Diagnostic challenges in the assessment of thyroid neoplasms using nuclear features and vascular and capsular invasion: a multi-center interobserver agreement study.

Background: The diagnosis of thyroid neoplasms necessitates the identification of distinct histological features. Various education/hospital centers located in cities across Indonesia likely result in discordances among pathologists when diagnosing thyroid neoplasms. Methods: This study examined the concordance among Indonesian pathologists in assessing nuclear features and capsular and vascular invasion of thyroid tumors. Fifteen pathologists from different centers independently assessed the same 14 digital slides of thyroid tumor specimens. All the specimens were thyroid neoplasms with known BRAFV600E and RAS mutational status, from a single center. We evaluated the pre- and post-training agreement using the Fleiss kappa. The significance of the training was evaluated using a paired T-test. Results: Baseline agreement on nuclear features was slight to fair based on a 3-point scoring system (k = 0.14 to 0.28) and poor to fair based on an eight-point system (k = -0.02 to 0.24). Agreements on vascular (κ = 0.35) and capsular invasion (κ = 0.27) were fair, whereas the estimated molecular type showed substantial agreement (κ = 0.74). Following the training, agreement using the eight-point system significantly improved (p = 0.001). Conclusions: The level of concordance among Indonesian pathologists in diagnosing thyroid neoplasm was relatively poor. Consensus in pathology assessment requires ongoing collaboration and education to refine diagnostic criteria.

Inter-observer consistency on subsolid nodule follow-up recommendation based on National Comprehensive Cancer Network (NCCN) guidelines in low-dose computed tomography (LDCT) lung cancer screening.

Background: Follow-up management of pulmonary nodules is a crucial component of lung cancer screening. Consistency in follow-up recommendations is essential for effective lung cancer screening. This study aimed to assess inter-observer agreement on National Comprehensive Cancer Network (NCCN) guideline-based follow-up recommendation for subsolid nodules from low-dose computed tomography (LDCT) screening. Methods: A retrospective collection of LDCT reports from 2014 to 2017 for lung cancer screening was conducted using the Radiology Information System and keyword searches, focusing on subsolid nodules. A total of 110 LDCT cases containing subsolid nodules were identified. Two senior radiologists provided standardized follow-up recommendation. Follow-up recommendation was categorized into four groups (0-, 3-, 6-, and 12-month). To ensure overall balance and representativeness of the follow-up categories, 60 scans from 60 participants were included (distribution ratio 1:1:2:2). Cases were categorised into follow-up recommendation groups by five observers following NCCN guidelines. Fleiss' kappa statistic was used to evaluate inter-observer agreement. Results: Overall accuracy rate for follow-up recommendation among five observers was 72.3%. Chest radiologists' overall agreement was significantly higher than radiology residents (P<0.01). The overall agreement among the five observers was moderate, with a Fleiss' kappa of 0.437. For all paired readers, the mean Cohen's kappa value was 0.603, with 95% confidence interval (CI) from 0.489 to 0.716. Chest radiologists demonstrated substantial agreement, evidenced by a Cohen's kappa of 0.655 (95% CI: 0.503-0.807). In contrast, the mean Cohen's kappa among radiology residents was 0.533 (95% CI: 0.501-0.565). The majority of cases with discrepancies, accounting for 73.5%, were associated with the same risk-dominant nodules. A higher proportion of part-solid nodule was a risk factor for discrepancies. Of the 600 paired readings, major discrepancies and substantial discrepancies were observed in 27.5% and 4.8% (29/600) of the cases. Conclusions: In subsolid nodules, category evaluation of observer follow-up recommendation based on NCCN guidelines achieved moderate consistency. Disagreements were mainly caused by measurement and type disagreements of identical risk-dominant nodules. Part-solid nodule was a contributor for discrepancies in follow-up recommendation. Major and substantial management discrepancies were 27.5% and 4.8% in the paired evaluations.

[Translated article] Diagnostic imaging in patients with vertebral compression fractures.

Vertebral compression fractures by osteoporosis (OVF) is usually a diagnostic problem and coincides on the age group of metastatic vertebral compression fractures (MVF). Although radiography is the first diagnostic technique, generally is not accurate for depicting demineralization and soft tissue lesions. Magnetic resonance (MRI) is the diagnostic choice. The most relevant signs are intravertebral fluid collection or fluid signal, other vertebral deformities without oedema and older age. Among the most relevant findings for diagnosis MVF are soft tissue mass and pedicle intensity signal asymmetries. However, reproducibility of these findings in clinical practice is moderate.

Actinic keratosis metrics.

Actinic keratosis (AK) is a common precancerous skin condition predominantly affecting older males with fair skin and significant UV exposure. The clinical significance of AK is related to its potential for malignant transformation and progression to squamous cell carcinoma (SCC). Accurate diagnosis of AK is essential for adequate treatment, evaluation of therapeutic efficacy, and mitigating the risk of developing SCC. However, clinician variability due to the subjective nature of current diagnostic tools presents significant challenges to achieving consistent and reliable AK diagnoses. Thus, there is no universally accepted standard for measuring AK.This review evaluates current methods for evaluating and diagnosing AK, focusing on clinician variability through inter- and intraobserver agreement. Eight peer-reviewed studies investigating the reliability of various approaches for AK evaluation show substantial variability in interobserver or intraobserver agreement, with most methods demonstrating only slight to moderate reliability. Some suggest that consensus discussions and simplified rating scales can modestly improve diagnostic reliability. However, remaining variability and the lack of a universally accepted standard for measuring AK underscore the need for more robust and standardized diagnostic and evaluation methods.The review emphasizes the need for improved diagnostic tools and standardized methods to enhance the accuracy and reliability of AK assessments. It also proposes applying a novel examination approach using 1,3-dihydroxyacetone (DHA) staining which may improve the visualization and identification of AK lesions. Advancements in these areas have significant potential, promising better clinical practices and patient outcomes in AK management.

Inter-observer reproducibility of the 2021 AAGL Endometriosis Classification.

BACKGROUND: Inter-observer agreement for the American Association of Gynecologic Laparoscopists (AAGL) 2021 Endometriosis Classification staging system has not been described. Its predecessor staging system, the revised American Society for Reproductive Medicine (rASRM), has historically demonstrated poor inter-observer agreement. AIMS: We aimed to determine the inter-observer agreement performance of the AAGL 2021 Endometriosis Classification staging system, and compare this with the rASRM staging system. MATERIALS AND METHODS: A database of 317 patients with coded surgical data was retrospectively analysed. Three independent observers allocated AAGL surgical stages (1-4), twice. Observers made their own interpretation of how to apply the tool in the first staging allocation. Consensus rules were then developed for a second staging allocation. RESULTS: First staging allocation: odds ratio (OR) (and 95% CI) for observer 1 to score higher than observer 2 was 8.08 (5.12-12.76). Observer 1 to score higher than observer 3 was 12.98 (7.99-21.11) and observer 2 to score higher than observer 3 was 1.61 (1.03-2.51). This represents poor agreement. Second staging allocation (after consensus): OR for observer 1 to score higher than observer 2 was 1.14 (0.64-2.03), observer 1 to score higher than observer 3 was 1.81 (0.99-3.28) and observer 2 to score higher than observer 3 was 1.59 (0.87-2.89). This represents good agreement. CONCLUSIONS: These findings suggest that in its current format the AAGL 2021 Endometriosis Classification staging system has poor inter-observer agreement, not superior to the rASRM staging system. However, performance improved when additional measures were taken to simplify and clarify areas of ambiguity in interpreting the staging system.

Diagnostic imaging in patients with vertebral compression fractures. / Diagnóstico radiográfico de pacientes con fracturas por compresión vertebral.

Vertebral compression fractures by osteoporosis (OVF) is usually a diagnostic problem and coincides on the age group of metastatic vertebral compression fractures (MVF). Although radiography is the first diagnostic technique, generally is not accurate for depicting demineralization and soft tissue lesions. Magnetic resonance (MRI) is the diagnostic choice. The most relevant signs are Intravertebral fluid collection or fluid signal, other vertebral deformities without edema and older age. Among the most relevant findings for diagnosis MVF are soft tissue mass and pedicle intensity signal asymmetries. However, reproducibility of these findings in clinical practice is moderate.

Inter-observer effects in needle reconstruction for temporary prostate brachytherapy: Dosimetric implications and adaptive CBCT-TRUS registration solutions.

PURPOSE: To investigate geometric and dosimetric inter-observer variability in needle reconstruction for temporary prostate brachytherapy. To assess the potential of registrations between transrectal ultrasound (TRUS) and cone-beam computed tomography (CBCT) to support implant reconstructions. METHODS AND MATERIALS: The needles implanted in 28 patients were reconstructed on TRUS by three physicists. Corresponding geometric deviations and associated dosimetric variations to prostate and organs at risk (urethra, bladder, rectum) were analyzed. To account for the found inter-observer variability, various approaches (template-based, probe-based, marker-based) for registrations of CBCT to TRUS were investigated regarding the respective needle transfer accuracy in a phantom study. Three patient cases were examined to assess registration accuracy in-vivo. RESULTS: Geometric inter-observer deviations >1 mm and >3 mm were found for 34.9% and 3.5% of all needles, respectively. Prostate dose coverage (changes up to 7.2%) and urethra dose (partly exceeding given dose constraints) were most affected by associated dosimetric changes. Marker-based and probe-based registrations resulted in the phantom study in high mean needle transfer accuracies of 0.73 mm and 0.12 mm, respectively. In the patient cases, the marker-based approach was the superior technique for CBCT-TRUS fusions. CONCLUSION: Inter-observer variability in needle reconstruction can substantially affect dosimetry for individual patients. Especially marker-based CBCT-TRUS registrations can help to ensure accurate reconstructions for improved treatment planning.

Reproducibility of a semiautomatic lobar lung tissue assignment technique on noncontrast CT scans: a study on swine animal model.

BACKGROUND: To evaluate the reproducibility of a vessel-specific minimum cost path (MCP) technique used for lobar segmentation on noncontrast computed tomography (CT). METHODS: Sixteen Yorkshire swine (49.9 ± 4.7 kg, mean ± standard deviation) underwent a total of 46 noncontrast helical CT scans from November 2020 to May 2022 using a 320-slice scanner. A semiautomatic algorithm was employed by three readers to segment the lung tissue and pulmonary arterial tree. The centerline of the arterial tree was extracted and partitioned into six subtrees for lobar assignment. The MCP technique was implemented to assign lobar territories by assigning lung tissue voxels to the nearest arterial tree segment. MCP-derived lobar mass and volume were then compared between two acquisitions, using linear regression, root mean square error (RMSE), and paired sample t-tests. An interobserver and intraobserver analysis of the lobar measurements was also performed. RESULTS: The average whole lung mass and volume was 663.7 ± 103.7 g and 1,444.22 ± 309.1 mL, respectively. The lobar mass measurements from the initial (MLobe1) and subsequent (MLobe2) acquisitions were correlated by MLobe1 = 0.99 MLobe2 + 1.76 (r = 0.99, p = 0.120, RMSE = 7.99 g). The lobar volume measurements from the initial (VLobe1) and subsequent (VLobe2) acquisitions were correlated by VLobe1 = 0.98VLobe2 + 2.66 (r = 0.99, p = 0.160, RSME = 15.26 mL). CONCLUSIONS: The lobar mass and volume measurements showed excellent reproducibility through a vessel-specific assignment technique. This technique may serve for automated lung lobar segmentation, facilitating clinical regional pulmonary analysis. RELEVANCE STATEMENT: Assessment of lobar mass or volume in the lung lobes using noncontrast CT may allow for efficient region-specific treatment strategies for diseases such as pulmonary embolism and chronic thromboembolic pulmonary hypertension. KEY POINTS: • Lobar segmentation is essential for precise disease assessment and treatment planning. • Current methods for segmentation using fissure lines are problematic. • The minimum-cost-path technique here is proposed and a swine model showed excellent reproducibility for lobar mass measurements. • Interobserver agreement was excellent, with intraclass correlation coefficients greater than 0.90.

Identification of tumour regression in neoadjuvantly treated pancreatic cancer is based on divergent and nonspecific criteria.

AIMS: Following the increased use of neoadjuvant therapy for pancreatic cancer, grading of tumour regression (TR) has become part of routine diagnostics. However, it suffers from marked interobserver variation, which is mainly ascribed to the subjectivity of the defining criteria of the categories in TR grading systems. We hypothesized that a further cause for the interobserver variation is the use of divergent and nonspecific morphological criteria to identify tumour regression. METHODS AND RESULTS: Twenty treatment-naïve pancreatic cancers and 20 pancreatic cancers treated with neoadjuvant chemotherapy were reviewed by three experienced pancreatic pathologists who, blinded for treatment status, categorized each tumour as treatment-naïve or neoadjuvantly treated, and annotated all tissue areas they considered showing tumour regression. Only 50%-65% of the cases were categorized correctly, and the annotated tissue areas were highly discrepant (only 3%-41% overlap). When the prevalence of various morphological features deemed to indicate TR was compared between treatment-naïve and neoadjuvantly treated tumours, only one pattern, characterized by reduced cancer cell density and prominent stroma affecting a large area of the tumour bed, occurred significantly more frequently, but not exclusively, in the neoadjuvantly treated group. Finally, stromal features, both morphological and biological, were investigated as possible markers for tumour regression, but failed to distinguish TR from native tumour stroma. CONCLUSION: There is considerable divergence in opinion between pathologists when it comes to the identification of tumour regression. Reliable identification of TR is only possible if it is extensive, while lesser degrees of treatment effect cannot be recognized with certainty.

Reliability, costs, and radiation dose of dual-energy X-ray absorptiometry in diagnosis of radiologic sarcopenia in surgically menopausal women.

OBJECTIVE: The aim of this study was to evaluate and compare reliability, costs, and radiation dose of dual-energy X-ray absorptiometry (DXA) to MRI and CT in measuring muscle mass for the diagnosis of sarcopenia. METHODS: Thirty-four consecutive DXA scans performed in surgically menopausal women from November 2019 until March 2020 were analyzed by two observers. Observers analyzed muscle mass of the lower limbs in every scan twice. Reliability was assessed by calculating inter- and intra-observer variability. Reliability from CT and MRI as well as radiation dose from CT and DXA were collected from literature. Costs for each type of scan were calculated according to the guidelines for economic evaluation of the Dutch National Health Care Institute. RESULTS: The 34 participants had a median age of 58 years (IQR 53-65) and a median body mass index of 24.6 (IQR 21.7-29.7). Inter-observer variability had an intraclass correlation coefficient (ICC) of 0.997 (95% CI 0.994-0.998) with a relative variability of 0.037 ± 0.022%. Regarding intra-observer variability, observer 1 had an ICC of 0.998 (95% CI 0.996-0.999) with a relative variability of 0.019 ± 0.016% and observer 2 had an ICC of 0.997 (95% CI 0.993-0.998) with a relative variability of 0.016 ± 0.011%. DXA costs were €62, CT €77, and MRI €195. The estimated radiation dose of CT was 2.5-3.0 mSv, for DXA this was 2-4 µSv. CONCLUSIONS: DXA has lower costs and a lower radiation dose, with low inter- and intra-observer variability, compared to CT and MRI for assessing lower limb muscle mass. TRIAL REGISTRATION: Netherlands Trial Register; NL8068. CRITICAL RELEVANCE STATEMENT: DXA is a good alternative for CT and MRI in assessing lower limb muscle mass, with lower costs and lower radiation dose, while inter-observer and intra-observer variability are low. KEY POINTS: • Screening for sarcopenia should be optimized as the population ages. • DXA outperformed CT and MRI in the measured metrics. • DXA validity should be further evaluated as an alternative to CT and MRI for sarcopenia evaluation.

Paris classification of colonic polyps using CT colonography: prospective cohort study of interobserver variation.

BACKGROUND: The Paris classification categorises colorectal polyp morphology. Interobserver agreement for Paris classification has been assessed at optical colonoscopy (OC) but not CT colonography (CTC). We aimed to determine the following: (1) interobserver agreement for the Paris classification using CTC between radiologists; (2) if radiologist experience influenced classification, gross polyp morphology, or polyp size; and (3) the extent to which radiologist classifications agreed with (a) colonoscopy and (b) a combined reference standard. METHODS: Following ethical approval for this non-randomised prospective cohort study, seven radiologists from three hospitals classified 52 colonic polyps using the Paris system. We calculated interobserver agreement using Fleiss kappa and mean pairwise agreement (MPA). Absolute agreement was calculated between radiologists; between CTC and OC; and between CTC and a combined reference standard using all available imaging, colonoscopic, and histopathological data. RESULTS: Overall interobserver agreement between the seven readers was fair (Fleiss kappa 0.33; 95% CI 0.30-0.37; MPA 49.7%). Readers with < 1500 CTC experience had higher interobserver agreement (0.42 (95% CI 0.35-0.48) vs. 0.33 (95% CI 0.25-0.42)) and MPA (69.2% vs 50.6%) than readers with ≥ 1500 experience. There was substantial overall agreement for flat vs protuberant polyps (0.62 (95% CI 0.56-0.68)) with a MPA of 87.9%. Agreement between CTC and OC classifications was only 44%, and CTC agreement with the combined reference standard was 56%. CONCLUSION: Radiologist agreement when using the Paris classification at CT colonography is low, and radiologist classification agrees poorly with colonoscopy. Using the full Paris classification in routine CTC reporting is of questionable value. CLINICAL RELEVANCE STATEMENT: Interobserver agreement for radiologists using the Paris classification to categorise colorectal polyp morphology is only fair; routine use of the full Paris classification at CT colonography is questionable. KEY POINTS: • Overall interobserver agreement for the Paris classification at CT colonography (CTC) was only fair, and lower than for colonoscopy. • Agreement was higher for radiologists with < 1500 CTC experience and for larger polyps. There was substantial agreement when classifying polyps as protuberant vs flat. • Agreement between CTC and colonoscopic polyp classification was low (44%).

Assessment of bias in scoring of AI-based radiotherapy segmentation and planning studies using modified TRIPOD and PROBAST guidelines as an example.

BACKGROUND AND PURPOSE: Studies investigating the application of Artificial Intelligence (AI) in the field of radiotherapy exhibit substantial variations in terms of quality. The goal of this study was to assess the amount of transparency and bias in scoring articles with a specific focus on AI based segmentation and treatment planning, using modified PROBAST and TRIPOD checklists, in order to provide recommendations for future guideline developers and reviewers. MATERIALS AND METHODS: The TRIPOD and PROBAST checklist items were discussed and modified using a Delphi process. After consensus was reached, 2 groups of 3 co-authors scored 2 articles to evaluate usability and further optimize the adapted checklists. Finally, 10 articles were scored by all co-authors. Fleiss' kappa was calculated to assess the reliability of agreement between observers. RESULTS: Three of the 37 TRIPOD items and 5 of the 32 PROBAST items were deemed irrelevant. General terminology in the items (e.g., multivariable prediction model, predictors) was modified to align with AI-specific terms. After the first scoring round, further improvements of the items were formulated, e.g., by preventing the use of sub-questions or subjective words and adding clarifications on how to score an item. Using the final consensus list to score the 10 articles, only 2 out of the 61 items resulted in a statistically significant kappa of 0.4 or more demonstrating substantial agreement. For 41 items no statistically significant kappa was obtained indicating that the level of agreement among multiple observers is due to chance alone. CONCLUSION: Our study showed low reliability scores with the adapted TRIPOD and PROBAST checklists. Although such checklists have shown great value during development and reporting, this raises concerns about the applicability of such checklists to objectively score scientific articles for AI applications. When developing or revising guidelines, it is essential to consider their applicability to score articles without introducing bias.

[Challenges of automation in quantitative evaluation of liver biopsies : Automatic quantification of liver steatosis]. / Herausforderungen der Automation bei der quantitativen Auswertung von Leberbiopsien : Automatische Quantifizierung von Leberverfettung.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD), or non-alcoholic fatty liver disease (NAFLD), is a common disease that is diagnosed through manual evaluation of liver biopsies, an assessment that is subject to high interobserver variability (IBV). IBV can be reduced using automated methods. OBJECTIVES: Many existing computer-based methods do not accurately reflect what pathologists evaluate in practice. The goal is to demonstrate how these differences impact the prediction of hepatic steatosis. Additionally, IBV complicates algorithm validation. MATERIALS AND METHODS: Forty tissue sections were analyzed to detect steatosis, nuclei, and fibrosis. Data generated from automated image processing were used to predict steatosis grades. To investigate IBV, 18 liver biopsies were evaluated by multiple observers. RESULTS: Area-based approaches yielded more strongly correlated results than nucleus-based methods (⌀ Spearman rho [ρ] = 0.92 vs. 0.79). The inclusion of information regarding tissue composition reduced the average absolute error for both area- and nucleus-based predictions by 0.5% and 2.2%, respectively. Our final area-based algorithm, incorporating tissue structure information, achieved a high accuracy (80%) and strong correlation (⌀ Spearman ρ = 0.94) with manual evaluation. CONCLUSION: The automatic and deterministic evaluation of steatosis can be improved by integrating information about tissue composition and can serve to reduce the influence of IBV.

Application of computer-aided detection for NCCN-based follow-up recommendation in subsolid nodules: Effect on inter-observer agreement.

RATIONALE AND OBJECTIVES: Computer-aided detection (CAD) of pulmonary nodules reduces the impact of observer variability, improving the reliability and reproducibility of nodule assessments in clinical practice. Therefore, this study aimed to assess the impact of CAD on inter-observer agreement in the follow-up management of subsolid nodules. MATERIALS AND METHODS: A dataset comprising 60 subsolid nodule cases was constructed based on the National Cancer Center lung cancer screening data. Five observers independently assessed all low-dose computed tomography scans and assigned follow-up management strategies to each case according to the National Comprehensive Cancer Network (NCCN) guidelines, using both manual measurements and CAD assistance. The linearly weighted Cohen's kappa test was used to measure agreement between paired observers. Agreement among multiple observers was evaluated using the Fleiss kappa statistic. RESULTS: The agreement of the five observers for NCCN follow-up management categorization was moderate when measured manually, with a Fleiss kappa score of 0.437. Utilizing CAD led to a notable enhancement in agreement, achieving a substantial consensus with a Fleiss kappa value of 0.623. After using CAD, the proportion of major and substantial management discrepancies decreased from 27.5% to 15.8% and 4.8% to 1.5%, respectively (p < 0.01). In 23 lung cancer cases presenting as part-solid nodules, CAD significantly elevates the average sensitivity in detecting lung cancer cases presenting as part-solid nodules (overall sensitivity, 82.6% vs. 92.2%; p < 0.05). CONCLUSION: The application of CAD significantly improves inter-observer agreement in the follow-up management strategy for subsolid nodules. It also demonstrates the potential to reduce substantial management discrepancies and increase detection sensitivity in lung cancer cases presenting as part-solid nodules.

The accuracy and intra- and interobserver variability of PSMA PET/CT for the local staging of primary prostate cancer.

PURPOSE: Prostate-specific membrane antigen (PSMA) positron emission tomography/ computed tomography (PET/CT) is recognized as the most accurate imaging modality for detection of metastatic high-risk prostate cancer (PCa). Its role in the local staging of disease is yet unclear. We assessed the intra- and interobserver variability, as well as the diagnostic accuracy of the PSMA PET/CT based molecular imaging local tumour stage (miT-stage) for the local tumour stage assessment in a large, multicentre cohort of patients with intermediate and high-risk primary PCa, with the radical prostatectomy specimen (pT-stage) serving as the reference standard. METHODS: A total of 600 patients who underwent staging PSMA PET/CT before robot-assisted radical prostatectomy was studied. In 579 PSMA positive primary prostate tumours a comparison was made between miT-stage as assessed by four nuclear physicians and the pT-stage according to ISUP protocol. Sensitivity, specificity and diagnostic accuracy were determined. In a representative subset of 100 patients, the intra-and interobserver variability were assessed using Kappa-estimates. RESULTS: The sensitivity and specificity of the PSMA PET/CT based miT-stage were 58% and 59% for pT3a-stage, 30% and 97% for ≥ pT3b-stage, and 68% and 61% for overall ≥ pT3-stage, respectively. No statistically significant differences in diagnostic accuracy were found between tracers. We found a substantial intra-observer agreement for PSMA PET/CT assessment of ≥ T3-stage (k 0.70) and ≥ T3b-stage (k 0.75), whereas the interobserver agreement for the assessment of ≥ T3-stage (k 0.47) and ≥ T3b-stage (k 0.41) were moderate. CONCLUSION: In a large, multicentre study evaluating 600 patients with newly diagnosed intermediate and high-risk PCa, we showed that PSMA PET/CT may have a value in local tumour staging when pathological tumour stage in the radical prostatectomy specimen was used as the reference standard. The intra-observer and interobserver variability of assessment of tumour extent on PSMA PET/CT was moderate to substantial.

Recommendations for Additional Imaging on Head and Neck Imaging Examinations: Interradiologist Variation and Associated Factors.

BACKGROUND. A paucity of relevant guidelines may lead to pronounced variation among radiologists in issuing recommendations for additional imaging (RAI) for head and neck imaging. OBJECTIVE. The purpose of this article was to explore associations of RAI for head and neck imaging examinations with examination, patient, and radiologist factors and to assess the role of individual radiologist-specific behavior in issuing such RAI. METHODS. This retrospective study included 39,200 patients (median age, 58 years; 21,855 women, 17,315 men, 30 with missing sex information) who underwent 39,200 head and neck CT or MRI examinations, interpreted by 61 radiologists, from June 1, 2021, through May 31, 2022. A natural language processing (NLP) tool with manual review of NLP results was used to identify RAI in report impressions. Interradiologist variation in RAI rates was assessed. A generalized mixed-effects model was used to assess associations between RAI and examination, patient, and radiologist factors. RESULTS. A total of 2943 (7.5%) reports contained RAI. Individual radiologist RAI rates ranged from 0.8% to 22.0% (median, 7.1%; IQR, 5.2-10.2%), representing a 27.5-fold difference between minimum and a maximum values and 1.8-fold difference between 25th and 75th percentiles. In multivariable analysis, RAI likelihood was higher for CTA than for CT examinations (OR, 1.32), for examinations that included a trainee in report generation (OR, 1.23), and for patients with self-identified race of Black or African American versus White (OR, 1.25); was lower for male than female patients (OR, 0.90); and was associated with increasing patient age (OR, 1.09 per decade) and inversely associated with radiologist years since training (OR, 0.90 per 5 years). The model accounted for 10.9% of the likelihood of RAI. Of explainable likelihood of RAI, 25.7% was attributable to examination, patient, and radiologist factors; 74.3% was attributable to radiologist-specific behavior. CONCLUSION. Interradiologist variation in RAI rates for head and neck imaging was substantial. RAI appear to be more substantially associated with individual radiologist-specific behavior than with measurable systemic factors. CLINICAL IMPACT. Quality improvement initiatives, incorporating best practices for incidental findings management, may help reduce radiologist preference-sensitive decision-making in issuing RAI for head and neck imaging and associated care variation.

Diagnostic accuracy of non-contrast MRI in frozen shoulder.

INTRODUCTION: Despite being the most used exam today, few studies have evaluated the accuracy of findings on non-contrast magnetic resonance imaging (MRI). The primary objective of the study was to evaluate the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of non-contrast MRI findings in frozen shoulder, isolated and in combination. The secondary objectives were to define the interobserver and intraobserver agreement of the assessments and the odds ratio for frozen shoulder because of the various findings of MRI. METHODS: A retrospective diagnostic accuracy study comparing non-contrast MRI findings between the frozen shoulder group and the control group. Sensitivity, specificity, positive and negative predictive value, accuracy, odds ratio, interobserver and intraobserver agreement were calculated for each finding and their possible associations. RESULTS: The hyperintensity on capsule in the axillary recess presented 84% sensitivity, 94% specificity, and 89% accuracy. The obliteration of the subcoracoid fat triangle in the rotator interval had sensitivity 34%, specificity 82% and accuracy 58%. For coracohumeral ligament thickness ≥ 2 mm had specificity 66%, 48% specificity and 57% accuracy. Capsule thickness in the axillary recess ≥ 4 mm resulted in 54% sensitivity, 82% specificity, and 68% accuracy. Regarding interobserver agreement, only the posteroinferior and posterosuperior quadrants showed moderate results, and all the others showed strong reliability. The odds ratio for hyperintensity in the axillary recess was 82.3 for frozen shoulder. The association of these findings increased specificity (95%). CONCLUSION: The accuracy of non-contrast magnetic resonance imaging is high for diagnosing frozen shoulder, especially when evaluating the hyperintensity of the axillary recess. The exam has high reliability and reproducibility. The presence of an association of signs increases the specificity of the test. LEVEL OF EVIDENCE: Level III, study of diagnostic test.

Reproducibility of rCBV in glioblastomas using T2*-weighted perfusion MRI: an evaluation of sampling, normalization, and experience.

PURPOSE: The reproducibility of relative cerebral blood volume (rCBV) measurements among readers with different levels of experience is a concern. This study aimed to investigate the inter-reader reproducibility of rCBV measurement of glioblastomas using the hotspot method in dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC-MRI) with various strategies. METHODS: In this institutional review board-approved single-center study, 30 patients with glioblastoma were retrospectively evaluated with DSC-MRI at a 3.0 Tesla scanner. Three groups of reviewers, including neuroradiologists, general radiologists, and radiology residents, calculated the rCBV based on the number of regions of interest (ROIs) and reference areas. For statistical analysis of feature reproducibility, the intraclass correlation coefficient (ICC) and Bland-Altman plots were used. Analyses were made among individuals, reader groups, reader-group pooling, and a population that contained all of them. RESULTS: For individuals, the highest inter-reader reproducibility was observed between neuroradiologists [ICC: 0.527; 95% confidence interval (CI): 0.21-0.74] and between residents (ICC: 0.513; 95% CI: 0.20-0.73). There was poor reproducibility in the analyses of individuals with different levels of experience (ICC range: 0.296-0.335) and in reader-wise and group-wise pooling (ICC range: 0.296-0.335 and 0.397-0.427, respectively). However, an increase in ICC values was observed when five ROIs were used. In an analysis of all strategies, the ICC for the centrum semiovale was significantly higher than that for contralateral white matter (P < 0.001). CONCLUSION: The inter-reader reproducibility of rCBV measurement was poor to moderate regardless of whether it was calculated by neuroradiologists, general radiologists, or residents, which may indicate the need for automated methods. Choosing five ROIs and using the centrum semiovale as a reference area may increase reliability for all users.

MR Elastography of the Pancreas: Bowel Preparation and Repeatability Assessment in Pancreatic Cancer Patients and Healthy Controls.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) stromal viscoelasticity can be measured using MR elastography (MRE). Bowel preparation regimens could affect MRE quality and knowledge on repeatability is crucial for clinical implementation. PURPOSE: To assess effects of four bowel preparation regimens on MRE quality and to evaluate repeatability and differentiate patients from healthy controls. STUDY TYPE: Prospective. POPULATION: 15 controls (41 ± 16 years; 47% female), 16 PDAC patients (one excluded, 66 ± 12 years; 40% female) with 15 age-/sex-matched controls (65 ± 11 years; 40% female). Final sample size was 25 controls and 15 PDAC. FIELD STRENGTH/SEQUENCE: 3-T, spin-echo echo-planar-imaging, turbo spin-echo, and fast field echo gradient-echo. ASSESSMENT: Four different regimens were used: fasting; scopolaminebutyl; drinking 0.5 L water; combination of 0.5 L water and scopolaminebutyl. MRE signal-to-noise ratio (SNR) was compared between all regimens. MRE repeatability (test-retest) and differences in shear wave speed (SWS) and phase angle (ϕ) were assessed in PDAC and controls. Regions-of-interest were defined for tumor, nontumorous (n = 8) tissue in PDAC, and whole pancreas in controls. Two radiologists delineated tumors twice for evaluation of intraobserver and interobserver variability. STATISTICAL TESTS: Repeated measures analysis of variance, coefficients of variation (CoVs), Bland-Altman analysis, (un)paired t-test, Mann-Whitney U-test, and Wilcoxon signed-rank test. P-value<0.05 was considered statistically significant. RESULTS: Preparation regimens did not significantly influence MRE-SNR. Therefore, the least burdensome preparation (fasting only) was continued. CoVs for tumor SWS were: intrasession (12.8%) and intersession (21.7%), and intraobserver (7.9%) and interobserver (10.3%) comparisons. For controls, CoVs were intrasession (4.6%) and intersession (6.4%). Average SWS for tumor, nontumor, and healthy tissue were: 1.74 ± 0.58, 1.38 ± 0.27, and 1.18 ± 0.16 m/sec (ϕ: 1.02 ± 0.17, 0.91 ± 0.07, and 0.85 ± 0.08 rad), respectively. Significant differences were found between all groups, except for ϕ between healthy-nontumor (P = 0.094). DATA CONCLUSION: The proposed bowel preparation regimens may not influence MRE quality. MRE may be able to differentiate between healthy tissue-tumor and tumor-nontumor. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study.

PURPOSE: To quantify interobserver variation (IOV) in target volume and organs-at-risk (OAR) contouring across 31 institutions in breast cancer cases and to explore the clinical utility of deep learning (DL)-based auto-contouring in reducing potential IOV. METHODS AND MATERIALS: In phase 1, two breast cancer cases were randomly selected and distributed to multiple institutions for contouring six clinical target volumes (CTVs) and eight OAR. In Phase 2, auto-contour sets were generated using a previously published DL Breast segmentation model and were made available for all participants. The difference in IOV of submitted contours in phases 1 and 2 was investigated quantitatively using the Dice similarity coefficient (DSC) and Hausdorff distance (HD). The qualitative analysis involved using contour heat maps to visualize the extent and location of these variations and the required modification. RESULTS: Over 800 pairwise comparisons were analysed for each structure in each case. Quantitative phase 2 metrics showed significant improvement in the mean DSC (from 0.69 to 0.77) and HD (from 34.9 to 17.9 mm). Quantitative analysis showed increased interobserver agreement in phase 2, specifically for CTV structures (5-19 %), leading to fewer manual adjustments. Underlying IOV differences causes were reported using a questionnaire and hierarchical clustering analysis based on the volume of CTVs. CONCLUSION: DL-based auto-contours improved the contour agreement for OARs and CTVs significantly, both qualitatively and quantitatively, suggesting its potential role in minimizing radiation therapy protocol deviation.