Intraobserver and interobserver variability in the calculation of apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (DW-MRI) of breast tumours

Apparent diffusion coefficient values in Modic changes – interobserver reproducibility and relation to Modic type

Background

Modic 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.

Methods

We 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).

Results

The 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%).

Conclusions

The 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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05610-4.

Local ablation of hepatocellular carcinoma by interstitial brachytherapy: prediction of outcome by diffusion-weighted imaging

BACKGROUND

Interstitial brachytherapy (iBT) has become a viable treatment option in the therapy of early and intermediate stage hepatocellular carcinoma (HCC). Prognostic imaging tools to predict patient outcome are missing.

PURPOSE

To assess the predictive value of baseline diffusion-weighted imaging in HCC before iBT with regard to local tumor control and overall survival (OS).

MATERIAL AND METHODS

We retrospectively identified 107 patients who underwent iBT for HCC from 2011 to 2018 from our database. Apparent diffusion coefficient (ADC) values for each treated lesion were analyzed in region of interest measurements. Additionally, explorative combined ratios adjusting total measured lesion area and mean measured lesion area per patient by ADC values were calculated. Measurements underwent a univariate and multivariate Cox regression analysis. The log rank test was then used to verify prognostic cutoff levels for median survival time.

RESULTS

A total of 189 lesions in 81 patients were measured. Median survival of patients was 46.0 months. Neither ADC parameter was indicative of local tumor control. Lesion size >5 cm was associated with lower local tumor control (hazard ratio [HR]=4.292, 95% confidence interval [CI]=1.285-14.331; P = 0.018). Average measured lesion area divided by ADC_min (ADC_{area mean, min}) was identified to independently predict OS (HR=1.994, 95% CI=1.172-3.392; P = 0.011). A cutoff based on the variable's median (0.29 × 10-4 AU) identified patients with poor outcome (OS 36 vs. 61 months) for lower ADC_{area mean, min} values as verified by the log-rank test (P = 0.040).

CONCLUSION

Pre-treatment ADC_{area mean, min} may serve as an independent predictor of OS in patients with HCC undergoing iBT.

Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial

Mean tumor apparent diffusion coefficient (ADC) of breast cancer showed excellent repeatability but only moderate predictive power for breast cancer therapy response in the ACRIN 6698 multicenter imaging trial. Previous single-center studies have shown improved predictive performance for alternative ADC histogram metrics related to low ADC dense tumor volume. Using test/retest (TT/RT) 4 b-value diffusion-weighted imaging acquisitions from pretreatment or early-treatment time-points on 71 ACRIN 6698 patients, we evaluated repeatability for ADC histogram metrics to establish confidence intervals and inform predictive models for future therapy response analysis. Histograms were generated using regions of interest (ROIs) defined separately for TT and RT diffusion-weighted imaging. TT/RT repeatability and intra- and inter-reader reproducibility (on a 20-patient subset) were evaluated using wCV and Bland–Altman limits of agreement for histogram percentiles, low-ADC dense tumor volumes, and fractional volumes (normalized to total histogram volume). Pearson correlation was used to reveal connections between metrics and ROI variability across the sample cohort. Low percentiles (15th and 25th) were highly repeatable and reproducible, wCV < 8.1%, comparable to mean ADC values previously reported. Volumetric metrics had higher wCV values in all cases, with fractional volumes somewhat better but at least 3 times higher than percentile wCVs. These metrics appear most sensitive to ADC changes around a threshold of 1.2 μm²/ms. Volumetric results were moderately to strongly correlated with ROI size. In conclusion, Lower histogram percentiles have comparable repeatability to mean ADC, while ADC-thresholded volumetric measures currently have poor repeatability but may benefit from improvements in ROI techniques.

Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions

BACKGROUND

The purpose of the present meta-analysis was to provide evident data about use of Apparent Diffusion Coefficient (ADC) values for distinguishing malignant and benign breast lesions.

METHODS

MEDLINE library and SCOPUS database were screened for associations between ADC and malignancy/benignancy of breast lesions up to December 2018. Overall, 123 items were identified. The following data were extracted from the literature: authors, year of publication, study design, number of patients/lesions, lesion type, mean value and standard deviation of ADC, measure method, b values, and Tesla strength. The methodological quality of the 123 studies was checked according to the QUADAS-2 instrument. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used without any further correction to account for the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated separately for benign and malign lesions.

RESULTS

The acquired 123 studies comprised 13,847 breast lesions. Malignant lesions were diagnosed in 10,622 cases (76.7%) and benign lesions in 3225 cases (23.3%). The mean ADC value of the malignant lesions was 1.03 × 10^- 3 mm²/s and the mean value of the benign lesions was 1.5 × 10^- 3 mm²/s. The calculated ADC values of benign lesions were over the value of 1.00 × 10^- 3 mm²/s. This result was independent on Tesla strength, choice of b values, and measure methods (whole lesion measure vs estimation of ADC in a single area).

CONCLUSION

An ADC threshold of 1.00 × 10^- 3 mm²/s can be recommended for distinguishing breast cancers from benign lesions.

Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial

BACKGROUND

Quantitative diffusion-weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker.

PURPOSE

To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi-institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures.

STUDY TYPE

Prospective.

SUBJECTS

In all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer.

FIELD STRENGTH/SEQUENCE

DWI was acquired before and after patient repositioning using a four b-value, single-shot echo-planar sequence at 1.5T or 3.0T.

ASSESSMENT

A QA procedure by trained operators assessed artifacts, fat suppression, and signal-to-noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast-enhanced images. Twenty cases were evaluated multiple times to assess intra- and interoperator variability. Segmentation similarity was assessed via the Sørenson-Dice similarity coefficient.

STATISTICAL TESTS

Repeatability and reproducibility were evaluated using within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson's correlation coefficients.

RESULTS

In all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane-based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10^-3 mm² /sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96).

DATA CONCLUSION

Breast tumor ADC can be measured with excellent repeatability and reproducibility in a multi-institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1617-1628.

Association among T2 signal intensity, necrosis, ADC and Ki-67 in estrogen receptor-positive and HER2-negative invasive ductal carcinoma

PURPOSE

To determine whether T2 signal intensity, necrosis, and ADC values are associated with Ki-67 in patients with Estrogen Receptor (ER)-positive and Human epidermal growth factor receptor type 2 (HER2)-negative invasive ductal carcinoma (IDC).

MATERIALS AND METHODS

Between March 2012 and February 2013, one hundred eighty seven women with ER-positive and HER2-negative IDC who underwent breast MRI and subsequent surgery were included. Intratumoral signal intensity was evaluated based on a combination of T2-weighted (low or equal, high, or very high) and contrast-enhanced MR images (enhancement or not). Necrosis was defined as very high T2 and no enhancement. Using the analysis of variance and pairwise t-test, a model based on intratumoral signal intensity was developed to assess Ki-67 of the surgical specimen. Inter-observer agreement for the developed model was analyzed. Conventional mean and minimum apparent diffusion coefficient (ADC) measurements were performed and correlated with Ki-67.

RESULTS

As the grade of the developed model increased (Grade I: low or equal T2, Grade II: high T2, or necrosis < 50%, Grade III: necrosis ≥ 50%), mean Ki-67 significantly increased (Grade I to III: 12.5%, 17.6%, 45.0%, respectively; P < 0.001). Good inter-observer agreement was found for the model (κ = 0.846, P < 0.001). ADC did not show significant correlations with Ki-67 (Pearson's correlation coefficient, 0.140 [P = 0.057] for mean ADC; -0.079 [P = 0.284] for minimum ADC).

CONCLUSION

Intratumoral signal intensity but not ADC was associated with Ki-67 in patients with ER-positive and HER2-negative IDC.

Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variability

PURPOSE

We aimed to compare two different methods of region of interest (ROI) demarcation and determine interobserver variability on apparent diffusion coefficient (ADC) in breast lesions.

METHODS

Thirty-two patients with 39 lesions were evaluated with a 3.0 Tesla scanner using a diffusion-weighted sequence with several b-values. Two observers independently performed the ADC measurements using: 1) a small fixed area of 10 mm2 ROI within the area with highest restriction; 2) a large ROI so as to include the whole lesion. Differences were assessed using the Wilcoxon-rank test. Bland-Altman method and Spearman coefficient were applied for interobserver variability and correlation analysis.

RESULTS

ADC values measured using the two ROI demarcation methods were significantly different for both observers (P = 0.026; P = 0.033). There was no interobserver variability in ADC values using either method (large ROI, P = 0.21; small ROI, P = 0.64). ADC values of malignant lesions were significantly different between the two methods (P < 0.001). Variability in ADC was ≤0.008×10-3 mm2/s for both methods. When using the same method, ADC values were significantly correlated between the observers (small ROI: r=0.990, P < 0.001; large ROI: r=0.985, P < 0.001).

CONCLUSION

The choice of ROI demarcation method influences ADC measurements. Small ROIs show less overlap in ADC values and higher ADC reproducibility, suggesting that this method may improve lesion discrimination. Interobserver variability was low for both methods.

Diffusion-weighted MRI of breast lesions: a prospective clinical investigation of the quantitative imaging biomarker characteristics of reproducibility, repeatability, and diagnostic accuracy

Diffusion-weighted MRI (DWI) provides insights into tissue microstructure by visualization and quantification of water diffusivity. Quantitative evaluation of the apparent diffusion coefficient (ADC) obtained from DWI has been proven helpful for differentiating between malignant and benign breast lesions, for cancer subtyping in breast cancer patients, and for prediction of response to neoadjuvant chemotherapy. However, to further establish DWI of breast lesions it is important to evaluate the quantitative imaging biomarker (QIB) characteristics of reproducibility, repeatability, and diagnostic accuracy. In this intra-individual prospective clinical study 40 consecutive patients with suspicious findings, scheduled for biopsy, underwent an identical 3T breast MRI protocol of the breast on two consecutive days (>24 h). Mean ADC of target lesions was assessed (two independent readers) in four separate sessions. Reproducibility, repeatability, and diagnostic accuracy between examinations (E1, E2), readers (R1, R2), and measurements (M1, M2) were assessed with intraclass correlation coefficients (ICCs), coefficients of variation (CVs), Bland-Altman plots, and receiver operating characteristic (ROC) analysis with calculation of the area under the ROC curve (AUC). The standard of reference was either histopathology (n = 38) or imaging follow-up of up to 24 months (n = 2). Eighty breast MRI examinations (median E1-E2, 2 ± 1.7 days, 95% confidence interval (CI) 1-2 days, range 1-11 days) in 40 patients (mean age 56, standard deviation (SD) ±14) were evaluated. In 55 target lesions (mean size 25.2 ± 20.8 (SD) mm, range 6-106 mm), mean ADC values were significantly (P < 0.0001) higher in benign (1.38, 95% CI 1.27-1.49 × 10(-3)  mm(2) /s) compared with malignant (0.86, 95% CI 0.81-0.91 × 10(-) (3)  mm(2) /s) lesions. Reproducibility and repeatability showed high agreement for repeated examinations, readers, and measurements (all ICCs >0.9, CVs 3.2-8%), indicating little variation. Bland-Altman plots demonstrated no systematic differences, and diagnostic accuracy was not significantly different in the two repeated examinations (all ROC curves >0.91, P > 0.05). High reproducibility, repeatability, and diagnostic accuracy of DWI provide reliable characteristics for its use as a potential QIB, to further improve breast lesion detection, characterization, and treatment monitoring of breast lesions.

Diagnostic Value of Diffusion-weighted Imaging and Apparent Diffusion Coefficient Values in the Differentiation of Breast Lesions, Histpathologic Subgroups and Correlatıon with Prognostıc Factors using 3.0 Tesla MR

OBJECTIVE

The aim of this study was to evaluate the effect of the apparent diffusion coefficient (ADC) and diffusion-weighted imaging in differentiating benign from malignant breast lesions, histopathologic subtypes of breast tumors, and to find a correlation with prognostic factors using 3T MR.

MATERIALS AND METHODS

A total of 165 patients aged between 16 and 78 years with 181 histopathologically-verifed breast lesions were enrolled in this study. A 3T MR system and bilateral phased array breast coil was used. Diffusion-weighted imaging was performed with spin echo "echo planar" with "b" values: 50, 400, and 800 seconds/mm². ADC values were calculated for normal fibroglandular tissue and breast lesions. ADC values of independent groups were compared using Student's t-test. ROC analysis was used to find a threshold ADC value in the differentiation of lesions.

RESULTS

The mean ADC values were 1.35±0.16 × 10^-3 mm²/s for normal fibroglandular tissue, 1.41±0.24 × 10^-3 mm²/s for benign breast lesions and 0.83±0.19 × 10^-3 mm²/s for malignant breast lesions. The AUC with ROC analysis was 0.945 and the threshold for ADC was 1.08 × 10^-3 mm²/s with a sensitivity and specificity of 92% and 92%, respectively. The threshold value for ADC ratio was 0.9 with 96% sensitivity and 89% specificity. The mean ADC of malignant breast lesions was statistically lower for benign lesions (p<0.01). We found no correlation between the mean ADC values and ER-PR receptor, Her2, and Ki-67 values.

CONCLUSION

Diffusion-weighted imaging has high diagnostic value with high sensitivity and specificity in differentiating malignant and benign breast lesions.

Inter- and intraobserver agreement of ADC measurements of lung cancer in free breathing, breath-hold and respiratory triggered diffusion-weighted MRI

OBJECTIVE

To prospectively evaluate the inter- and intraobserver agreement of apparent diffusion coefficient (ADC) measurements in free breathing, breath-hold, and respiratory triggered diffusion-weighted imaging (DWI) of lung cancer.

METHODS

Twenty-two patients with lung cancer (tumor size >2cm) underwent DWIs (3.0T) in three imaging methods. Lesion ADCs were measured twice by both of the two independent observers and compared.

RESULTS

No statistical significance was found among methods, though respiratory-triggered DWI tended to have higher ADCs than breath-hold DWI. Great inter- and intraobserver agreement was shown.

CONCLUSION

ADCs had good inter- and intraobserver agreement in all three DWI methods.

Combining standardized uptake value of FDG-PET and apparent diffusion coefficient of DW-MRI improves risk stratification in head and neck squamous cell carcinoma

OBJECTIVES

To assess the independent prognostic value of standardized uptake value (SUV) and apparent diffusion coefficient (ADC), separately and combined, in order to evaluate if the combination of these two variables allows further prognostic stratification of patients with head and neck squamous cell carcinomas (HNSCC).

METHODS

Pretreatment SUV and ADC were calculated in 57 patients with HNSCC. Mean follow-up was 21.3 months. Semiquantitative analysis of primary tumours was performed using SUV_maxT/B, ADC_mean, ADC_min and ADC_max. The prognostic value of SUV_maxT/B, ADC_mean, ADC_min and ADC_max in predicting disease-free survival (DFS) was evaluated with log-rank test and Cox regression models.

RESULTS

Patients with SUV_maxT/B ≥5.75 had an overall worse prognosis (p = 0.003). After adjusting for lymph node status and diameter, SUV_maxT/B and ADC_min were both significant predictors of DFS with hazard ratio (HR) = 10.37 (95 % CI 1.22-87.95) and 3.26 (95 % CI 1.20-8.85) for SUV_maxT/B ≥5.75 and ADC_min ≥0.58 × 10^-3 mm²/s, respectively. When the analysis was restricted to subjects with SUV_maxT/B ≥5.75, high ADC_min significantly predicted a worse prognosis, with adjusted HR = 3.11 (95 % CI 1.13-8.55).

CONCLUSIONS

The combination of SUV_maxT/B and ADC_min improves the prognostic role of the two separate parameters; patients with high SUV_maxT/B and high ADC_min are associated with a poor prognosis.

KEY POINTS

• High SUV _maxT/B is a poor prognostic factor in HNSCC • High ADC _min is a poor prognostic factor in HNSCC • In patients with high SUV _maxT/B , high ADC _min identified those with worse prognosis.

MR mammography using diffusion-weighted imaging in evaluating breast cancer: a correlation with proliferation index

PURPOSE

To evaluate whether the variation of the apparent diffusion coefficient (ADC) values obtained with DWI can predict elevated levels of Ki67 proliferation index and aggressive subtypes in patients with breast cancer.

MATERIALS AND METHODS

Breast MRI studies of 115 patients (mean age 57.3 years, range 36-81 years) with a biopsy-proven breast cancers were evaluated in this retrospective IRB-approved study. Examinations were performed on a 1.5 T magnet and included a Single-Shot Echoplanar DWI sequence with b values of 0 and 1000 s/mm(2). For each target lesion, ADC was measured. ADC values were compared considering Ki67 status (≥20 % or <20 %), histology, grade (G1, G2 or G3) and clinical-pathological classification (Luminal A, Luminal B HER2-positive, Luminal B HER-2 negative, HER-2 enriched and Triple Negative). Mann-Whitney U test and Kruskal-Wallis test were used for comparisons and receiver operating characteristic (ROC) curves were obtained. Inter- and intra-reader variability was evaluated in a subset of 40 patients, using interclass correlation coefficient (ICC) and Bland-Altman plots.

RESULTS

Of 115 lesions, 53 (46.1 %) were assessed as Ki67 positive and 62 (53.9 %) as Ki67 negative. ADC values were significantly (p < 0.0001) lower in Ki67-positive patients (median 0.86 × 10(-3) mm(2)/s; interquartile range 0.75-0.92) compared to Ki67-negative (median 1.03 × 10(-3) mm(2)/s; interquartile range 0.92-1.13). Median ADC was also lower in G2 and G3 cancer and in the Luminal B Her2-negative subtype (p = 0.0015). No differences were found when evaluating histology. ROC curve showed a sensitivity and specificity of 83.0 and 66.1 %, respectively, when using a cutoff of 0.95 s/mm(2) to differentiate Ki67-positive from Ki67-negative cancers. Inter- and intra-reader variability was moderate (ICC = 0.623; ICC = 0.548, respectively). No systematic differences were identified with Bland-Altman plots.

CONCLUSIONS

Lower ADC values are associated with elevated Ki67 proliferation index and more aggressive pathologic features. Moderate agreement in ADC measurement could be a limitation.

Diffusion-weighted imaging for head and neck squamous cell carcinoma: quantifying repeatability to understand early treatment-induced change

OBJECTIVE

The purpose of this study was to define baseline variability of apparent diffusion coefficient (ADC) on diffusion-weighted MR imaging (DWI) in patients with head and neck squamous cell carcinoma (HNSCC) and to compare it with early treatment-induced ADC change.

SUBJECTS AND METHODS

Patients with American Joint Committee on Cancer stages III and IV HNSCC were imaged with two baseline DWI examinations 1 week apart and a third DWI examination during the 2nd week of curative-intent chemoradiation therapy. Mean ADC was measured in the primary tumor and largest lymph node for each patient on the three DWI scans. Mean baseline percentage differences (%∆ADC) were compared with intratreatment change. The repeatability coefficient for baseline %∆ADC was calculated and compared with intratreatment %∆ADC. Repeatability was also assessed with Bland-Altman plots and the intraclass correlation coefficient (ICC).

RESULTS

Sixteen patients underwent double baseline imaging, with 14 also undergoing intratreatment imaging. Baseline nodal disease ADC could be measured in 16 patients, but ADC in primary tumors could only be measured in five patients. The nodal mean (SD) baseline %∆ADC was 8% (± 7%), which was significantly different compared with intratreatment changes of 32% (± 31%) (p = 0.01). Baseline ICC was 0.86 for nodal disease and 0.99 for primary tumor (excellent correlation). The calculated repeatability coefficient for baseline nodal ADC was 15%. No patients had decreases in intratreatment ADC of more than 15%.

CONCLUSION

Baseline ADC variability for HNSCC is less than intratreatment ADC change for nodal disease. Assessment of response should consider intrinsic baseline variability.

Rim sign in breast lesions on diffusion-weighted magnetic resonance imaging: diagnostic accuracy and clinical usefulness

PURPOSE

To investigate the diagnostic accuracy and clinical usefulness of the rim sign in breast lesions observed in diffusion-weighted magnetic resonance imaging (DWI).

MATERIALS AND METHODS

The magnetic resonance imaging (MRI) findings of 98 pathologically confirmed lesions (62 malignant and 36 benign) in 84 patients were included. Five breast radiologists were asked to independently review the breast MRI results, to grade the degree of high peripheral signal, the "rim sign," in the DWI, and to confirm the mean apparent diffusion coefficient (ADCmean ) values. We analyzed the diagnostic accuracy and compared the consensus (when ≥ 4 of 5 independent reviewers agreed) results of the rim sign with the ADCmean values. Additionally, we evaluated the correlation between the dynamic contrast-enhanced (DCE)-MRI morphologic appearance and DWI rim sign.

RESULTS

According to the consensus results, the rim sign in DWI was observed on 59.7% of malignant lesions and 19.4% of benign lesions. The sensitivity, specificity, and area under the curve (AUC) value for the rim sign in DWI were 59.7%, 80.6%, and 0.701, respectively. The sensitivity, specificity, and AUC value for the ADCmean value (criteria ≤ 1.46 × 10(-3) mm(2) /sec) were 82.3%, 63.9%, and 0.731, respectively. Based on consensus, no correlation was observed between the DCE-MRI and DWI rim signs.

CONCLUSION

In DWI, a high-signal rim is a valuable morphological feature for improving specificity in DWI.

MR scanner systems should be adequately characterized in diffusion-MRI of the breast

Breast imaging represents a relatively recent and promising field of application of quantitative diffusion-MRI techniques. In view of the importance of guaranteeing and assessing its reliability in clinical as well as research settings, the aim of this study was to specifically characterize how the main MR scanner system-related factors affect quantitative measurements in diffusion-MRI of the breast. In particular, phantom acquisitions were performed on three 1.5 T MR scanner systems by different manufacturers, all equipped with a dedicated multi-channel breast coil as well as acquisition sequences for diffusion-MRI of the breast. We assessed the accuracy, inter-scan and inter-scanner reproducibility of the mean apparent diffusion coefficient measured along the main orthogonal directions (<ADC>) as well as of diffusion-tensor imaging (DTI)-derived mean diffusivity (MD) measurements. Additionally, we estimated spatial non-uniformity of <ADC> (NU_<ADC>) and MD (NU_MD) maps. We showed that the signal-to-noise ratio as well as overall calibration of high strength diffusion gradients system in typical acquisition sequences for diffusion-MRI of the breast varied across MR scanner systems, introducing systematic bias in the measurements of diffusion indices. While <ADC> and MD values were not appreciably different from each other, they substantially varied across MR scanner systems. The mean of the accuracies of measured <ADC> and MD was in the range [−2.3%,11.9%], and the mean of the coefficients of variation for <ADC> and MD measurements across MR scanner systems was 6.8%. The coefficient of variation for repeated measurements of both <ADC> and MD was < 1%, while NU_<ADC> and NU_MD values were <4%. Our results highlight that MR scanner system-related factors can substantially affect quantitative diffusion-MRI of the breast. Therefore, a specific quality control program for assessing and monitoring the performance of MR scanner systems for diffusion-MRI of the breast is highly recommended at every site, especially in multicenter and longitudinal studies.

Interobserver agreement of semi-automated and manual measurements of functional MRI metrics of treatment response in hepatocellular carcinoma

PURPOSE

To assess the interobserver agreement in 50 patients with hepatocellular carcinoma (HCC) before and 1 month after intra-arterial therapy (IAT) using two semi-automated methods and a manual approach for the following functional, volumetric and morphologic parameters: (1) apparent diffusion coefficient (ADC), (2) arterial phase enhancement (AE), (3) portal venous phase enhancement (VE), (4) tumor volume, and assessment according to (5) the Response Evaluation Criteria in Solid Tumors (RECIST), and (6) the European Association for the Study of the Liver (EASL).

MATERIALS AND METHODS

This HIPAA-compliant retrospective study had institutional review board approval. The requirement for patient informed consent was waived. Tumor ADC, AE, VE, volume, RECIST, and EASL in 50 index lesions was measured by three observers. Interobserver reproducibility was evaluated using intraclass correlation coefficients (ICC). P<0.05 was considered to indicate a significant difference.

RESULTS

Semi-automated volumetric measurements of functional parameters (ADC, AE, and VE) before and after IAT as well as change in tumor ADC, AE, or VE had better interobserver agreement (ICC=0.830-0.974) compared with manual ROI-based axial measurements (ICC=0.157-0.799). Semi-automated measurements of tumor volume and size in the axial plane before and after IAT had better interobserver agreement (ICC=0.854-0.996) compared with manual size measurements (ICC=0.543-0.596), and interobserver agreement for change in tumor RECIST size was also higher using semi-automated measurements (ICC=0.655) compared with manual measurements (ICC=0.169). EASL measurements of tumor enhancement in the axial plane before and after IAT ((ICC=0.758-0.809), and changes in EASL after IAT (ICC=0.653) had good interobserver agreement.

CONCLUSION

Semi-automated measurements of functional changes assessed by ADC and VE based on whole-lesion segmentation demonstrated better reproducibility than ROI-based axial measurements, or RECIST or EASL measurements.

Development of a diagnostic test set to assess agreement in breast pathology: practical application of the Guidelines for Reporting Reliability and Agreement Studies (GRRAS)

Background

Diagnostic test sets are a valuable research tool that contributes importantly to the validity and reliability of studies that assess agreement in breast pathology. In order to fully understand the strengths and weaknesses of any agreement and reliability study, however, the methods should be fully reported. In this paper we provide a step-by-step description of the methods used to create four complex test sets for a study of diagnostic agreement among pathologists interpreting breast biopsy specimens. We use the newly developed Guidelines for Reporting Reliability and Agreement Studies (GRRAS) as a basis to report these methods.

Methods

Breast tissue biopsies were selected from the National Cancer Institute-funded Breast Cancer Surveillance Consortium sites. We used a random sampling stratified according to woman’s age (40–49 vs. ≥50), parenchymal breast density (low vs. high) and interpretation of the original pathologist. A 3-member panel of expert breast pathologists first independently interpreted each case using five primary diagnostic categories (non-proliferative changes, proliferative changes without atypia, atypical ductal hyperplasia, ductal carcinoma in situ, and invasive carcinoma). When the experts did not unanimously agree on a case diagnosis a modified Delphi method was used to determine the reference standard consensus diagnosis. The final test cases were stratified and randomly assigned into one of four unique test sets.

Conclusions

We found GRRAS recommendations to be very useful in reporting diagnostic test set development and recommend inclusion of two additional criteria: 1) characterizing the study population and 2) describing the methods for reference diagnosis, when applicable.

Readout-segmented echo-planar imaging improves the diagnostic performance of diffusion-weighted MR breast examinations at 3.0 T

PURPOSE

To qualitatively and quantitatively compare the diagnostic value of diffusion-weighted (DW) magnetic resonance (MR) imaging based on standard single-shot echo-planar imaging and readout-segmented echo-planar imaging in patients with breast cancer at 3.0 T.

MATERIALS AND METHODS

Institutional review board approval and written informed consent were obtained. Forty-seven patients with 49 histopathologically verified lesions were included in this study. In all patients, DW imaging, with single-shot echo-planar imaging and readout-segmented echo-planar imaging with comparable imaging parameters, was performed with a 3.0-T MR imager. Two independent readers visually assessed image quality and lesion conspicuity, and image properties (ie, signal-to-noise ratio, contrast, geometric distortions) were quantified. Regions of interest were drawn in all lesions (28 malignant, 21 benign) and in the normal breast parenchyma to investigate differences in apparent diffusion coefficient (ADC). Diagnostic accuracy was calculated on the basis of an ADC threshold of 1.25 × 10(-3) mm(2)/sec.

RESULTS

Each reader found a higher diagnostic accuracy for readout-segmented (96%) than for single-shot (90%) echo-planar imaging. The area under the curve for readout-segmented echo-planar imaging (0.981) was significantly larger than for single-shot echo-planar imaging (0.867) (P = .026). There was no significant difference in the ADC obtained by using either DW imaging method. Lesion conspicuity and image quality of readout-segmented echo-planar imaging were rated superior to those of single-shot echo-planar imaging (P < .001). Readout-segmented echo-planar imaging reduced geometric distortions by a factor of three.

CONCLUSION

DW imaging based on readout-segmented echo-planar imaging provided significantly higher image quality and lesion conspicuity than single-shot echo-planar imaging by reducing geometric distortions, image blurring, and artifact level with a clinical high-field-strength MR imager. Thereby, readout-segmented echo-planar imaging reached a higher diagnostic accuracy for the differentiation of benign and malignant breast lesions.