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Objective. To investigate if histogram analysis and visually assessed heterogeneity of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping can predict molecular subtypes of invasive breast cancers.
Materials and Methods. In this retrospective study, 91 patients with invasive breast carcinoma who underwent preoperative magnetic resonance imaging (MRI) with DWI at our institution were included. Two radiologists delineated a 2-D region of interest (ROI) on ADC maps in consensus. Tumors were also independently classified into low and high heterogeneity based on visual assessment of DWI. First-order statistics extracted through histogram analysis within the ROI of the ADC maps (mean, 10th percentile, 50th percentile, 90th percentile, standard deviation, kurtosis, and skewness) and visually assessed heterogeneity were evaluated for associations with tumor receptor status (ER, PR, and HER2 status) as well as molecular subtype.
esults. HER2-positive lesions demonstrated significantly higher mean (), Perc50 (), and Perc90 (), with AUCs of 0.605, 0.592, and 0.652, respectively, than HER2-negative lesions. No significant differences were found in the histogram values for ER and PR statuses. Neither quantitative histogram analysis based on ADC maps nor qualitative visual heterogeneity assessment of DWI images was able to significantly differentiate between molecular subtypes, i.e., luminal A versus all other subtypes (luminal B, HER2-enriched, and triple negative) combined, luminal A and B combined versus HER2-enriched and triple negative combined, and triple negative versus all other types combined.
Conclusion. Histogram analysis and visual heterogeneity assessment cannot be used to differentiate molecular subtypes of invasive breast cancer.
Background: To evaluate the diagnostic performance of radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (CE-MRI) for the assessment of breast cancer receptor status and molecular subtypes.
Methods: One hundred and forty-three patients with biopsy-proven breast cancer who underwent CE-MRI at 3 T were included in this IRB-approved HIPAA-compliant retrospective study. The training dataset comprised 91 patients (luminal A, n = 49; luminal B, n = 8; HER2-enriched, n = 11; triple negative, n = 23), while the validation dataset comprised 52 patients from a second institution (luminal A, n = 17; luminal B, n = 17; triple negative, n = 18). Radiomic analysis of manually segmented tumors included calculation of features derived from the first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient (GRA), autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry (GEO). Fisher, probability of error and average correlation (POE + ACC), and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise radiomic-based separation of receptor status and molecular subtypes. Histopathology served as the standard of reference.
Results: In the training dataset, radiomic signatures yielded the following accuracies > 80%: luminal B vs. luminal A, 84.2% (mainly based on COM features); luminal B vs. triple negative, 83.9% (mainly based on GEO features); luminal B vs. all others, 89% (mainly based on COM features); and HER2-enriched vs. all others, 81.3% (mainly based on COM features). Radiomic signatures were successfully validated in the separate validation dataset for luminal A vs. luminal B (79.4%) and luminal B vs. triple negative (77.1%).
Conclusions: In this preliminary study, radiomic signatures with CE-MRI enable the assessment of breast cancer receptor status and molecular subtypes with high diagnostic accuracy. These results need to be confirmed in future larger studies.
Background: The management of intraductal papilloma without atypia (IDP) in breast needle biopsy remains controversial. This study investigates the upgrade rate of IDP to carcinoma and clinical and radiologic features predictive of an upgrade. Methods: Patients with a diagnosis of IDP on image-guided (mammography, ultrasound, magnetic resonance imaging) core needle or vacuum-assisted biopsy and surgical excision of this lesion at a certified breast center between 2007 and 2017 were included in this institutional review board-approved retrospective study. Appropriate statistical tests were performed to assess clinical and radiologic characteristics associated with an upgrade to malignancy at excision. Results: For 60 women with 62 surgically removed IDPs, the upgrade rate to malignancy was 16.1% (10 upgrades, 4 invasive ductal carcinoma, 6 ductal carcinoma in situ). IDPs with upgrade to carcinoma showed a significantly greater distance to the nipple (63.5 vs. 36.8 mm; p = 0.012). No significant associations were found between upgrade to carcinoma and age, menopausal status, lesion size, microcalcifications, BI-RADS descriptors, initial BI-RADS category, and biopsy modality. Conclusion: The upgrade rate at excision for IDPs diagnosed with needle biopsy was higher than expected according to some guideline recommendations. Observation only might not be appropriate for all patients with IDP, particularly for those with peripheral IDP.
BACKGROUND: Evaluation of latest generation automated attenuation-based tube potential selection (ATPS) impact on image quality and radiation dose in contrast-enhanced chest-abdomen-pelvis computed tomography examinations for gynaecologic cancer staging.
METHODS: This IRB approved single-centre, observer-blinded retrospective study with a waiver for informed consent included a total of 100 patients with contrast-enhanced chest-abdomen-pelvis CT for gynaecologic cancer staging. All patients were examined with activated ATPS for adaption of tube voltage to body habitus. 50 patients were scanned on a third-generation dual-source CT (DSCT), and another 50 patients on a second-generation DSCT. Predefined image quality setting remained stable between both groups at 120 kV and a current of 210 Reference mAs. Subjective image quality assessment was performed by two blinded readers independently. Attenuation and image noise were measured in several anatomic structures. Signal-to-noise ratio (SNR) was calculated. For the evaluation of radiation exposure, CT dose index (CTDIvol) values were compared.
RESULTS: Diagnostic image quality was obtained in all patients. The median CTDIvol (6.1 mGy, range 3.9-22 mGy) was 40 % lower when using the algorithm compared with the previous ATCM protocol (median 10.2 mGy · cm, range 5.8-22.8 mGy). A reduction in potential to 90 kV occurred in 19 cases, a reduction to 100 kV in 23 patients and a reduction to 110 kV in 3 patients of our experimental cohort. These patients received significantly lower radiation exposure compared to the former used protocol.
CONCLUSION: Latest generation automated ATPS on third-generation DSCT provides good diagnostic image quality in chest-abdomen-pelvis CT while average radiation dose is reduced by 40 % compared to former ATPS protocol on second-generation DSCT.
One limitation of mechanical thrombectomy (MT) is clot migration during procedure. This might be caused by abruption of the trapped thrombus at the distal access catheter (DAC) tip during stent-retriever retraction due to the cylindrical shaped tip of the DAC. Aiming to solve this problem, this study evaluates the proof-of-concept of a new designed funnel-shaped tip, in an experimental in vitro setting. Two catheter models, one with a funnel-shaped tip and one with a cylindrical-shaped tip, were compared in an experimental setup. For MT a self-made vessel model and thrombi generated from pig’s blood were used. MT was performed 20 times for each device using two different stent-retrievers, 10 times respectively. For the funnel-shaped model: for both stent-retrievers (Trevo XP ProVue 3/20 mm; Trevo XP ProVue 4/20 mm) MT was successful at first pass in 9/10 (90%), respectively. For the cylindrical-shaped model: MT was successful at first pass in 5/10 (50%) with the smaller stent-retriever and in 6/10 (60%) with the larger stent-retriever. The experiments show a better recanalization rate for funnel-shaped tips, than for cylindrical-shaped tips. These results are indicating a good feasibility for this new approach, thus the development of a prototype catheter seems reasonable.
Background: The MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI proto-col contain T2-weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imag-ing (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, andT2-weighted imaging are most strongly associated with a breast cancer diagnosis.Purpose/Hypothesis: To develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating Ameri-can College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2-weighted imaging, andDWI with apparent diffusion coefficient (ADC) mapping.Study Type: Retrospective.Subjects: In all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwentmpMRI from December 2010 to September 2014.Field Strength/Sequence: IR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBEVolume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography withstochastic Trajectories.Assessment: Two radiologists in consensus and another radiologist independently evaluated the mpMRI data. Charac-teristics for mass (n = 182) and nonmass (n = 28) lesions were recorded on DCE and T2-weighted imaging accordingto BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2-weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoffvalue of ≤1.25 × 10−3mm2/sec for differentiation between benign and malignant lesions. Histopathology was the stan-dard of reference.Statistical Tests: χ2test, Fisher’s exact test, Kruskal–Wallis test, Pearson correlation coefficient, multivariate logistic regres-sion analysis, Hosmer–Lemeshow test of goodness-of-fit, receiver operating characteristics analysis.Results: In Model 1, ADCmean (P = 0.0031), mass margins with DCE (P = 0.0016), and delayed enhancement with DCE(P = 0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean(P = 0.0031), mass margins with DCE (P = 0.0012), initial enhancement (P = 0.0422), and delayed enhancement with DCE(P = 0.0065) to be significantly independently associated with breast cancer diagnosis. T2-weighted imaging variables werenot included in the final models