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In vivo assessment of ductal carcinoma in situ grade: a model incorporating dynamic contrast-enhanced and diffusion-weighted breast MR imaging parameters.

ABSTRACT: To develop a model incorporating dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging features to differentiate high-nuclear-grade (HNG) from non-HNG ductal carcinoma in situ (DCIS) in vivo.This HIPAA-compliant study was approved by the institutional review board and requirement for informed consent was waived. A total of 55 pure DCIS lesions (19 HNG, 36 non-HNG) in 52 women who underwent breast MR imaging at 1.5 T with both DCE and DW imaging (b = 0 and 600 sec/mm(2)) were retrospectively reviewed. The following lesion characteristics were recorded or measured: DCE morphology, DCE maximum lesion size, peak initial enhancement at 90 seconds, worst-curve delayed enhancement kinetics, apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR) at DW imaging with b values of 0 and 600 sec/mm(2), and T2 signal effects (measured with CNR at b = 0 sec/mm(2)). Univariate and stepwise multivariate logistic regression modeling was performed to identify MR imaging features that optimally discriminated HNG from non-HNG DCIS. Discriminative abilities of models were compared by using the area under the receiver operating characteristic curve (AUC).HNG lesions exhibited larger mean maximum lesion size (P = .02) and lower mean CNR for images with b value of 600 sec/mm(2) (P = .004), allowing discrimination of HNG from non-HNG DCIS (AUC = 0.71 for maximum lesion size, AUC = 0.70 for CNR at b = 600 sec/mm(2)). Differences in CNR for images with b value of 0 sec/mm(2) (P = .025) without corresponding differences in ADC values were observed between HNG and non-HNG lesions. Peak initial enhancement was the only kinetic variable to approach significance (P = .05). No differences in lesion morphology (P = .11) or worst-curve delayed enhancement kinetics (P = .97) were observed. A multivariate model combining CNR for images with b value of 600 sec/mm(2) and maximum lesion size most significantly discriminated HNG from non-HNG (AUC = 0.81).The preliminary findings suggest that DCE and DW MR imaging features may aid in identifying patients with high-risk DCIS. Further study may yield a model combining MR characteristics with histopathologic data to facilitate lesion-specific targeted therapies. © RSNA, 2012.

SUBMITTER: Rahbar H

PROVIDER: S-EPMC3329273 | biostudies-other | 2012 May

REPOSITORIES: biostudies-other

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Project description:PurposeDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI) of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported.Materials and methodsThe study comprised of 234 female patients with 85 benign and 149 malignant lesions. Four distinct groups of features, coupling with pathological tests, were estimated to comprehensively characterize the pictorial properties of each lesion, which was obtained by a semi-automated segmentation method. Classical machine learning scheme including feature subset selection and various classification schemes were employed to build prognostic model, which served as a foundation for evaluating the combined effects of the multi-sided features for predicting of the types of lesions. Various measurements including cross validation and receiver operating characteristics were used to quantify the diagnostic performances of each feature as well as their combination.ResultsSeven features were all found to be statistically different between the malignant and the benign groups and their combination has achieved the highest classification accuracy. The seven features include one pathological variable of age, one morphological variable of slope, three texture features of entropy, inverse difference and information correlation, one kinetic feature of SER and one DWI feature of apparent diffusion coefficient (ADC). Together with the selected diagnostic features, various classical classification schemes were used to test their discrimination power through cross validation scheme. The averaged measurements of sensitivity, specificity, AUC and accuracy are 0.85, 0.89, 90.9% and 0.93, respectively.ConclusionMulti-sided variables which characterize the morphological, kinetic, pathological properties and DWI measurement of ADC can dramatically improve the discriminatory power of breast lesions.

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: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:To determine the diagnostic availability of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MR images for evaluating residual tumours at short-term follow-up after unplanned excision of malignant soft-tissue tumours.From January 2013 to September 2014, 38 patients underwent first follow-up MRI, including DCE and DW imaging (DWI), within 3 months of unplanned malignant soft-tissue tumour excision. The presence or absence of definite nodule formation, focal fluid/haematoma collection, oedema and fascial thickening around or at tumour beds were evaluated using conventional MR images. The volume transfer constant between blood plasma and extracellular/extravascular space (EES) (Ktrans), rate constant between EES and blood plasma (Kep), volume of EES space per unit volume of tissue and initial area under the concentration curve (iAUC) values with time-concentration curve (TCC) plots were obtained on DCE images, and apparent diffusion coefficient (ADC) values were measured on ADC maps. All data were statistically analyzed.Of the 21 patients who underwent re-excision, 12 patients had a residual tumor and 9 did not. All conventional MRI variables, except definite nodule formation, were insignificantly related to the presence of residual tumour. However, ADC values were found to be significantly associated with the presence of residual tumour, as were the DCE MRI variables, Ktrans, Kep and iAUC. In particular, TCC pattern and Kep were most significantly associated with residual tumour.Additional DCE images may be useful for determining the presence of residual tumours in tumour beds during short-term follow-up after inadequate malignant soft-tissue tumour excision.The addition of DCE MRI and quantitative analysis of the images obtained might be useful for determining the presence of residual tumour in a tumour bed during short-term follow-up after inadequate excision of a malignant soft-tissue tumour, although DWI was also found to be helpful.

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In vivo assessment of ductal carcinoma in situ grade: a model incorporating dynamic contrast-enhanced and diffusion-weighted breast MR imaging parameters.

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