologically proven squamous cell carcinoma and neck nodal metastases were eligible for the study. Pretreatment DCE-MRI was performed on a 1.5T MRI. Clinical follow-up was a minimum of 12 months. DCE-MRI data were analyzed using the Tofts model. DCE-MRI parameters were related to treatment outcome (progression-free survival [PFS] and overall survival [OS]). Patients were grouped as no evidence of disease (NED), alive with disease (AWD), dead with disease (DOD), or dead of other causes (DOC). Prognostic significance was assessed using the log-rank test for single variables and Cox proportional hazards regression for combinations of variables. RESULTS At last clinical follow-up, for Stage III, all 12 patients were NED. For Stage IV, 43 patients were NED, 4 were AWD, 11 were DOD, and 4 were DOC. K(trans) is volume transfer constant. In a stepwise Cox regression, skewness of K(trans) (volume transfer constant) was the strongest predictor for Stage IV patients (PFS and OS: p <0.001). CONCLUSION Our study shows that skewness of K(trans) was the strongest predictor of PFS and OS in Stage IV HNSCC patients with nodal disease. This study suggests an important role for pretreatment DCE-MRI parameter K(trans) as a predictor of outcome in these patients.

Non-gaussian analysis of diffusion-weighted MR imaging in head and neck squamous cell carcinoma: A feasibility study.

BACKGROUND AND PURPOSE: Water in biological structures often displays non-Gaussian diffusion behavior. The objective of this study was to test the feasibility of non-Gaussian fitting by using the kurtosis model of the signal intensity decay curves obtained from DWI by using an extended range of b-values in studies of phantoms and HNSCC. MATERIALS AND METHODS: Seventeen patients with HNSCC underwent DWI by using 6 b-factors (0, 50–1500 s/mm2) at 1.5T. Monoexponential (yielding ADCmono) and non-Gaussian kurtosis (yielding apparent diffusion coefficient Dapp and apparent kurtosis coefficient Kapp) fits were performed on a voxel-by-voxel basis in selected regions of interest (primary tumors, metastatic lymph nodes, and spinal cord). DWI studies were also performed on phantoms containing either water or homogenized asparagus. To determine whether the kurtosis model provided a significantly better fit than did the monoexponential model, an F test was performed. Spearman correlation coefficients were calculated to assess correlations between Kapp and Dapp. RESULTS: The kurtosis model fit the experimental data points significantly better than did the monoexponential model (P < .05). Dapp was approximately twice the value of ADCmono (eg, in neck nodal metastases Dapp was 1.54 and ADCmono was 0.84). Kapp showed a weak Spearman correlation with Dapp in a homogenized asparagus phantom and for 44% of tumor lesions. CONCLUSIONS: The use of kurtosis modeling to fit DWI data acquired by using an extended b-value range in HNSCC is feasible and yields a significantly better fit of the data than does monoexponential modeling. It also provides an additional parameter, Kapp, potentially with added value.