Intraobserver Variability Research Articles

AI drives the assessment of lung cancer microenvironment composition

PurposeThe abundance and distribution of tumor-infiltrating lymphocytes (TILs) as well as that of other components of the tumor microenvironment is of particular importance for predicting response to immunotherapy in lung cancer (LC). We describe here a pilot study employing artificial intelligence (AI) in the assessment of TILs and other cell populations, intending to reduce the inter- or intra-observer variability that commonly characterizes this evaluation. DesignWe developed a machine learning-based classifier to detect tumor, immune, and stromal cells on hematoxylin and eosin-stained sections, using the open-source framework QuPath. We evaluated the quantity of the aforementioned three cell populations among 37 LC whole slide images regions of interest, comparing the assessments made by five pathologists, both before and after using graphical predictions made by AI, for a total of 1110 quantitative measurements. ResultsOur findings indicate noteworthy variations in score distribution among pathologists and between individual pathologists and AI. The AI-guided pathologist's evaluations resulted in reduction of significant discrepancies across pathologists: three comparisons showed a loss of significance (p > 0.05),whereas other four showed a reduction in significance (p > 0.01). ConclusionsWe show that employing a machine learning approach in cell population quantification reduces inter- and intra-observer variability, improving reproducibility and facilitating its use in further validation studies.

The bone trauma and soft-tissue injury classification system in total hip arthroplasty (BOSTI Hip).

The primary objective of this study was to develop a validated classification system for assessing iatrogenic bone trauma and soft-tissue injury during total hip arthroplasty (THA). The secondary objective was to compare macroscopic bone trauma and soft-tissues injury in conventional THA (CO THA) versus robotic arm-assisted THA (RO THA) using this classification system. This study included 30 CO THAs versus 30 RO THAs performed by a single surgeon. Intraoperative photographs of the osseous acetabulum and periacetabular soft-tissues were obtained prior to implantation of the acetabular component, which were used to develop the proposed classification system. Interobserver and intraobserver variabilities of the proposed classification system were assessed. The BOne trauma and Soft-Tissue Injury classification system in total Hip arthroplasty (BOSTI Hip) grades osseous acetabular trauma and periarticular muscle damage during THA. The classification system has an interclass correlation coefficient of 0.90 (95% CI 0.86 to 0.93) for interobserver agreement and 0.89 (95% CI 0.84 to 0.93) for intraobserver agreement. RO THA was associated with improved BOSTI Hip scores (p = 0.002) and more pristine osseous surfaces in the anterior superior (p = 0.001) and posterior superior (p < 0.001) acetabular quadrants compared with CO THA. There were no differences between the groups in relation to injury to the gluteus medius (p = 0.084), obturator internus (p = 0.241), piriformis (p = 0.081), superior gamellus (p = 0.116), inferior gamellus (p = 0.132), quadratus femoris (p = 0.208), and vastus lateralis (p = 0.135), but overall combined muscle injury was reduced in RO THA compared with CO THA (p = 0.023). The proposed BOSTI Hip classification provides a reproducible grading system for stratifying iatrogenic bone trauma and soft-tissue injury during THA. RO THA was associated with improved BOSTI Hip scores, more pristine osseous acetabular surfaces, and reduced combined periarticular muscle injury compared with CO THA. Further research is required to understand if these intraoperative findings translate to differences in clinical outcomes between the treatment groups.

Deep learning with uncertainty estimation for automatic tumor segmentation in PET/CT of head and neck cancers: impact of model complexity, image processing and augmentation

Objective. Target volumes for radiotherapy are usually contoured manually, which can be time-consuming and prone to inter- and intra-observer variability. Automatic contouring by convolutional neural networks (CNN) can be fast and consistent but may produce unrealistic contours or miss relevant structures. We evaluate approaches for increasing the quality and assessing the uncertainty of CNN-generated contours of head and neck cancers with PET/CT as input. Approach. Two patient cohorts with head and neck squamous cell carcinoma and baseline 18F-fluorodeoxyglucose positron emission tomography and computed tomography images (FDG-PET/CT) were collected retrospectively from two centers. The union of manual contours of the gross primary tumor and involved nodes was used to train CNN models for generating automatic contours. The impact of image preprocessing, image augmentation, transfer learning and CNN complexity, architecture, and dimension (2D or 3D) on model performance and generalizability across centers was evaluated. A Monte Carlo dropout technique was used to quantify and visualize the uncertainty of the automatic contours. Main results. CNN models provided contours with good overlap with the manually contoured ground truth (median Dice Similarity Coefficient: 0.75–0.77), consistent with reported inter-observer variations and previous auto-contouring studies. Image augmentation and model dimension, rather than model complexity, architecture, or advanced image preprocessing, had the largest impact on model performance and cross-center generalizability. Transfer learning on a limited number of patients from a separate center increased model generalizability without decreasing model performance on the original training cohort. High model uncertainty was associated with false positive and false negative voxels as well as low Dice coefficients. Significance. High quality automatic contours can be obtained using deep learning architectures that are not overly complex. Uncertainty estimation of the predicted contours shows potential for highlighting regions of the contour requiring manual revision or flagging segmentations requiring manual inspection and intervention.

Automated immunohistochemistry of intra-epidermal nerve fibres in skin biopsies: A proof-of-concept study.

To develop a standardised, automated protocol for detecting protein gene product 9.5 (PGP9.5) positive intra-epidermal nerve fibres (IENFs) in skin biopsies, transitioning from the established manual technique to an automated platform. This automated method, although currently intended for research applications, may improve the accessibility of this diagnostic test for small fibre neuropathy in clinical settings. Skin biopsies (n = 274) from 100 participants (fibromyalgia syndrome n = 62; idiopathic small fibre neuropathy: n = 16; healthy volunteers: n = 22) were processed using an automated immunohistochemistry platform. IENF quantification was performed by blinded examiners, with reliability assessed via a two-way mixed-effects model to evaluate inter- and intra-observer variability. The automated staining system reproduced intra-epidermal nerve fibre density (IENFD) counts consistent with free-floating sections (mean ± standard deviation: free-floating: 5.6 ± 3.4 fibres/mm; automated: 5.9 ± 3.2 fibres/mm). A median difference of 0.3 with a lower bound 95% Confidence Interval (CI) at -0.00005 established non-inferiority against a margin of -0.4 (p = .08). Specifically, the inter-class correlation coefficient (class denotes consistency in measured observations) was 99% (95% CI: 0.9-1), indicating excellent agreement between free-floating and automated methods. The inter- and intra-class coefficient between examiners were both 99% (95% CI: 0.9-0.1) for IENFD, demonstrating high reliability using sections stained using the automated method. Automated immunohistochemistry provides high-throughput reliable and reproducible intra-epidermal nerve fibre quantification. This method, although currently proof-of-concept, for research use only, may be more widely deployed in histopathology laboratories to increase the adoption of IENFD assessment for the diagnosis of peripheral neuropathies.

A new era of high-resolution CT diagnostics of the lung: improved image quality, detailed morphology, and reduced radiation dose with high-resolution photon-counting CT of the lungs compared to high-resolution energy-integrated CT.

High-resolution computed tomography (HRCT) is dependent on detailed morphology in diagnostic assessment of interstitial lung diseases. Photon-counting CT (PCCT) enables improved resolution while reducing radiation. To compare if the image quality, detailed morphology, and radiation dose in HRCT of the lung improves with PCCT compared to energy-integrated CT (EICT). HRCT with PCCT in patients with body mass index (BMI) from normal to obese, previously examined with different EICT were included. They were evaluated in a five-step scale for image quality according to Quality Criteria for CT (Diagnostic Requirement of the ImPACT group-European standardization). In addition, ground-glass opacities, bronchiectasis, emphysema, nodules, and subpleural detailed morphology (≤1 cm from the pleural border) were evaluated by three independent thoracic and/or pediatric radiologists. Visual grading characteristics (VGC) were used for comparison of image quality and detailed morphology and Fleiss kappa for intra-observer variability. Dose-length product (DLP) and CT dose index-volume (CTDIvol) were collected to calculate effective radiation dose. HRCT with PCCT in 52 women and 48 men (mean age=67.2 ± 13.6 years; age range=27-87 years; BMI=26.9 kg/m2; range=18.6-45 kg/m2) previously examined with EICT (mean age=65.3 ± 13.6 years; age range=27-85 years; BMI=27 kg/m2; range=18.9-45 kg/m2) were included. There were significant differences in image quality for all entities in favor of PCCT. The radiation dose was reduced with PCCT by 47% in all, particularly pronounced in obese with 48.5%. Image quality, detailed morphology, and radiation dose, particularly in obese patients, were significantly improved in HRCT with PCCT compared to conventional EICT. The new technique enables visualization of subpleural structures.

Evaluation of automatic cochlear dimension measurement using ALPACA: a comparative study

Background Cochlear dimension measurements are critical in diagnosing and managing congenital sensorineural hearing loss. Objectives To evaluate the feasibility and reliability of an automated landmark approach for measuring cochlear dimensions (A-, B- and H-values). Material and Methods Cochlear parameters from 100 patients were measured by MPR, manual three-dimensional and ALPACA. We assessed intra- and inter-observer reliability as well as inter-method reliability. Statistical analyses were conducted to detect differences between the right and left ears, as well as to assess the relevance of the values obtained using ALPACA. Results All A-, B-, and H-values measured by the various methods showed a high intra-observer reliability with intra-class correlation coefficients (ICC) ranging from 0.70 to 0.99, and values gained by ALPACA reaching the highest ICC. Inter-method reliability was at a good level with ICC ranging from 0.51 to 0.86. There were no significant differences between the right and left ears’ measured values. Obvious positive correlations existed among cochlear dimensions measured by ALPACA. Conclusions and Significance The ALPACA method can be used to measure cochlear dimensions. Values obtained by the method demonstrate high reliability and consistency with a significant reduction in intra-observer variability compared to results from conventional MPR and manual 3D measurements.

Evaluation of Osteotomy Healing in Boxer Dogs Undergoing Tibial Plateau Levelling Osteotomy Using Two Radiographic Scoring Systems.

The aim of this study was to (1) compare 5-point and 10-point bone healing radiographic scoring systems using postoperative tibial plateau levelling osteotomy (TPLO) radiographs and (2) determine whether Boxer osteotomy healing time differs from age-matched Labrador Retrievers. This was a multicentre retrospective study. Fifty-eight client-owned dogs undergoing TPLO (29 Boxers and 29 Labrador Retrievers) were included. Five board-certified surgeons evaluated the radiographs three independent times. Osteotomy healing approximately 8 weeks postoperatively was graded using previously reported 5-point and 10-point scoring systems and immediate postoperative radiographs were assessed for the presence of an osteotomy gap of ≥1 mm. Both scoring systems had good consistency among observers. Intraobserver consistency was good in three out of five observers using the 5-point system and in four out of five observers using the 10-point system. Boxers had significantly lower radiographic healing scores at 8 weeks postoperatively compared with Labrador Retrievers using both scoring systems (p ≤ 0.001). The presence of an osteotomy gap postoperatively resulted in significantly lower healing scores at 8 weeks using both scoring systems (p < 0.001) in both breeds. No difference was found in inter- and intraobserver variability between scoring systems. Boxer dogs had lower healing scores at 8 weeks after TPLO compared with Labrador Retrievers. An osteotomy gap of ≥1 mm was associated with lower healing scores.

Intra-observer variability in liver stiffness and ultrasound attenuation parameter measurement using vibration-controlled transient elastography in patients with metabolic dysfunction-associated steatotic liver disease

Intra-observer variability in liver stiffness and ultrasound attenuation parameter measurement using vibration-controlled transient elastography in patients with metabolic dysfunction-associated steatotic liver disease

A New Index for Assessment of Severity and Extent of Gingival Pigmentation; A Diagnostic Cross-Sectional Study According to Inter and Intra-Observer Variability.

Classification of gingival pigmentation (GP) is often performed using gingival pigmentation index (GPI), melanin pigmentation index (MPI), oral pigmentation index (DOPI), melanin index (MI), or physiologic/pathologic GPI. However, the internal and external reproducibility of these indexes have not been evaluated. This study aimed to introduce a new simple and applicable GPI and assess its internal and external reproducibility. This diagnostic cross-sectional study was conducted on 40 patients with maxillary and mandibular GP. Patients were in the age range of 12-60 years, and degree of GP was determined by four periodontists using DOPI, MI, MPI, GPI and the new index namely the severity and extension of gingival melanotic pigmentation index (SEMPI) under similar environmental and lighting conditions. The inclusion criteria were in the age range of 12-60 years and presence of melanin pigmentation (physiologic or pathologic) in the gingival margin, papilla, or attached gingiva. The exclusion criteria were systemic diseases, vascular lesions, hemochromatosis, amalgam tattoo, hyperbilirubinemia, or use of medications causing nonmelanotic pigmentation (hemoglobin, iron, and amalgam). The Fleiss kappa between all examiners for all indexes at 0, 7, and 14 days was higher than 0.8, indicating high agreement among the examiners. The Spearman's correlation coefficient for all indexes was positive and high at 0, 7, and 14 days (P < 0.001). Considering the high agreement among the examiners for all indexes and at all-time points as well as the positive, strong correlations among them, it seems that the new index is useful for classification of GP.

Automated contouring of CTV and OARs in planning CT scans using novel hybrid convolution-transformer networks for prostate cancer radiotherapy

Purpose objective(s)Manual contouring of the prostate region in planning computed tomography (CT) images is a challenging task due to factors such as low contrast in soft tissues, inter- and intra-observer variability, and variations in organ size and shape. Consequently, the use of automated contouring methods can offer significant advantages. In this study, we aimed to investigate automated male pelvic multi-organ contouring in multi-center planning CT images using a hybrid convolutional neural network-vision transformer (CNN-ViT) that combines convolutional and ViT techniques.Materials/methodsWe used retrospective data from 104 localized prostate cancer patients, with delineations of the clinical target volume (CTV) and critical organs at risk (OAR) for external beam radiotherapy. We introduced a novel attention-based fusion module that merges detailed features extracted through convolution with the global features obtained through the ViT.ResultsThe average dice similarity coefficients (DSCs) achieved by VGG16-UNet-ViT for the prostate, bladder, rectum, right femoral head (RFH), and left femoral head (LFH) were 91.75%, 95.32%, 87.00%, 96.30%, and 96.34%, respectively. Experiments conducted on multi-center planning CT images indicate that combining the ViT structure with the CNN network resulted in superior performance for all organs compared to pure CNN and transformer architectures. Furthermore, the proposed method achieves more precise contours compared to state-of-the-art techniques.ConclusionResults demonstrate that integrating ViT into CNN architectures significantly improves segmentation performance. These results show promise as a reliable and efficient tool to facilitate prostate radiotherapy treatment planning.

Inter- and intra-observer variation in phytolith morphometry.

Archaeobotanists and palaeoecologists extensively use geometric morphometrics to identify plant opal phytoliths. Particularly when applied to assemblages of phytoliths from concentrations retrieved from closed contexts, morphometric data from archaeological phytoliths compared with similar data from reference material may allow taxonomic attribution. Observer variation is one aspect of phytolith morphometry that has received little attention but may be an important source of error, and hence cause of potential misidentification of plant remains. To investigate inter- and intra-observer variation in phytolith morphometry, eight researchers (observers) from different laboratories measured 50 samples each from three phytolith morphotypes, Bilobate, Bulliform flabellate and Elongate dendritic, three times, under the auspices of the International Committee for Phytolith Morphometrics (ICPM). Data for 17 size and shape variables were collected for each phytolith by manually digitising a phytolith outline (mask) from a photograph, followed by measurement of the mask with open-source morphometric software. Inter-observer variation ranged from 0 to 23% difference from the mean of all observers. Intra-observer variation ranged from 0 to 9% difference from the mean of individual observers per week. Inter- and intra-observer variation was generally higher among inexperienced researchers. Scaling errors were a major cause of variation and occurred more with less experienced researchers, which is likely related to familiarity with data collection. The results indicate that inter- and intra-observer variation can be substantially reduced by providing clear instructions for and training with the equipment, photo capturing, software, data collection and data cleaning. In this paper, the ICPM provides recommendations to minimise variation.Advances in automatic data collection may eventually reduce inter- and intra-observer variation, but until this is common practice, the ICPM recommends that phytolith morphometric analyses adhere to standardised guidelines to assure that measured phytolith variables are accurate, consistent and comparable between different researchers and laboratories.

Clinical applicability of signal heterogeneity and tumor border assessment on T2-weighted MR images to distinguish astrocytic from oligodendroglial origin of gliomas

Background and purposeRadiological features on magnetic resonance imaging (MRI) were attributed to oligodendroglioma, although the diagnostic accuracy in a real-world clinical setting remains partially elusive. This study investigated the accuracy and robustness of tumor heterogeneity and tumor border delineation on T2-weighted MRI to distinguish oligodendroglioma from astrocytoma. Materials and methodsEight readers from three different specialties (radiology, neurology, neurosurgery) with varying levels of experience blindly rated 79 T2-weighted MR images of patients with either oligodendroglioma or astrocytoma. After the first reading session, all readers were re-invited for a second reading session within three weeks. Diagnostic accuracy, including area under the receiver operator characteristics curve (AUC), and intra-observer variability and inter-observer variability were used as outcome measures. ResultsPooled sensitivity and specificity to distinguish oligodendroglioma from astrocytoma for the use of tumor heterogeneity were 59.9 % respectively 74.5 %, and 85.7 % respectively 40.1 % for tumor border. A second reading session did not result in a significant change in sensitivity or specificity for tumor heterogeneity (P = 0.752 and P = 0.733, respectively) or tumor border (P = 0.309 and P = 0.271, respectively). An AUC of 0.825 was achieved with regard to predicting oligodendroglial origin of gliomas. Intra-observer agreement ranged from moderate to very good for tumor heterogeneity (kappa-value 0.43–0.87) and tumor border (0.40–0.84). A moderate inter-oberserver agreement was achieved for tumor heterogeneity and tumor border (kappa-value of 0.50 and 0.45, respectively). ConclusionThis study demonstrates that tumor heterogeneity and tumor borders on T2-weighted MRI could be used with moderate Finter-observer agreement to non-invasively distinguish oligodendroglioma from astrocytoma.

Optimized target delineation procedure for the radiosurgery treatment of ventricular tachycardia: observer-independent accuracy.

Part of the current stereotactic arrythmia radioablation (STAR) workflow is transfer of findings from the electroanatomic mapping (EAM) to computed tomography (CT). Here, we analyzed inter- and intraobserver variation in a modified EAM-CT registration using automatic registration algorithms designed to yield higher robustness. This work is based on data of 10 patients who had previously undergone STAR. Two observers participated in this study: (1) an electrophysiologist technician (cardiology) with substatial experience in EAM-CT merge, and (2) a clinical engineer (radiotherapy) with minimum experience with EAM-CT merge. EAM-CT merge consists of 3 main steps: segmentation of left ventricle from CT (CT LV), registration of the CT LV and EAM, clinical target volume (CTV) delineation from EAM specific points. Mean Hausdorff distance (MHD), Dice Similarity Coefficient (DSC) and absolute difference in Center of Gravity (CoG) were used to assess intra/interobserver variability. Intraobserver variability: The mean DSC and MHD for 3 CT LVs altogether was 0.92 ± 0.01 and 1.49 ± 0.23 mm. The mean DSC and MHD for 3 CTVs altogether was 0,82 ± 0,06 and 0,71 ± 0,22 mm. Interobserver variability: Segmented CT LVs showed great similarity (mean DSC of 0,91 ± 0,01, MHD of 1,86 ± 0,47 mm). The mean DSC comparing CTVs from both observers was 0,81 ± 0,11 and MHD was 0,87 ± 0,45 mm. The high interobserver similarity of segmented LVs and delineated CTVs confirmed the robustness of the proposed method. Even an inexperienced user can perform a precise EAM-CT merge following workflow instructions.

Acceleration of skeletal maturation in Central Europe over the last two decades: insights from two cohorts of healthy children

BackgroundDeviations between the determination of bone age (BA) according to Greulich and Pyle (G&P) and chronological age (CA) are common in Caucasians. Assessing these discrepancies in a population over time requires analysis of large samples and low intra-observer variability in BA estimation, both can be achieved with artificial intelligence-based software. The latest software-based reference curve contrasting the BA determined by G&P to the CA of Central European children dates back over two decades.ObjectiveTo examine whether the reference curve from a historical cohort from the Netherlands (Rotterdam cohort) between BA determined by G&P and CA still applies to a current Central European cohort and derive a current reference curve.Materials and methodsThis retrospective single-center study included 1,653 children and adolescents (aged 3–17 years) who had received a radiograph of the hand following trauma. The G&P BA estimated using artificial intelligence-based software was contrasted with the CA, and the deviations were compared with the Rotterdam cohort.ResultsAmong the participants, the mean absolute error between BA and CA was 0.92 years for girls and 0.97 years for boys. For the ages of 8 years (boys) and 11 years (girls) and upward, the mean deviation was significantly greater in the current cohort than in the Rotterdam cohort. The reference curves of both cohorts also differed significantly from each other (P < 0.001 for both boys and girls).ConclusionThe BA of the current Central European population and that of the curve from the Rotterdam cohort from over two decades ago differ. Whether this effect can be attributed to accelerated bone maturation needs further evaluation.

Assessment of Interobserver Agreement Among Gynecologic Pathologists Between Three-Tier Versus Binary Pattern-based Classification Systems for HPV-associated Endocervical Adenocarcinoma.

The three-tier (A vs. B vs. C) pattern-based (Silva) classification system is a strong and fairly reproducible predictor of the risk of lymph node involvement and recurrence of human papillomavirus (HPV)-associated endocervical adenocarcinoma (EA). Recently, a binary pattern-based classification system has been proposed which incorporates the Silva pattern and lymphovascular invasion (LVI) to assign tumors as "low risk" or "high risk" and this may have superior prognostic significance compared with the three-tier system as well as current International Federation of Gynecology and Obstetrics (FIGO) staging of cervix-confined disease. The interobserver reproducibility of this binary system, however, is unknown. Representative slides from 59 HPV-associated EAs (1-3 slides/case) were independently reviewed by 5 gynecologic pathologists who participated in an online training module before the study. In the first review, a pattern was assigned using the three-tier system. On the second review, a "low risk" or "high risk" designation was assigned and the presence or absence of LVI was specifically documented. Interobserver agreement was assessed using Fleiss' kappa. The binary system showed improved interobserver agreement (kappa=0.634) compared with the three-tier system (kappa=0.564), with a higher proportion of cases having agreement between at least 4/5 reviewers (86% vs. 73%). Nineteen and 8 cases showed improved and worse interobserver agreement using the binary system, respectively; the remainder showed no change. 3/5 reviewers showed no intraobserver discrepancy while the remaining 2 did in a small subset of cases (n=2 and 4, respectively). In this study, a binary pattern-based classification system showed improved interobserver agreement compared with the traditional three-tier system.

A comparison of target volumes drawn on arterial and venous phase scans during radiation therapy planning for patients with pancreatic cancer: the PANCRINJ study

BackgroundThe planification of radiation therapy (RT) for pancreatic cancer (PC) requires a dosimetric computed tomography (CT) scan to define the gross tumor volume (GTV). The main objective of this study was to compare the inter-observer variability in RT planning between the arterial and the venous phases following intravenous contrast.MethodsPANCRINJ was a prospective monocentric study that included twenty patients with non-metastatic PC. Patients underwent a pre-therapeutic CT scan at the arterial and venous phases. The delineation of the GTV was performed by one radiologist (gold standard) and two senior radiation oncologists (operators). The primary objective was to compare the Jaccard conformity index (JCI) for the GTVs computed between the GS (gold standard) and the operators between the arterial and the venous phases with a Wilcoxon signed rank test for paired samples. The secondary endpoints were the geographical miss index (GMI), the kappa index, the intra-operator variability, and the dose-volume histograms between the arterial and venous phases.ResultsThe median JCI for the arterial and venous phases were 0.50 (range, 0.17–0.64) and 0.41 (range, 0.23–0.61) (p = 0.10) respectively. The median GS-GTV was statistically significantly smaller compared to the operators at the arterial (p < 0.0001) and venous phases (p < 0.001), respectively. The GMI were low with few tumors missed for all patients with a median GMI of 0.07 (range, 0-0.79) and 0.05 (range, 0-0.39) at the arterial and venous phases, respectively (p = 0.15). There was a moderate agreement between the radiation oncologists with a median kappa index of 0.52 (range 0.38–0.57) on the arterial phase, and 0.52 (range 0.36–0.57) on the venous phase (p = 0.08). The intra-observer variability for GTV delineation was lower at the venous phase than at the arterial phase for the two operators. There was no significant difference between the arterial and the venous phases regarding the dose-volume histogram for the operators.ConclusionsOur results showed inter- and intra-observer variability in delineating GTV for PC without significant differences between the arterial and the venous phases. The use of both phases should be encouraged. Our findings suggest the need to provide training for radiation oncologists in pancreatic imaging and to collaborate within a multidisciplinary team.

Inter- and Intra-Observer Variability of the AMADEUS Tool for Osteochondral Lesions of the Talus.

Managing osteochondral cartilage defects (OCDs) of the talus is a common daily challenge in orthopaedics as they predispose patients to further cartilage damage and progression to osteoarthritis. Therefore, the implementation of a reliable tool to quantify the amount of cartilage damage that is present is of the essence. We retrospectively identified 15 adult patients diagnosed with uncontained OCDs of the talus measuring <150 mm2, which were treated arthroscopically with bone marrow stimulation. Five independent assessors evaluated the pre-operative MRI scans with the AMADEUS scoring system (i.e., MR-based pre-operative assessment system) and the intra-/inter-observer variability was then calculated by means of the intraclass correlation coefficients (ICC) and Kappa (κ) statistics, respectively. In addition, the correlation between the mean AMADEUS scores and pre-operative self-reported outcomes as measured by the Manchester-Oxford foot questionnaire (MOxFQ) was assessed. The mean ICC and the κ statistic were 0.82 (95% CI [0.71, 0.94]) and 0.42 (95% CI [0.25, 0.59]). The Pearson correlation coefficient was found to be r = -0.618 (p = 0.014). The AMADEUS tool, which was originally designed to quantify knee osteochondral defect severity prior to cartilage repair surgery, demonstrated good reliability and moderate inter-observer variability for small OCDs of the talar shoulder. Given the strong negative correlation between the AMADEUS tool and pre-operative clinical scores, this tool could be implemented in clinical practise to reliably quantify the extent of the osteochondral defects of the talus.

A prognostic and predictive computational pathology immune signature for ductal carcinoma in situ: retrospective results from a cohort within the UK/ANZ DCIS trial

The density of tumour-infiltrating lymphocytes (TILs) could be prognostic in ductal carcinoma in situ (DCIS). However, manual TIL quantification is time-consuming and suffers from interobserver and intraobserver variability. In this study, we developed a TIL-based computational pathology biomarker and evaluated its association with the risk of recurrence and benefit of adjuvant treatment in a clinical trial cohort. In this retrospective cohort study, a computational pathology pipeline was developed to generate a TIL-based biomarker (CPath TIL categories). Subsequently, the signature underwent a masked independent validation on H&E-stained whole-section images of 755 patients with DCIS from the UK/ANZ DCIS randomised controlled trial. Specifically, continuous biomarker CPath TIL score was calculated as the average TIL density in the DCIS microenvironment and dichotomised into binary biomarker CPath TIL categories (CPath TIL-high vs CPath TIL-low) using the median value as a cutoff. The primary outcome was ipsilateral breast event (IBE; either recurrence of DCIS [DCIS-IBE] or invasive progression [I-IBE]). The Cox proportional hazards model was used to estimate the hazard ratio (HR). CPath TIL-score was evaluable in 718 (95%) of 755 patients (151 IBEs). Patients with CPath TIL-high DCIS had a greater risk of IBE than those with CPath TIL-low DCIS (HR 2·10 [95% CI 1·39-3·18]; p=0·0004). The risk of I-IBE was greater in patients with CPath TIL-high DCIS than those with CPath TIL-low DCIS (3·09 [1·56-6·14]; p=0·0013), and the risk of DCIS-IBE was non-significantly higher in those with CPath TIL-high DCIS (1·61 [0·95-2·72]; p=0·077). A significant interaction (pinteraction=0·025) between CPath TIL categories and radiotherapy was observed with a greater magnitude of radiotherapy benefit in preventing IBE in CPath TIL-high DCIS (0·32 [0·19-0·54]) than CPath TIL-low DCIS (0·40 [0·20-0·81]). High TIL density is associated with higher recurrence risk-particularly of invasive recurrence-and greater radiotherapy benefit in patients with DCIS. Our TIL-based computational pathology signature has a prognostic and predictive role in DCIS. National Cancer Institute under award number U01CA269181, Cancer Research UK (C569/A12061; C569/A16891), and the Breast Cancer Research Foundation, New York (NY, USA).

Influence of cardiac cycle on myocardial extracellular volume fraction measurements with dual-layer computed tomography.

In cardiac computed tomography (CT), the best image quality is obtained at mid-diastole at low heart rates (HRs) and at end-systole at high HRs. On the other hand, extracellular volume (ECV) measurements may be influenced by the cardiac phase. Therefore, we aimed to clarify the influence of the cardiac phase on the image quality and ECV values obtained using dual-layer spectral computed tomography (DLCT). Fifty-five patients (68.0±14.5 years; 26 men) with cardiac diseases who underwent retrospective electrocardiogram-gated myocardial CT delayed enhancement (CTDE) between February 2019 to April 2022 were enrolled. The ECVs at the right ventricle (RV) and left ventricle (LV) walls in the end-systolic and mid-diastolic phases were calculated using iodine-density measurements from CTDE spectral data. Iodine-density image quality was classified on a 4-point scale. ECV and image quality across cardiac phases were compared using the t-test and Wilcoxon signed-rank test, respectively. Inter- and intraobserver variability were evaluated using intraclass correlation coefficient (ICC) values. The ECV of the septal regions during mid-diastole was significantly higher than that during end-systole. Other regions showed similar ECV measurements in both groups (P=0.13-0.97), except for the LV anterior wall and LV posterior wall at the base-ventricular level. The image-quality score in end-systole was significantly higher than that in mid-diastole (systole vs. diastole: 3.6±0.5 vs. 3.2±0.7; P=0.0195). Intra- and interobserver variabilities for RV ECV measurements at the end-systolic phase were superior to those at the mid-diastolic phase, whereas the corresponding values for LV ECV measurements were similar. Septal ECV showed small but significant differences while other region ECV showed no difference during the cardiac cycle. RV ECV measurements in the end-systolic phase were more reproducible than those in the mid-diastolic phase.

Assessment of the Predictive Role of Ki-67 in Breast Cancer Patients' Responses to Neoadjuvant Chemotherapy.

Neoadjuvant chemotherapy (NAC) in breast cancer (BC) is being considered for a broader range of cases, including locally advanced tumors and situations where downstaging could reduce extensive surgery. Several trials have explored predictive markers of pathological complete response (pCR). The role of Ki-67 as a predictor of pCR has been demonstrated in studies. However, the cut-off remains vague, given the lack of standardization of measurement methods. The aim of our study was to evaluate the predictive value of Ki-67 in response to NAC and to identify the cut-off values that exhibit the strongest correlation with best response. This retrospective study included 187 patients who had undergone surgery following NAC for BC at the CHU Souss Massa of Agadir between January 2020 and January 2023. Logistic regression was used to assess the correlation between Ki-67 and patients' characteristics. Optimal Ki-67 cutoff was identified by receiver operating characteristic curve. Kaplan-Meier curves were used to assess disease-free survival (DFS), and survival comparisons were assessed with the log-rank test. The median age was 51.8±10.7 years and 51.4% of tumors were smaller than 5 cm. Node invasion was found in 55.4%. Luminal B subtype was found in 49.7%, followed by human epidermal growth factor receptor-2 (HER-2)-positive in 27.4%, triple-negative in 14.3% and Luminal A in 8.6%. pCR occurred in 40% of patients overall. Subgroup analysis revealed a significant association between pCR and tumor size (p<0.001), lymph node involvement (p<0.001), grade 2 (p<0.001), vascular invasion (p<0.001), and positive HER-2 status (p = 0.022). In statistical analysis, pathological responses were improved in patients with Ki-67 >35% (p<0.001). DFS was 98.8% at 12 months. No statistical difference was found in DFS according to Ki-67 values and pCR status. Our results indicate that Ki-67 is a predictive marker for response in the neoadjuvant setting in BC patients. Our study showed that a Ki-67 cut-off >35% predicts a better pCR rate in response to NAC. However, this cutoff value remains controversial due to the absence of a standard method of measurement, with inter- and intra-observer variability. It would be necessary to validate this cutoff in other studies.