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Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype.

ABSTRACT: To investigate associations between the clinicopathologic features and MRI features of triple-negative breast cancer (TNBC) and ER-positive breast cancer (BC) via apparent diffusion coefficient (ADC) histogram analysis.In this study, 221 breast cancer patients with pre-operative MRI performed from August 2009 to March 2015 were included in a retrospective analysis. All patients had a pathologically confirmed diagnosis of invasive carcinoma and were grouped into ER-positive (149) or triple-negative (72) subtypes. DWI rim sign and various ADC parameters (mean; mode; 25, 50, and 75 percentiles; skewness; and kurtosis) between ER-positive and TNBC were compared using whole-lesion ADC histogram analysis. Univariate and multivariate regression analyses were used for statistical comparison.DWI rim signs were detected in 42.3% and 41.7% of ER-positive subtype and TNBC, respectively (P = 0.931). TNBC had poorer histologic grade (P<0.001) and higher Ki-67 expression (P <0.001) than ER-positive subtype BC. TNBC displayed higher ADC parameters (mean, mode, 50th & 75th percentiles, kurtosis on univariate analysis, all P<0.001; only kurtosis on multivariate anaylsis; P<0.001) than ER-positive subtype BC. TNBC had significantly more recurrence events than ER-positive subtype BC on univarate analysis (9.7% (7/72) vs. 2.7% (4/149), P = 0.035).Poorer clinicopathologic outcomes were found in TNBC. Whole-lesion ADC histogram analysis revealed ADC kurtosis to be higher in TNBC than ER-positive subtype BC.

SUBMITTER: Choi Y

PROVIDER: S-EPMC5436838 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype.

Choi Yangsean Y Kim Sung Hun SH Youn In Kyung IK Kang Bong Joo BJ Park Woo-Chan WC Lee Ahwon A

PloS one 20170518 5

<h4>Purpose</h4>To investigate associations between the clinicopathologic features and MRI features of triple-negative breast cancer (TNBC) and ER-positive breast cancer (BC) via apparent diffusion coefficient (ADC) histogram analysis.<h4>Materials and methods</h4>In this study, 221 breast cancer patients with pre-operative MRI performed from August 2009 to March 2015 were included in a retrospective analysis. All patients had a pathologically confirmed diagnosis of invasive carcinoma and were g ...[more]

PMID: 28542297

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Project description:PurposeGlioblastoma and anaplastic astrocytoma represent the most commonly encountered high-grade-glioma (HGG) in adults. Although both neoplasms are very distinct entities in context of epidemiology, clinical course and prognosis, their appearance in conventional magnetic resonance imaging (MRI) is very similar. In search for additional information aiding the distinction of potentially confusable neoplasms, histogram analysis of apparent diffusion coefficient (ADC) maps recently proved to be auxiliary in a number of entities. Therefore, our present exploratory retrospective study investigated whether ADC histogram profile parameters differ significantly between anaplastic astrocytoma and glioblastoma, reflect the proliferation index Ki-67, or are associated with the prognostic relevant MGMT (methylguanine-DNA methyl-transferase) promotor methylation status.MethodsPre-surgical ADC volumes of 56 HGG patients were analyzed by histogram-profiling. Association between extracted histogram parameters and neuropathology including WHO-grade, Ki-67 expression and MGMT promotor methylation status was investigated due to comparative and correlative statistics.ResultsGrade IV gliomas were more heterogeneous than grade III tumors. More specifically, ADCmin and the lowest percentile ADCp10 were significantly lower, whereas ADCmax, ADC standard deviation and Skewness were significantly higher in the glioblastoma group. ADCmin, ADCmax, ADC standard deviation, Kurtosis and Entropy of ADC histogram were significantly correlated with Ki-67 expression. No significant difference could be revealed by comparison of ADC histogram parameters between MGMT promotor methylated and unmethylated HGG.ConclusionsADC histogram parameters differ significantly between glioblastoma and anaplastic astrocytoma and show distinct associations with the proliferative activity in both HGG. Our results suggest ADC histogram profiling as promising biomarker for differentiation of both, however, further studies with prospective multicenter design are wanted to confirm and further elaborate this hypothesis.

Project description:Background and purposeApparent diffusion coefficient (ADC) reflects micro-enviromental changes and therefore might be useful in predicting recurrence prior to brachytherapy. The purpose of this study is to evaluate change in ADC of the primary tumour and pathologic lymph nodes during treatment and to correlate this with clinical outcome.Material and methodsTwenty patients were included who received chemoradiation for locally advanced cervical cancer between July 2016 and November 2017. All patients underwent magnetic resonance imaging (MRI) prior to treatment, and three MRIs in weeks 1/2, 3 and 4 of treatment, including T2 and diffusion weighted imaging (b-values 0, 200, 800 s/mm2) for determining an ADC-map. Primary tumour was delineated on T2 and ADC-map and pathologic lymph nodes were delineated only on ADC-map.ResultsAt time of analysis median follow-up was 15 (range 7-22) months. From MRI one to four, primary tumour on ADC-map showed a significant signal increase of 0.94 (range 0.74-1.46) × 10-3 mm2/s to 1.13 (0.98-1.49) × 10-3 mm2/s (p < 0.001). When tumour was delineated on T2, ADC-value signal increase (in tumour according to T2) was similar. All 46 delineated pathologic lymph nodes showed an ADC-value increase on average from 0.79 (range 0.33-1.12) × 10-3 mm2/s to 1.14 (0.59-1.75) × 10-3 mm2/s (p < 0.001). The mean tumour/suspected lymph node volumes decreased respectively 51/40%. Four patients developed relapse (one local and three nodal), without clear relation with ΔADC. However, the median volume decrease of the primary tumour was substantially lower in the failing patients compared to the group without relapse (19 vs. 57%).ConclusionsADC values can be acquired using T2-based tumour delineations unless there are substantial shifts between ADC-mapping and T2 acquisition. It remains plausible that ΔADC is a predictor for response to EBRT. However, the correlation in this study was not statistically significant.

Project description:Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. Materials and Methods Nine prospective patient studies and one prospective volunteer study, performed between 2006 and 2016 with research ethics committee approval and written informed consent from each subject, were included in this single-institution study. A total of 141 tumors and healthy organs were imaged twice (interval between repeated examinations, 45 minutes to 10 days, depending the on study) to assess the repeatability of median and mean ADC estimates. The Levene test was used to determine whether ADC repeatability differed between studies. The Pearson linear correlation coefficient was used to assess correlation between coefficient of variation (CoV) and the year the study started, study size, and volumes of tumors and healthy organs. The repeatability of ADC estimates from small, medium, and large tumors and healthy organs was assessed irrespective of study, and the Levene test was used to determine whether ADC repeatability differed between these groups. Results CoV aggregated across all studies was 4.1% (range for each study, 1.7%-6.5%). No correlation was observed between CoV and the year the study started or study size. CoV was weakly correlated with volume (r = -0.5, P = .1). Repeatability was significantly different between small, medium, and large tumors (P < .05), with the lowest CoV (2.6%) for large tumors. There was a significant difference in repeatability between studies-a difference that did not persist after the study with the largest tumors was excluded. Conclusion ADC is a robust imaging metric with excellent repeatability in extracranial soft tissues across a wide range of tumor sites, sizes, patient populations, and imaging protocol variations. Online supplemental material is available for this article.

Project description:BackgroundModic Changes (MCs) in the vertebral bone marrow were related to back pain in some studies but have uncertain clinical relevance. Diffusion weighted MRI with apparent diffusion coefficient (ADC)-measurements can add information on bone marrow lesions. However, few have studied ADC measurements in MCs. Further studies require reproducible and valid measurements. We expect valid ADC values to be higher in MC type 1 (oedema type) vs type 3 (sclerotic type) vs type 2 (fatty type). Accordingly, the purpose of this study was to evaluate ADC values in MCs for interobserver reproducibility and relation to MC type.MethodsWe used ADC maps (b 50, 400, 800 s/mm2) from 1.5 T lumbar spine MRI of 90 chronic low back pain patients with MCs in the AIM (Antibiotics In Modic changes)-study. Two radiologists independently measured ADC in fixed-sized regions of interests. Variables were MC-ADC (ADC in MC), MC-ADC% (0% = vertebral body, 100% = cerebrospinal fluid) and MC-ADC-ratio (MC-ADC divided by vertebral body ADC). We calculated mean difference between observers ± limits of agreement (LoA) at separate endplates. The relation between ADC variables and MC type was assessed using linear mixed-effects models and by calculating the area under the receiver operating characteristic curve (AUC).ResultsThe 90 patients (mean age 44 years; 54 women) had 224 MCs Th12-S1 comprising type 1 (n = 111), type 2 (n = 91) and type 3 MC groups (n = 22). All ADC variables had higher predicted mean for type 1 vs 3 vs 2 (p < 0.001 to 0.02): MC-ADC (10- 6 mm2/s) 1201/796/576, MC-ADC% 36/21/14, and MC-ADC-ratio 5.9/4.2/3.1. MC-ADC and MC-ADC% had moderate to high ability to discriminate between the MC type groups (AUC 0.73-0.91). MC-ADC-ratio had low to moderate ability (AUC 0.67-0.85). At L4-S1, widest/narrowest LoA were for MC-ADC 20 ± 407/12 ± 254, MC-ADC% 1.6 ± 18.8/1.4 ± 10.4, and MC-ADC-ratio 0.3 ± 4.3/0.2 ± 3.9. Difference between observers > 50% of their mean value was less frequent for MC-ADC (9% of MCs) vs MC-ADC% and MC-ADC-ratio (17-20%).ConclusionsThe MC-ADC variable (highest mean ADC in the MC) had best interobserver reproducibility, discriminated between MC type groups, and may be used in further research. ADC values differed between MC types as expected from previously reported MC histology.

Dataset Information

Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype.

Publications

Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype.

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