Repurposing the Public BraTS Dataset for Postoperative Brain Tumour Treatment Response Monitoring.

The Brain Tumor Segmentation (BraTS) Challenge has been a main driver of the development of deep learning (DL) algorithms and provides by far the largest publicly available expert-annotated brain tumour dataset but contains solely preoperative examinations. The aim of our study was to facilitate the use of the BraTS dataset for training DL brain tumour segmentation algorithms for a postoperative setting. To this end, we introduced an automatic conversion of the three-label BraTS annotation protocol to a two-label annotation protocol suitable for postoperative brain tumour segmentation. To assess the viability of the label conversion, we trained a DL algorithm using both the three-label and the two-label annotation protocols. We assessed the models pre- and postoperatively and compared the performance with a state-of-the-art DL method. The DL algorithm trained using the BraTS three-label annotation misclassified parts of 10 out of 41 fluid-filled resection cavities in 72 postoperative glioblastoma MRIs, whereas the two-label model showed no such inaccuracies. The tumour segmentation performance of the two-label model both pre- and postoperatively was comparable to that of a state-of-the-art algorithm for tumour volumes larger than 1 cm3. Our study enables using the BraTS dataset as a basis for the training of DL algorithms for postoperative tumour segmentation.

Introduction of one-view tomosynthesis in population-based mammography screening: Impact on detection rate, interval cancer rate and false-positive rate.

OBJECTIVE: To assess performance endpoints of a combination of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) compared with FFDM only in breast cancer screening. MATERIALS AND METHODS: This was a prospective population-based screening study, including eligible (50-69 years) women attending the Capital Region Mammography Screening Program in Denmark. All attending women were offered FFDM. A subgroup was consecutively allocated to a screening room with DBT. All FFDM and DBT underwent independent double reading, and all women were followed up for 2 years after screening date or until next screening date, whichever came first. RESULTS: 6353 DBT + FFDM and 395 835 FFDM were included in the analysis and were undertaken in 196 267 women in the period from 1 November 2012 to 12 December 2018. Addition of DBT increased sensitivity: 89.9% (95% confidence interval (CI): 81.0-95.5) for DBT + FFDM and 70.1% (95% CI: 68.6-71.6) for FFDM only, p < 0.001. Specificity remained similar: 98.2% (95% CI: 97.9-98.5) for DBT + FFDM and 98.3% (95% CI: 98.2-98.3) for FFDM only, p = 0.9. Screen-detected cancer rate increased statistically significantly: 11.18/1000 for DBT + FFDM and 6.49/1000 for FFDM only, p < 0.001. False-positive rate was unchanged: 1.75% for DBT + FFDM and 1.73% for FFDM only, p = 0.9. Positive predictive value for recall was 39.0% (95% CI: 31.9-46.5) for DBT + FFDM and 27.3% (95% CI: 26.4-28.2), for FFDM only, p < 0.0005. The interval cancer rate decreased: 1.26/1000 for DBT + FFDM and 2.76/1000 for FFDM only, p = 0.02. CONCLUSION: DBT + FFDM yielded a statistically significant increase in cancer detection and program sensitivity.

Prognostic relevance of radiological findings on early postoperative MRI for 187 consecutive glioblastoma patients receiving standard therapy.

Several prognostic factors are known to influence survival for patients treated with IDH-wildtype glioblastoma, but unknown factors may remain. We aimed to investigate the prognostic implications of early postoperative MRI findings. A total of 187 glioblastoma patients treated with standard therapy were consecutively included. Patients either underwent a biopsy or surgery followed by an early postoperative MRI. Progression-free survival (PFS) and overall survival (OS) were analysed for known prognostic factors and MRI-derived candidate factors: resection status as defined by the response assessment in neuro-oncology (RANO)-working group (no contrast-enhancing residual tumour, non-measurable contrast-enhancing residual tumour, or measurable contrast-enhancing residual tumour) with biopsy as reference, contrast enhancement patterns (no enhancement, thin linear, thick linear, diffuse, nodular), and the presence of distant tumours. In the multivariate analysis, patients with no contrast-enhancing residual tumour or non-measurable contrast-enhancing residual tumour on the early postoperative MRI displayed a significantly improved progression-free survival compared with patients receiving only a biopsy. Only patients with non-measurable contrast-enhancing residual tumour showed improved overall survival in the multivariate analysis. Contrast enhancement patterns were not associated with survival. The presence of distant tumours was significantly associated with both poor progression-free survival and overall survival and should be considered incorporated into prognostic models.

Timing of Early Postoperative MRI following Primary Glioblastoma Surgery-A Retrospective Study of Contrast Enhancements in 311 Patients.

An early postoperative MRI is recommended following Glioblastoma surgery. This retrospective, observational study aimed to investigate the timing of an early postoperative MRI among 311 patients. The patterns of the contrast enhancement (thin linear, thick linear, nodular, and diffuse) and time from surgery to the early postoperative MRI were recorded. The primary endpoint was the frequencies of the different contrast enhancements within and beyond the 48-h from surgery. The time dependence of the resection status and the clinical parameters were analysed as well. The frequency of the thin linear contrast enhancements significantly increased from 99/183 (50.8%) within 48-h post-surgery to 56/81 (69.1%) beyond 48-h post-surgery. Similarly, MRI scans with no contrast enhancements significantly declined from 41/183 (22.4%) within 48-h post-surgery to 7/81 (8.6%) beyond 48-h post-surgery. No significant differences were found for the other types of contrast enhancements and the results were robust in relation to the choice of categorisation of the postoperative periods. Both the resection status and the clinical parameters were not statistically different in patients with an MRI performed before and after 48 h. The findings suggest that surgically induced contrast enhancements are less frequent when an early postoperative MRI is performed earlier than 48-h, supporting the recommendation of a 48-h window for an early postoperative MRI.

Evaluation of the HD-GLIO Deep Learning Algorithm for Brain Tumour Segmentation on Postoperative MRI.

In the context of brain tumour response assessment, deep learning-based three-dimensional (3D) tumour segmentation has shown potential to enter the routine radiological workflow. The purpose of the present study was to perform an external evaluation of a state-of-the-art deep learning 3D brain tumour segmentation algorithm (HD-GLIO) on an independent cohort of consecutive, post-operative patients. For 66 consecutive magnetic resonance imaging examinations, we compared delineations of contrast-enhancing (CE) tumour lesions and non-enhancing T2/FLAIR hyperintense abnormality (NE) lesions by the HD-GLIO algorithm and radiologists using Dice similarity coefficients (Dice). Volume agreement was assessed using concordance correlation coefficients (CCCs) and Bland-Altman plots. The algorithm performed very well regarding the segmentation of NE volumes (median Dice = 0.79) and CE tumour volumes larger than 1.0 cm3 (median Dice = 0.86). If considering all cases with CE tumour lesions, the performance dropped significantly (median Dice = 0.40). Volume agreement was excellent with CCCs of 0.997 (CE tumour volumes) and 0.922 (NE volumes). The findings have implications for the application of the HD-GLIO algorithm in the routine radiological workflow where small contrast-enhancing tumours will constitute a considerable share of the follow-up cases. Our study underlines that independent validations on clinical datasets are key to asserting the robustness of deep learning algorithms.

Multimodality Imaging in Cranial Giant Cell Arteritis: First Experience with High-Resolution T1-Weighted 3D Black Blood without Contrast Enhancement Magnetic Resonance Imaging.

In order to support or refute the clinical suspicion of cranial giant cell arteritis (GCA), a supplemental imaging modality is often required. High-resolution black blood Magnetic Resonance Imaging (BB MRI) techniques with contrast enhancement can visualize artery wall inflammation in GCA. We compared findings on BB MRI without contrast enhancement with findings on 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/low-dose computed tomography (2-[18F]FDG PET/CT) in ten patients suspected of having GCA and in five control subjects who had a 2-[18F]FDG PET/CT performed as a routine control for malignant melanoma. BB MRI was consistent with 2-[18F]FDG PET/CT in 10 out of 10 cases in the group with suspected GCA. In four out of five cases in the control group, the BB MRI was consistent with 2-[18F]FDG PET/CT. In this small population, BB MRI without contrast enhancement shows promising performance in the diagnosis of GCA, and might be an applicable imaging modality in patients.

Surgically Induced Contrast Enhancements on Intraoperative and Early Postoperative MRI Following High-Grade Glioma Surgery: A Systematic Review.

For the radiological assessment of resection of high-grade gliomas, a 72-h diagnostic window is recommended to limit surgically induced contrast enhancements. However, such enhancements may occur earlier than 72 h post-surgery. This systematic review aimed to assess the evidence on the timing of the postsurgical MRI. PubMed, Embase, Web of Science and Cochrane were searched following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only original research articles describing surgically induced contrast enhancements on MRI after resection for high-grade gliomas were included and analysed. The frequency of different contrast enhancement patterns on intraoperative MRI (iMRI) and early postoperative MRI (epMRI) was recorded. The search resulted in 1443 studies after removing duplicates, and a total of 12 studies were chosen for final review. Surgically induced contrast enhancements were reported at all time points after surgery, including on iMRI, but their type and frequency vary. Thin linear contrast enhancements were commonly found to be surgically induced and were less frequently recorded on postoperative days 1 and 2. This suggests that the optimal time to scan may be at or before this time. However, the evidence is limited, and higher-quality studies using larger and consecutively sampled populations are needed.

Impact of adding breast density to breast cancer risk models: A systematic review.

PURPOSE: Assessment of a woman's risk of breast cancer is essential when moving towards personalized screening. Breast density is a well-known risk factor and has the potential to improve accuracy of risk prediction models. In this study we reviewed the impact on model performance of adding breast density to clinical breast cancer risk prediction models. METHODS: We conducted a systematic review using a pre-specified search strategy for PubMed, EMBASE, Web of Science, and Cochrane Library from January 2007 until November 2019. Studies were screened using the Covidence software. Eligible studies developed or modified existing breast cancer risk prediction models applicable to the general population of women by adding breast density to the model. Improvement in discriminatory accuracy was measured as an increase in the Area Under the Curve or concordance statistics. RESULTS: Eleven eligible studies were identified by the search and one by reference check. Four studies modified the Gail model, four modified the Tyrer-Cuzick model, and five studies developed new models. Several methods were used to measure breast density, including visual, semi- and fully automated methods. Eleven studies reported discriminatory accuracy and one study reported calibration. Seven studies found a statistically significantly increased discriminatory accuracy when including density in the model. The increase in AUC ranged 0.03 to 0.14. Four studies did not report on statistical significance, but reported an increased AUC ranging from 0.01 to 0.06. CONCLUSION: Including mammographic breast density has the potential to improve breast cancer risk prediction models. However, all models demonstrated limited discrimination accuracy.

Can Strain Elastography Predict Malignancy of Soft Tissue Tumors in a Tertiary Sarcoma Center?

This study aims to investigate the ability of ultrasound strain elastography as an adjunct to predict malignancy in soft tissue tumors suspect of sarcoma or metastasis in a tertiary reference center for sarcoma. A total of 137 patients were included prospectively. Patients were referred on the basis of clinical or radiological suspicion of malignant soft tissue tumor. All patients had previously undergone diagnostic imaging (MRI, CT or PET-CT). After recording strain elastography cine loops, ultrasound guided biopsy was performed. Three investigators, who were blinded to final diagnosis, reviewed all elastograms retrospectively. For each elastogram, a qualitative, visual 5-point score was decided in consensus and a strain ratio was calculated. Final pathology obtained from biopsy or tumor resection served as gold standard. Eighty-one tumors were benign, and 56 were malignant. t-tests showed a significant difference in mean visual score between benign and malignant tumors. There was no significant difference in mean strain ratio between the two groups. Strain elastography may be a valuable adjunct to conventional B-mode ultrasound, perhaps primarily in primary care, when considering whether to refer to a sarcoma center or to biopsy, although biopsies cannot reliably be ruled out based on the current data.

Strain histograms are equal to strain ratios in predicting malignancy in breast tumours.

OBJECTIVES: To assess whether strain histograms are equal to strain ratios in predicting breast tumour malignancy and to see if either could be used to upgrade Breast Imaging Reporting and Data System (BI-RADS) 3 tumours for immediate biopsy. METHODS: Ninety-nine breast tumours were examined using B-mode BI-RADS scorings and strain elastography. Strain histograms and ratios were assessed, and areas- under-the-receiver-operating-characteristic-curve (AUROC) for each method calculated. In BI-RADS 3 tumours cut-offs for strain histogram and ratio values were calculated to see if some tumours could be upgraded for immediate biopsy. Linear regression was performed to evaluate the effect of tumour depth and size, and breast density on strain elastography. RESULTS: Forty-four of 99 (44.4%) tumours were malignant. AUROC of BI-RADS, strain histograms and strain ratios were 0.949, 0.830 and 0.794 respectively. There was no significant difference between AUROCs of strain histograms and strain ratios (P = 0.405), while they were both inferior to BI-RADS scoring (P<0.001, P = 0.008). Four out of 26 BI-RADS 3 tumours were malignant. When cut-offs of 189 for strain histograms and 1.44 for strain ratios were used to upgrade BI-RADS 3 tumours, AUROCS were 0.961 (Strain histograms and BI-RADS) and 0.941 (Strain ratios and BI-RADS). None of them was significantly different from BI-RADS scoring alone (P = 0.249 and P = 0.414). Tumour size and depth, and breast density influenced neither strain histograms (P = 0.196, P = 0.115 and P = 0.321) nor strain ratios (P = 0.411, P = 0.596 and P = 0.321). CONCLUSION: Strain histogram analyses are reliable and easy to do in breast cancer diagnosis and perform comparably to strain ratio analyses. No significant difference in AUROCs between BI-RADS scoring and elastography combined with BI-RADS scoring was found in this study.

Ultrasound Elastography Is Useful for Evaluation of Liver Fibrosis in Children-A Systematic Review.

OBJECTIVES: Adult studies have proven ultrasound elastography as a validated measure of liver fibrosis. The present study aimed to review the available literature on ultrasound elastography in children to evaluate the ability of the method to distinguish healthy from fibrotic liver tissue and investigate whether cutoff values for liver fibrosis in children have been established. METHODS: A literature search was performed in MEDLINE, EMBASE, the Cochrane Library, and Web of Science to identify studies on ultrasound elastography of the liver in children. Only original research articles in English concerning ultrasound elastography in children with and without liver disease, younger than 18 years, were included. All reference lists of the included articles were hand-searched for further references. RESULTS: Twenty-seven articles were included. Elastography in children without liver disease was investigated in 14 studies and were comparable to those existing for adults. Twelve studies compared elastography with liver biopsy in children with liver disease and found that cirrhosis was correctly diagnosed, whereas it was more difficult to assess severe fibrosis correctly. For the distinction between no, mild, and moderate fibrosis in children with liver disease the method was less accurate. Ultrasound elastography was able to differentiate between children with and without liver fibrosis. In children without liver disease ultrasound, elastography showed consistent liver stiffness values comparable to those found in adults. No fibrosis-specific cutoffs were proposed. CONCLUSIONS: Ultrasound elastography was able to diagnose cirrhosis, distinguish healthy from fibrotic liver tissue, and showed consistent liver stiffness values in children without liver disease.