BACKGROUND: There is growing interest in the development and application of standardized imaging criteria (SIC), to minimize variability and improve the reproducibility of image interpretation in head and neck squamous cell carcinoma (HNSCC).
METHODS: \"Squamous cell carcinoma\" AND \"standardized interpretation criteria\" OR \"radiographic response assessment\" were searched using PubMed and Google Scholar for articles published between 2009 and 2024, returning 56 publications. After abstract review, 18 were selected for further evaluation, and 6 different SICs (i.e., PERCIST, Porceddu, Hopkins, NI-RADS, modified Deauville, and Cuneo) were included in this review. Each SIC is evaluated in the context of 8 desired traits of a standardized reporting system.
RESULTS: Two SICs have societal endorsements (i.e., PERCIST, NI-RADS); four can be used in the evaluation of locoregional and systemic disease (i.e., PERCIST, Hopkins, NI-RADS, Cuneo), and four have specific categories for equivocal imaging results (i.e., Porceddu, NI-RADS, modified Deauville, and Cuneo). All demonstrated areas for future improvement in the context of the 8 desired traits.
CONCLUSIONS: Multiple SICs have been developed for and demonstrated value in HNSCC post-treatment imaging; however, these systems remain underutilized. Selecting an SIC with features that best match the needs of one\'s practice is expected to maximize the likelihood of successful implementation.

UNASSIGNED: A method for visualizing and analyzing the complete information contained in spectral CT scans using two-dimensional histograms (i.e. Material Attenuation Decomposition plots - MADplots) of the water-photoelectric attenuation versus water-scatter attenuation at the cohort (combination of multiple studies across patients), examination, series, slice, and organ/ROI levels is described.
UNASSIGNED: The appearance of a MADplot with several standard biological materials was predicted using ideal material properties available from NIST and the ICRU to generate a map for this non-spatial data space. Software tools were developed to generate MADplots as new DICOM series that facilitate spectral analysis. Illustrative examples were selected from an IRB-approved, retrospective cohort of Spectral Basis Images (SBIs) scanned using a pre-release, dual-layer detector spectral CT.
UNASSIGNED: By combining all of the voxels for contrast and non-contrast studies, the predicted appearance of the MADplot was confirmed. Locations of several kinds of tissue, the shape of the tissue distributions in normal lung, and the variations in the manner in which organ-specific MADplots change with pathology are demonstrated for the presence of fat in both the liver and pancreas highlighting the potential use for identifying pathologies on spectral CT images.
UNASSIGNED: The examples of MADplots shown at cohort (combined studies), examination, series, slice, organ, and ROI levels illustrate their potential utility in analyzing and displaying spectral CT data. Future studies are directed at developing MADplot based organ segmentation and the automated detection and display of organ based pathologies.

OBJECTIVE: Interpretation of dental radiographs is a difficult process, particularly for inexperienced students. This study introduced concept mapping for dental students to help in the radiographic interpretation of common jaw lesions. We aimed to analyze the efficacy of the concept map (CM) in radiographic interpretation, with a discussion of the diagnostic reasoning dilemma.
METHODS: This study included 39 dental students. After a 1-h class for CM guidance and based on three group discussions and one-on-one feedback, the students completed and submitted CMs for three jaw diseases (ameloblastoma, odontogenic keratocyst, and simple bone cyst). All participants underwent a pretest and posttest of knowledge and diagnosis; all students but one completed an open-ended questionnaire regarding the use of CMs.
RESULTS: Concept mapping effectively improved diagnostic accuracy. The participants\' posttest scores were better than their pretest scores in both knowledge and diagnostic tests. Most of the students attempted radiographic interpretation through analytic reasoning. The time required for the students to draw a CM varied from student to student from 3-5 h to 1-3 days.
CONCLUSIONS: This study shows that CMs can improve the radiographic diagnostic ability of dental students by providing a framework for analytic reasoning. Continuous research is warranted to improve the effectiveness of CM in oral radiographic interpretation in the dental student\'s class.

The main purpose of vital pulp therapy (VPT) is to preserve the integrity and function of the pulp. A wide variety of materials and techniques have been proposed to improve treatment outcomes, and among them, the utilization of lasers has gained significant attention. The application of lasers in different stages of VPT has witnessed remarkable growth in recent years, surpassing previous approaches.This study aimed to review the applications of lasers in different steps of VPT and evaluate associated clinical and radiographic outcomes. An electronic search using Scopus, MEDLINE, Web of Science and Google Scholar databases from 2000 to 2023 was carried out by two independent researchers. The focus was on human studies that examined the clinical and/or radiographic effects of different laser types in VPT. A total of 4243 studies were included in this narrative review article. Based on the compiled data, it can be concluded that although current literature suggests laser may be proposed as an adjunct modality for some procedural steps in VPT, more research with standardized methodologies and criteria is needed to obtain more reliable and conclusive results.

Metal artifact reduction (MAR) algorithms are commonly used in computed tomography (CT) scans where metal implants are involved. However, MAR algorithms also have the potential to create new artifacts in reconstructed images. We present a case of a screw pseudofracture due to MAR on CT.

Convolutional neural networks (CNNs) have produced state-of-the-art results in meningioma segmentation on magnetic resonance imaging (MRI). However, images obtained from different institutions, protocols, or scanners may show significant domain shift, leading to performance degradation and challenging model deployment in real clinical scenarios.
This research aims to investigate the realistic performance of a well-trained meningioma segmentation model when deployed across different health care centers and verify the methods to enhance its generalization.
This study was performed in four centers. A total of 606 patients with 606 MRIs were enrolled between January 2015 and December 2021. Manual segmentations, determined through consensus readings by neuroradiologists, were used as the ground truth mask. The model was previously trained using a standard supervised CNN called Deeplab V3+ and was deployed and tested separately in four health care centers. To determine the appropriate approach to mitigating the observed performance degradation, two methods were used: unsupervised domain adaptation and supervised retraining.
The trained model showed a state-of-the-art performance in tumor segmentation in two health care institutions, with a Dice ratio of 0.887 (SD 0.108, 95% CI 0.903-0.925) in center A and a Dice ratio of 0.874 (SD 0.800, 95% CI 0.854-0.894) in center B. Whereas in the other health care institutions, the performance declined, with Dice ratios of 0.631 (SD 0.157, 95% CI 0.556-0.707) in center C and 0.649 (SD 0.187, 95% CI 0.566-0.732) in center D, as they obtained the MRI using different scanning protocols. The unsupervised domain adaptation showed a significant improvement in performance scores, with Dice ratios of 0.842 (SD 0.073, 95% CI 0.820-0.864) in center C and 0.855 (SD 0.097, 95% CI 0.826-0.886) in center D. Nonetheless, it did not overperform the supervised retraining, which achieved Dice ratios of 0.899 (SD 0.026, 95% CI 0.889-0.906) in center C and 0.886 (SD 0.046, 95% CI 0.870-0.903) in center D.
Deploying the trained CNN model in different health care institutions may show significant performance degradation due to the domain shift of MRIs. Under this circumstance, the use of unsupervised domain adaptation or supervised retraining should be considered, taking into account the balance between clinical requirements, model performance, and the size of the available data.

UNASSIGNED: This study assessed the diagnostic accuracy of cone-beam computed tomography (CBCT) with a modified grayscale range for the detection of buccal cortical plate defects adjacent to dental implants.
UNASSIGNED: In this in vitro experimental study, titanium implants were inserted in 168 fresh bovine bone blocks with 1-1.5 mm of buccal cortical plate thickness. The blocks were randomly divided into four groups (n = 42). No defect was created in the control blocks. In the three experimental groups, cortical plate defects were randomly created in the cervical, middle, or apical third by a round bur with a 2-mm diameter (n = 42). All blocks underwent CBCT with and without change in the grayscale range. Two observers evaluated all images regarding the presence/absence of defects. Kappa test is used for the agreement of the observers. The diagnostic accuracy of the two modalities was compared by calculating the area under the receiver operating characteristic curve (AUC) (P ≤ 0.05). The sensitivity and specificity values were also compared.
UNASSIGNED: The AUC was not significantly different between the two modalities with and without altered grayscale range (0.754 vs. 0.762, respectively, P = 0.716). The diagnostic sensitivity of CBCT with and without change in the grayscale range was 51% and 52%, respectively, with a specificity of 100% for both. The diagnostic accuracy of CBCT with and without altered grayscale range had no significant difference for apical and middle third defects (P > 0.05) and was significantly higher than that for the cervical third defects (P < 0.05).
UNASSIGNED: Changing the grayscale range does not improve the diagnostic accuracy of CBCT for the detection of buccal cortical plate defects adjacent to dental implants.

The Medical Radiation Practice Board of Australia (MRPBA) minimum competency framework requires all Australian radiographers to identify significant pathology in radiological images and take appropriate action to alert these urgent findings and ensure patient safety. Despite professional bodies endorsing the provision of preliminary image evaluations (PIE) in written format, radiographer image interpretation often remains inconsistent, informal, or undocumented. The purpose of this narrative review was to assess the literature to determine if PIE in the form of written radiographer comments is of value to the Australian healthcare system. A structured search was completed using four health research databases: CINAHL, Medline, Scopus and Web of Science. Studies have suggested that there is a contextual need for commenting due to increased imaging service pressures, radiologist shortages and subsequent reporting delays. Radiographers appear well placed and willing to provide accurate initial input with evidence that this would be valued and appreciated within the multidisciplinary team. Radiographer commenting has also been shown to reduce diagnostic and communicative errors with the potential to improve patient management. Finally, it was shown that participation in image interpretation practices can enhance recruitment, retention and job satisfaction among radiographers. Therefore, the current literature supports implementation of radiographer commenting within the Australian healthcare system.

OBJECTIVE: To investigate whether CT texture analysis allows differentiation between adenocarcinomas, squamous cell carcinomas, carcinoids, small cell lung cancers and organizing pneumonia and between carcinomas and neuroendocrine tumors.
METHODS: This retrospective study included patients 133 patients (30 patients with organizing pneumonia, 30 patients with adenocarcinoma, 30 patients with squamous cell carcinoma, 23 patients with small cell lung cancer, 20 patients with carcinoid), who underwent CT-guided biopsy of the lung and had a corresponding histopathologic diagnosis. Pulmonary lesions were segmented in consensus by two radiologists with and without a threshold of -50HU in three dimensions. Groupwise comparisons were performed to assess for differences between all five above-listed entities and between carcinomas and neuroendocrine tumors.
RESULTS: Pairwise comparisons of the five entities revealed 53 statistically significant texture features when using no HU-threshold and 6 statistically significant features with a threshold of -50HU. The largest AUC (0.818 [95%CI 0.706-0.930]) was found for the feature wavelet-HHH_glszm_SmallAreaEmphasis for discrimination of carcinoid from the other entities when using no HU-threshold. In differentiating neuroendocrine tumors from carcinomas, 173 parameters proved statistically significant when using no HU threshold versus 52 parameters when using a -50HU-threshold. The largest AUC (0.810 [95%CI 0.728-0,893]) was found for the parameter original_glcm_Correlation for discrimination of neuroendocrine tumors from carcinomas when using no HU-threshold.
CONCLUSIONS: CT texture analysis revealed features that differed significantly between malignant pulmonary lesions and organizing pneumonia and between carcinomas and neuroendocrine tumors of the lung. Applying a HU-threshold for segmentation substantially influenced the results of texture analysis.

The health sector of South Africa is burdened by the shortage of radiologists leading to the under-reporting of radiographic images and ultimately mismanagement of patients. Previous studies have recommended training of radiographers in radiographic image interpretation in order to improve the reporting. There is paucity of information regarding the knowledge and training required by radiographers to interpret radiographic images. The purpose of this study was therefore to explore the knowledge and training required by diagnostic radiographers, according to radiologists, for the interpretation of radiographs.
A qualitative descriptive study employing criterion sampling to select qualified radiologists practicing in the eThekwini district of the KwaZulu Natal province, was conducted. One-on-one and in-depth, semi-structured interviews were used to collect data from three participants. The interviews were not carried out face to face as a result of the Covid 19 pandemic and the regulation of social distancing. This did not permit engagement with research communities. The data from the interviews were analysed using Tesch\'s eight steps for analysing qualitative data.
Findings revealed that radiologists supported the interpretation of radiographic images by radiographers in rural settings, and for the radiographer\'s scope of practice to be restructured to include the reporting of chest and the musculoskeletal system images. The themes that emerged from the analysis included knowledge, training, clinical competencies and medico-legal responsibilities required by radiographers in the interpretation of radiographic images.
Although the radiologists support the training of radiographers in the interpretation of radiographic images, radiologists think that the scope of practice should be limited to the interpretation of the chest and musculoskeletal systems in rural areas only.