Multicentre validation of CT grey-level co-occurrence matrix features for overall survival in primary oesophageal adenocarcinoma.

BACKGROUND: Personalising management of primary oesophageal adenocarcinoma requires better risk stratification. Lack of independent validation of proposed imaging biomarkers has hampered clinical translation. We aimed to prospectively validate previously identified prognostic grey-level co-occurrence matrix (GLCM) CT features for 3-year overall survival. METHODS: Following ethical approval, clinical and contrast-enhanced CT data were acquired from participants from five institutions. Data from three institutions were used for training and two for testing. Survival classifiers were modelled on prespecified variables ('Clinical' model: age, clinical T-stage, clinical N-stage; 'ClinVol' model: clinical features + CT tumour volume; 'ClinRad' model: ClinVol features + GLCM_Correlation and GLCM_Contrast). To reflect current clinical practice, baseline stage was also modelled as a univariate predictor ('Stage'). Discrimination was assessed by area under the receiver operating curve (AUC) analysis; calibration by Brier scores; and clinical relevance by thresholding risk scores to achieve 90% sensitivity for 3-year mortality. RESULTS: A total of 162 participants were included (144 male; median 67 years [IQR 59, 72]; training, 95 participants; testing, 67 participants). Median survival was 998 days [IQR 486, 1594]. The ClinRad model yielded the greatest test discrimination (AUC, 0.68 [95% CI 0.54, 0.81]) that outperformed Stage (ΔAUC, 0.12 [95% CI 0.01, 0.23]; p = .04). The Clinical and ClinVol models yielded comparable test discrimination (AUC, 0.66 [95% CI 0.51, 0.80] vs. 0.65 [95% CI 0.50, 0.79]; p > .05). Test sensitivity of 90% was achieved by ClinRad and Stage models only. CONCLUSIONS: Compared to Stage, multivariable models of prespecified clinical and radiomic variables yielded improved prediction of 3-year overall survival. CLINICAL RELEVANCE STATEMENT: Previously identified radiomic features are prognostic but may not substantially improve risk stratification on their own. KEY POINTS: • Better risk stratification is needed in primary oesophageal cancer to personalise management. • Previously identified CT features-GLCM_Correlation and GLCM_Contrast-contain incremental prognostic information to age and clinical stage. • Compared to staging, multivariable clinicoradiomic models improve discrimination of 3-year overall survival.

The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights.

Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics. However, their lack of standardization restricts reproducibility and clinical translation of radiomics decision support tools. In this special report, teams of researchers who developed radiomics software participated in a three-phase study (September 2020 to December 2022) to establish a standardized set of filters. The first two phases focused on finding reference filtered images and reference feature values for commonly used convolutional filters: mean, Laplacian of Gaussian, Laws and Gabor kernels, separable and nonseparable wavelets (including decomposed forms), and Riesz transformations. In the first phase, 15 teams used digital phantoms to establish 33 reference filtered images of 36 filter configurations. In phase 2, 11 teams used a chest CT image to derive reference values for 323 of 396 features computed from filtered images using 22 filter and image processing configurations. Reference filtered images and feature values for Riesz transformations were not established. Reproducibility of standardized convolutional filters was validated on a public data set of multimodal imaging (CT, fluorodeoxyglucose PET, and T1-weighted MRI) in 51 patients with soft-tissue sarcoma. At validation, reproducibility of 486 features computed from filtered images using nine configurations × three imaging modalities was assessed using the lower bounds of 95% CIs of intraclass correlation coefficients. Out of 486 features, 458 were found to be reproducible across nine teams with lower bounds of 95% CIs of intraclass correlation coefficients greater than 0.75. In conclusion, eight filter types were standardized with reference filtered images and reference feature values for verifying and calibrating radiomics software packages. A web-based tool is available for compliance checking.

Bone turnover change after randomized switch from tenofovir disoproxil to tenofovir alafenamide fumarate in men with HIV.

OBJECTIVE: Bone loss in people with HIV (PWH) is poorly understood. Switching tenofovir disoproxil fumarate (TDF) to tenofovir alafenamide (TAF) has yielded bone mineral density (BMD) increases. PETRAM (NCT#:03405012) investigated whether BMD and bone turnover changes correlate. DESIGN: Open-label, randomized controlled trial. SETTING: Single-site, outpatient, secondary care. PARTICIPANTS: Nonosteoporotic, virologically suppressed, cis-male PWH taking TDF/emtricitabine (FTC)/rilpivirine (RPV) for more than 24 weeks. INTERVENTION: Continuing TDF/FTC/RPV versus switching to TAF/FTC/RPV (1 : 1 randomization). MAIN OUTCOME MEASURES: :[ 18 F]NaF-PET/CT for bone turnover (standardized uptake values, SUV mean ) and dual-energy x-ray absorptiometry for lumbar spine and total hip BMD. RESULTS: Thirty-two men, median age 51 years, 76% white, median duration TDF/FTC/RPV 49 months, were randomized between 31 August 2018 and 09 March 2020. Sixteen TAF:11 TDF were analyzed. Baseline-final scan range was 23-103 (median 55) weeks. LS-SUV mean decreased for both groups (TAF -7.9% [95% confidence interval -14.4, -1.5], TDF -5.3% [-12.1,1.5], P  = 0.57). TH-SUV mean showed minimal changes (TAF +0.3% [-12.2,12.8], TDF +2.9% [-11.1,16.9], P  = 0.77). LS-BMD changes were slightly more favorable with TAF but failed to reach significance (TAF +1.7% [0.3,3.1], TDF -0.3 [-1.8,1.2], P  = 0.06). Bone turnover markers decreased more with TAF ([CTX -35.3% [-45.7, -24.9], P1NP -17.6% [-26.2, -8.5]) than TDF (-11.6% [-28.8, +5.6] and -6.9% [-19.2, +5.4] respectively); statistical significance was only observed for CTX ( P  = 0.02, P1NP, P  = 0.17). CONCLUSION: Contrary to our hypothesis, lumbar spine and total hip regional bone formation (SUV mean ) and BMD did not differ postswitch to TAF. However, improved LS-BMD and CTX echo other TAF-switch studies. The lack of difference in SUV mean may be due to inadequate power.

Publisher Correction: Cdh2 coordinates Myosin-II dependent internalisation of the zebrafish neural plate.

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Cdh2 coordinates Myosin-II dependent internalisation of the zebrafish neural plate.

Tissue internalisation is a key morphogenetic mechanism by which embryonic tissues generate complex internal organs and a number of studies of epithelia have outlined a general view of tissue internalisation. Here we have used quantitative live imaging and mutant analysis to determine whether similar mechanisms are responsible for internalisation in a tissue that apparently does not have a typical epithelial organisation - the zebrafish neural plate. We found that although zebrafish embryos begin neurulation without a conventional epithelium, medially located neural plate cells adopt strategies typical of epithelia in order to constrict their dorsal surface membrane during cell internalisation. Furthermore, we show that Myosin-II activity is a significant driver of this transient cell remodeling which also depends on Cdh2 (N-cadherin). Abrogation of Cdh2 results in defective Myosin-II distribution, mislocalised internalisation events and defective neural plate morphogenesis. Our work suggests Cdh2 coordinates Myosin-II dependent internalisation of the zebrafish neural plate.