The aim of this work was to evaluate the inter- and intra-observer variation in contouring vestibular schwannoma (VS) and the organs-at-risk (OAR), and its dosimetric impact in Volumetric Modulated Arc Therapy (VMAT). Three VS typical cases were contoured by four clinicians. The Agreement Volume Index (AVI) appeared to be notably higher in VS than in OARs, such that the dose coverage of VS is fairly robust. In OARs, the largest variation was +1.02Gy in dmax for the brainstem, +0.78Gy in dmean for the cochlea and +1.05Gy in dmax of the trigeminal nerve. Accordingly, it was decided that all VS delineations for stereotactic radiosurgery (SRS), and all frame-based SRS contouring in general, should always be reviewed by a second physician. In addition, the retrospective presentation of VS cases at daily peer review meetings has also been adopted to ensure that the consensus is constantly updated, as well as for training purposes.

During the early stages of the pandemic, computed tomography (CT) of the chest, along with serological and clinical data, was frequently utilized in diagnosing COVID-19, particularly in regions facing challenges such as shortages of PCR kits. In these circumstances, CT scans played a crucial role in diagnosing COVID-19 and guiding patient management. The COVID-19 Reporting and Data System (CO-RADS) was established as a standardized reporting system for cases of COVID-19 pneumonia. Its implementation necessitates a high level of agreement among observers to prevent any potential confusion. This study aimed to assess the inter-observer agreement between physicians from different specialties with variable levels of experience in their CO-RADS scoring of CT chests for confirmed COVID-19 patients, and to assess the feasibility of applying this reporting system to those having little experience with it. All chest CT images of patients with positive RT-PCR tests for COVID-19 were retrospectively reviewed by seven observers. The observers were divided into three groups according to their type of specialty (three radiologists, three house officers, and one pulmonologist). The observers assessed each image and categorized the patients into five CO-RADS groups. A total of 630 participants were included in this study. The inter-observer agreement was almost perfect among the radiologists, substantial among a pulmonologist and the house officers, and moderate-to-substantial among the radiologists, the pulmonologist, and the house officers. There was substantial to almost perfect inter-observer agreement when reporting using the CO-RADS among observers with different experience levels. Although the inter-observer variability among the radiologists was high, it decreased compared to the pulmonologist and house officers. Radiologists, house officers, and pulmonologists applying the CO-RADS can accurately and promptly identify typical CT imaging features of lung involvement in COVID-19.

The O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET in Glioblastoma (FIG) trial is an Australian prospective, multi-centre study evaluating FET PET for glioblastoma patient management. FET PET imaging timepoints are pre-chemoradiotherapy (FET1), 1-month post-chemoradiotherapy (FET2), and at suspected progression (FET3). Before participant recruitment, site nuclear medicine physicians (NMPs) underwent credentialing of FET PET delineation and image interpretation.
Sites were required to complete contouring and dynamic analysis by ≥ 2 NMPs on benchmarking cases (n = 6) assessing biological tumour volume (BTV) delineation (3 × FET1) and image interpretation (3 × FET3). Data was reviewed by experts and violations noted. BTV definition includes tumour-to-background ratio (TBR) threshold of 1.6 with crescent-shaped background contour in the contralateral normal brain. Recurrence/pseudoprogression interpretation (FET3) required assessment of maximum TBR (TBRmax), dynamic analysis (time activity curve [TAC] type, time to peak), and qualitative assessment. Intraclass correlation coefficient (ICC) assessed volume agreement, coefficient of variation (CoV) compared maximum/mean TBR (TBRmax/TBRmean) across cases, and pairwise analysis assessed spatial (Dice similarity coefficient [DSC]) and boundary agreement (Hausdorff distance [HD], mean absolute surface distance [MASD]).
Data was accrued from 21 NMPs (10 centres, n ≥ 2 each) and 20 underwent review. The initial pass rate was 93/119 (78.2%) and 27/30 requested resubmissions were completed. Violations were found in 25/72 (34.7%; 13/12 minor/major) of FET1 and 22/74 (29.7%; 14/8 minor/major) of FET3 reports. The primary reasons for resubmission were as follows: BTV over-contour (15/30, 50.0%), background placement (8/30, 26.7%), TAC classification (9/30, 30.0%), and image interpretation (7/30, 23.3%). CoV median and range for BTV, TBRmax, and TBRmean were 21.53% (12.00-30.10%), 5.89% (5.01-6.68%), and 5.01% (3.37-6.34%), respectively. BTV agreement was moderate to excellent (ICC = 0.82; 95% CI, 0.63-0.97) with good spatial (DSC = 0.84 ± 0.09) and boundary (HD = 15.78 ± 8.30 mm; MASD = 1.47 ± 1.36 mm) agreement.
The FIG study credentialing program has increased expertise across study sites. TBRmax and TBRmean were robust, with considerable variability in BTV delineation and image interpretation observed.

BACKGROUND: To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) assessment through conventional microscopy by comparing observers\' estimations.
METHODS: Intratumoral and tumor-front stromal TILs, and TSR, were assessed by three pathologists using 86 CRC HE slides. TSR and TILs were categorized using one and four different proposed cutoff systems, respectively, and agreement was assessed using the intraclass coefficient (ICC) and Cohen\'s kappa statistics. Pairwise evaluation of agreement was performed using the Fleiss kappa statistic and the concordance rate and it was visualized by Bland-Altman plots. To investigate the association between biomarkers and patient data, Pearson\'s correlation analysis was applied.
RESULTS: For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI: 0.35-0.64) was obtained, kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI: 0.32-0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI: 0.35-0.60), the kappa value was 0.49 and the concordance rate was 0.76. We observed a significant correlation between tumor grade and the median of TSR (0.29 (95% CI: 0.032-0.51), p-value = 0.03).
CONCLUSIONS: The agreement between pathologists in estimating these markers corresponds to poor-to-moderate agreement; implementing immune scores in daily practice requires more concentration in inter-observer agreements.

Radiomics image analysis has the potential to uncover disease characteristics for the development of predictive signatures and personalised radiotherapy treatment. Inter-observer and inter-software delineation variabilities are known to have downstream effects on radiomics features, reducing the reliability of the analysis. The purpose of this study was to investigate the impact of these variabilities on radiomics outputs from preclinical cone-beam computed tomography (CBCT) scans. Inter-observer variabilities were assessed using manual and semi-automated contours of mouse lungs (n = 16). Inter-software variabilities were determined between two tools (3D Slicer and ITK-SNAP). The contours were compared using Dice similarity coefficient (DSC) scores and the 95th percentile of the Hausdorff distance (HD95p) metrics. The good reliability of the radiomics outputs was defined using intraclass correlation coefficients (ICC) and their 95% confidence intervals. The median DSC scores were high (0.82-0.94), and the HD95p metrics were within the submillimetre range for all comparisons. the shape and NGTDM features were impacted the most. Manual contours had the most reliable features (73%), followed by semi-automated (66%) and inter-software (51%) variabilities. From a total of 842 features, 314 robust features overlapped across all contouring methodologies. In addition, our results have a 70% overlap with features identified from clinical inter-observer studies.

BACKGROUND: Salivary gland tumors (SGT) are a diverse group of neoplasms arising from the major and minor glands. The oral cavity is the most common site for minor SGT (IMSGT), and these lesions frequently pose a challenge to the pathologist due to overlapping histopathological features and limited material for analysis. Our objective was to determine specific clinical and histopathological features associated with challenges in IMSGT diagnoses and pathologists\' agreement.
METHODS: We conducted a retrospective analysis of 248 IMSGT received between 2010 and 2019. We evaluated the diagnostic challenge of the cases by stratifying according to whether a definitive, favored, or indeterminate (challenging) diagnosis was provided. Inter-observer agreement and concordance of biopsy diagnoses with the final diagnoses after tumor resection were evaluated.
RESULTS: Of the 248 biopsies, 191 had a definitive diagnosis, 38 favored diagnoses, and 19 were indeterminate. The predominant diagnoses considered for the indeterminate category were pleomorphic adenoma/myoepithelioma (PA), polymorphous adenocarcinoma (PAC), adenoid cystic carcinoma (AdCC), and low-grade adenocarcinoma. Using multivariate analysis of clinical features, younger patient age, smaller tumor size, and larger biopsy size increased the likelihood of a definitive diagnosis (p = 0.014, p = 0.037, p = 0.012). The inter-observer agreement for 68 representative cases was moderate overall (Fleiss\'s Kappa 0.575) and good for the 40 cases with a definitive diagnosis (Fleiss\'s Kappa 0.66). Sixty-five biopsy diagnoses were matched with corresponding tumor resection diagnoses and found to show a good concordance (Cramer\'s V test 0.76). The discordant diagnoses predominantly involved PA, carcinoma exPA, PAC, AdCC, and adenocarcinoma NOS.
CONCLUSIONS: Diagnostic challenges in IMSGT incisional biopsies were infrequent, especially if multiple pathologists were consulted. PA, PAC, AdCC, and adenocarcinoma NOS were the histologic types more commonly posing diagnostic challenges. Younger patient age, smaller tumor size, and larger biopsy are associated with a definitive diagnosis. This data highlights the importance of appropriate sampling in IMSGT.

OBJECTIVE: Inter-modality image registration between computed tomography (CT) and magnetic resonance (MR) images is associated with systematic uncertainties and the magnitude of these uncertainties is not well documented. The purpose of this study was to investigate the potential uncertainty of gold fiducial marker (GFM) registration for localized prostate cancer and to estimate the inter-observer bias in a clinical setting.
METHODS: Four experienced observers registered CT and MR images for 42 prostate cancer patients. Manual GFM identification was followed by a landmark-based registration. The absolute difference between observers in GFM identification and the displacement of the clinical target volume (CTV) was investigated. The CTV center of mass (CoM) vector displacements, DICE-index and Hausdorff distances for the observer registrations were compared against a clinical baseline registration. The time allocated for the manual registrations was compared.
RESULTS: Absolute difference in GFM identification between observers ranged from 0.0 to 3.0 mm. The maximum CTV CoM displacement from the clinical baseline was 3.1 mm. Displacements larger than or equal to 1 mm, 2 mm and 3 mm were 46%, 18% and 4%, respectively. No statistically significant difference was detected between observers in terms of CTV displacement. Median DICE-index and Hausdorff distance for the CTV, with their respective ranges were 0.94 [0.70-1.00] and 2.5 mm [0.7-8.7].
CONCLUSIONS: Registration of CT and MR images using GFMs for localized prostate cancer patients was subject to inter-observer bias on an individual patient level. A CTV displacement as large as 3 mm occurred for individual patients. These results show that GFM registration in a clinical setting is associated with uncertainties, which motivates the removal of inter-modality registrations in the radiotherapy workflow and a transition to an MRI-only workflow for localized prostate cancer.

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Oral lichen planus (OLP) and oral lichenoid lesions (OLL) can both present with histological dysplasia. Despite the presence of WHO-defined criteria for the evaluation of epithelial dysplasia, its assessment is frequently subjective (inter-observer variability). The lack of reproducibility in the evaluation of dysplasia is even more complex in the presence of a lichenoid inflammation. We evaluated dysplasia in 112 oral biopsies with lichenoid inflammation in order to study the inter-observer and the intra-observer variability.

BACKGROUND: Computed tomography (CT) gives an idea about the prognosis in patients with COVID-19 lung infiltration.
OBJECTIVE: To evaluate the success rates of various scoring methods utilized in order to predict survival periods, on the basis of the imaging findings of COVID-19. Another purpose, on the other hand, was to evaluate the agreements among the evaluating radiologists.
METHODS: A total of 100 cases of known COVID-19 pneumonia, of which 50 were deceased and 50 were living, were included in the study. Pre-existing scoring systems, which were the Total Severity Score (TSS), Chest Computed Tomography Severity Score (CT-SS), and Total CT Score, were utilized, together with the Early Decision Severity Score (ED-SS), which was developed by our team, to evaluate the initial lung CT scans of the patients obtained at their initial admission to the hospital. The scans were evaluated retrospectively by two radiologists. Area under the curve (AUC) values were acquired for each scoring system, according to their performances in predicting survival times.
RESULTS: The mean age of the patients was 61 ± 14.85 years (age range = 18-87 years). There was no difference in co-morbidities between the living and deceased patients. The survival predicted AUC values of ED-SS, CT-SS, TSS, and Total CT Score systems were 0.876, 0.823, 0.753, and 0.744, respectively.
CONCLUSIONS: Algorithms based on lung infiltration patterns of COVID-19 may be utilized for both survival prediction and therapy planning.