The evolution of imaging actively shapes clinical management in the field. Ultrasonography (US), computed tomography angiography (CTA), and magnetic resonance angiography (MRA) stand out as the most extensively researched imaging modalities for ABR. Ongoing advancements include \"real-time\" angiography and three-dimensional (3D) surface imaging, and future prospects incorporate augmented or virtual reality (AR/VR) and artificial intelligence (AI). These technologies may further enhance perioperative efficiency, reduce donor-site morbidity, and improve surgical outcomes in ABR.

UNASSIGNED: To determine which combination of imaging modalities/contrast, radiomics models, and how many features provides the best diagnostic performance for the differentiation between low- and high-grade soft tissue sarcomas (STS) using a radiomics approach.
UNASSIGNED: MRI and CT from 39 patients with a histologically confirmed STS were prospectively analyzed. Images were evaluated both quantitatively by radiomics models and qualitatively by visual evaluation (used as reference) for grading (low-grade vs high-grade). In radiomics analysis, 120 radiomic features were extracted and contributed into three models: least absolute shrinkage and selection operator with logistic regression(LASSO-LR), recursive feature elimination and cross-validation (RFECV-SVC) and analysis of variance with SVC (ANOVA-SVC). Those were applied to different combinations of imaging modalities acquisition, with and without contrast medium administration, as well as selected number of features.
UNASSIGNED: Fat-saturated T2w (FS-T2w) MR images using RFECV-SVC radiomic models involving five features yielded the best results with mean sensitivity, specificity, and accuracy of 92% ± 10%, 78% ± 30%, and 89% ± 12%, respectively. The performance of radiomics was better than that of conventional analysis (67% accuracy) for STS grading. Combination of multiple contrast or imaging modalities did not increase the diagnostic performance.
UNASSIGNED: FS-T2w MR images alone with a five-feature radiomics analysis usingh REFCV-SVC model may be able to provide sufficient diagnositic performance compared to conventional visual evaluation with multiple MRI contrast and CT imaging.

The radiomic analysis of the tissue surrounding colorectal liver metastases (CRLM) enhances the prediction accuracy of pathology data and survival. We explored the variation of the textural features in the peritumoural tissue as the distance from CRLM increases. We considered patients with hypodense CRLMs >10 mm and high-quality computed tomography (CT). In the portal phase, we segmented (1) the tumour, (2) a series of concentric rims at a progressively increasing distance from CRLM (from one to ten millimetres), and (3) a cylinder of normal parenchyma (Liver-VOI). Sixty-three CRLMs in 51 patients were analysed. Median peritumoural HU values were similar to Liver-VOI, except for the first millimetre around the CRLM. Entropy progressively decreased (from 3.11 of CRLM to 2.54 of Liver-VOI), while uniformity increased (from 0.135 to 0.199, p < 0.001). At 10 mm from CRLM, entropy was similar to the Liver-VOI in 62% of cases and uniformity in 46%. In small CRLMs (≤30 mm) and responders to chemotherapy, normalisation of entropy and uniformity values occurred in a higher proportion of cases and at a shorter distance. The radiomic analysis of the parenchyma surrounding CRLMs unveiled a wide halo of progressively decreasing entropy and increasing uniformity despite a normal radiological aspect. Underlying pathology data should be investigated.

UNASSIGNED: Standardized consensus-based radiological reports for shoulder instability may improve clinical quality, reduce heterogeneity, and reduce workload. Therefore, the aim of this study was to determine important elements for the x-ray, magnetic resonance imaging (MRI) arthrography (MRA), and computed tomography (CT) report, the extent of variability, and important MRI views and settings.
UNASSIGNED: An expert panel of musculoskeletal radiologists and orthopedic surgeons was recruited in a three-round Delphi design. Important elements were identified for the x-ray, MRA, and CT report and important MRI views and setting. These were rated on a 0-9 Likert scale. High variability was defined as at least one score between 1-3 and 7-9. Consensus was reached when ≥80% scored an element 1-3 or 7-9.
UNASSIGNED: The expert panel consisted of 21 musculoskeletal radiologists and 15 orthopedic surgeons. The number of elements identified in the first round was seventeen for the x-ray report, 52 for MRA, 21 for CT, and 23 for the MRI protocol. The number of elements that reached consensus was five for x-ray, twenty for MRA, nine for CT, and two for the MRI protocol. High variability was observed in 76.5% (n = 13) x-ray elements, 85.0% (n = 45) MRA, 76.2% (n = 16) CT, and 85.7% (n = 18) MRI protocol.
UNASSIGNED: Substantial variability was observed in the scoring of important elements in the radiological for the evaluation of anterior shoulder instability, regardless of modality. Consensus was reached for five elements in the x-ray report, twenty in the MRA report, and nine in the CT report. Finally, consensus was reached on two elements regarding MRA views and settings.

UNASSIGNED: The commonly used methods for removing metal-induced beam hardening artifacts often rely on the use of high energy photons with either high tube voltage or high energy virtual monoenergetic images in dual-energy computed tomography (CT), the radiation dose was usually relatively high in order to generate adequate signals. This retrospective study is designed to evaluate the application of a metal artifact reduction (MAR) algorithm in reducing pedicle screw metal-caused beam hardening artifacts in post-surgery pediatric low radiation dose spine CT images.
UNASSIGNED: Seventy-seven children (3-15 years) who had undergone a low dose CT with 140 or 100 kV were enrolled. The radiation dose was 1.40 mGy for the 3-8 years old and 2.61 mGy for 9-15 years old children. There were 116 pedicle screws evaluated. The raw data were reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) at 50% strength, ASIR-V with MAR (AV-MAR), deep learning image reconstruction (DLIR) at high strength and DLIR with MAR (DL-MAR). The image quality concerning pedicle screws was evaluated objectively in terms of the length of beam-hardening artifact (LHA) and artifact index (AI), and subjectively using a 4-point scale (4 points: best, 3 points: acceptable).
UNASSIGNED: Both AV-MAR and DL-MAR significantly reduced metal-induced beam hardening artifacts with smaller LHA (15.76±10.12 mm, a reduction of 57.24% and 15.66±10.49 mm, a reduction of 57.40%, respectively), and AI value (62.50±33.51, a reduction of 64.65% and 61.03±32.61, a reduction of 65.01%, respectively) compared to ASIR-V and DLIR (all P<0.01), The subjective image quality scores concerning the screws were 3.37±0.49 and 3.47±0.50 with AV-MAR and DL-MAR, respectively, higher than the respective value of 1.73±0.44 and 1.76±0.43 without MAR (all P<0.01).
UNASSIGNED: MAR significantly reduces the low-density artifacts caused by metal screws in post-surgery pediatric low-dose spine CT images, across different tube voltages, radiation dose levels and reconstruction algorithms. Combining DL-MAR further improves the overall image quality under low radiation dose conditions.

BACKGROUND: Percutaneous Endoscopic Lumbar Discectomy (PELD) has emerged as routine treatment for lumbar disc herniation (LDH) due to its minimal invasiveness and quick recovery. However, PELD demands high precision from the surgeon, as the risk of intraoperative complications is substantial, including potential damage to the nerve root and dura, and a higher likelihood of recurrence post-surgery. Thus, preoperative planning utilizing CT and MRI imaging is essential.
METHODS: In this study, the clinical data of 140 patients treated with PELD for LDH from January 2021 to December 2023 were retrospectively analyzed. Patients were categorized into two groups based on whether CT and MRI registration (CMR) was employed for surgical planning: a CMR group (n=68) and a control group (n=72). Data collected included surgery time, hospital stay duration, and scores from the Visual Analog Scale (VAS) for low back and leg pain, as well as the Japanese Orthopaedic Association Lumbar Spine Score (JOA). Differences between the two groups were assessed using the Student\'s t-test.
RESULTS: No significant difference was found in hospital stay length between the groups (P=0.277). Surgery time was significantly shorter in the CMR group (P<0.001). Prior to surgery, no significant differences in VAS scores for leg and low back pain were observed between the groups (P=0.341 and P=0.131, respectively); however, at 2 months postoperatively, both scores were significantly lower in the CMR group (P<0.001 and P=0.002, respectively). Similarly, no difference in preoperative JOA scores was noted (P=0.750), but at 2 months postoperative, the CMR group exhibited significantly higher scores (P<0.001).
CONCLUSIONS: Compared with the traditional PELD, the preoperative use of CMR has shown to reduce surgery time, alleviate leg and low back pain, and increase the lumbar JOA score at 2 months after surgery, underscoring its efficacy in enhancing surgical outcomes.

Although kidney transplantation is the best therapeutic option for patients with chronic kidney disease, the immunosuppression required greatly increases susceptibility to infections that are responsible for high post-transplant mortality. Pulmonary tuberculosis (TB) represents a major cause of such infections, and its early diagnosis is therefore quite important. In view of that, we researched the manifestations of active pulmonary TB in kidney transplant recipients, through chest X-ray and computed tomography (CT), as well as determining the number of cases of active pulmonary TB occurring over a 3.5-year period at our institution. We identified four cases of active pulmonary TB in kidney transplant recipients. The CT scans provided information complementary to the chest X-ray findings in all four of those cases. We compared our CT findings with those reported in the literature. We analyzed our experience in conjunction with an extensive review of the literature that was nevertheless limited because few studies have been carried out in lowand middle-income countries, where the incidence of TB is higher.
Apesar de o transplante renal ser a melhor opção terapêutica para pacientes com doença renal crônica, a imunodepressão decorrente desse tratamento eleva muito a suscetibilidade desses pacientes a infecções, responsáveis por altas taxas de mortalidade pós-operatórias. A tuberculose (TB) pulmonar é uma significativa causa dessas infecções, sendo muito importante o seu diagnóstico precoce. Assim, nós pesquisamos as manifestações da TB pulmonar ativa nessa população de transplantados renais por meio de radiografias simples e tomografia computadorizada (TC) do tórax, também para estabelecer o número de casos de TB pulmonar ativa em nossa instituição após levantamento de 3,5 anos. Encontramos quatro casos de TB pulmonar ativa em pacientes transplantados renais. A TC forneceu informações adicionais em relação às radiografias de tórax em 100% dos casos analisados. Comparamos os nossos achados de TC com os relatados na literatura. Somamos a experiência obtida com extensa revisão da literatura, ainda limitada nessa questão, com poucos estudos realizados em países em desenvolvimento onde a incidência de TB é maior.

UNASSIGNED: To conduct a survey on the use of the term \"interstitial lung abnormalities\" in radiology reports in Brazil, propose an appropriate Portuguese-language translation for the term, and provide a brief review of the literature on the topic.
UNASSIGNED: A survey was sent via electronic message to various radiologists in Brazil, asking about their familiarity with the term, which translation of the term they use in Portuguese, and whether they use the criteria proposed by the Fleischner Society.
UNASSIGNED: A total of 163 responses were received, from all regions of Brazil. Although the vast majority (88%) of the respondents stated that they were familiar with the term \"interstitial lung abnormalities\", there was considerable variation regarding the equivalent term they used in Portuguese.
UNASSIGNED: We suggest that the term \"anormalidades pulmonares intersticiais\" be used in order to standardize radiology reports and disseminate knowledge of these findings in Brazil.
UNASSIGNED: Fazer um levantamento sobre o uso do termo interstitial lung abnormalities nos laudos radiológicos no Brasil, propor uma tradução para o termo e fazer uma breve revisão sobre o tema.
UNASSIGNED: Foi enviada uma pesquisa, por meio de mensagem eletrônica, para diversos radiologistas de todo o Brasil, questionando sobre a familiarização com o termo, qual tradução em português utilizam e se usam os critérios propostos pela diretriz da Sociedade Fleischner.
UNASSIGNED: Foram recebidas 163 respostas de todas as regiões do Brasil e a grande maioria dos radiologistas respondeu estar familiarizado com o termo interstitial lung abnormalities (88%), mas houve grande variação em relação ao termo utilizado como tradução para o português.
UNASSIGNED: Sugerimos a padronização do termo “anormalidades pulmonares intersticiais”, a fim de uniformizar os relatórios radiológicos e difundir esta entidade no País.

BACKGROUND: This study aimed to quantitatively reveal contributing factors to airway navigation failure during radial probe endobronchial ultrasound (R-EBUS) by using geometric analysis in a three-dimensional (3D) space and to investigate the clinical feasibility of prediction models for airway navigation failure.
METHODS: We retrospectively reviewed patients who underwent R-EBUS between January 2017 and December 2018. Geometric quantification was analyzed using in-house software built with open-source python libraries including the Vascular Modeling Toolkit ( http://www.vmtk.org ), simple insight toolkit ( https://sitk.org ), and sci-kit image ( https://scikit-image.org ). We used a machine learning-based approach to explore the utility of these significant factors.
RESULTS: Of the 491 patients who were eligible for analysis (mean age, 65 years +/- 11 [standard deviation]; 274 men), the target lesion was reached in 434 and was not reached in 57. Twenty-seven patients in the failure group were matched with 27 patients in the success group based on propensity scores. Bifurcation angle at the target branch, the least diameter of the last section, and the curvature of the last section are the most significant and stable factors for airway navigation failure. The support vector machine can predict airway navigation failure with an average area under the curve of 0.803.
CONCLUSIONS: Geometric analysis in 3D space revealed that a large bifurcation angle and a narrow and tortuous structure of the closest bronchus from the lesion are associated with airway navigation failure during R-EBUS. The models developed using quantitative computer tomography scan imaging show the potential to predict airway navigation failure.

UNASSIGNED: To construct and validate a computed tomography (CT) radiomics model for differentiating lung neuroendocrine neoplasm (LNEN) from lung adenocarcinoma (LADC) manifesting as a peripheral solid nodule (PSN) to aid in early clinical decision-making.
UNASSIGNED: A total of 445 patients with pathologically confirmed LNEN and LADC from June 2016 to July 2023 were retrospectively included from five medical centers. Those patients were split into the training set (n = 316; 158 LNEN) and external test set (n = 129; 43 LNEN), the former including the cross-validation (CV) training set and CV test set using ten-fold CV. The support vector machine (SVM) classifier was used to develop the semantic, radiomics and merged models. The diagnostic performances were evaluated by the area under the receiver operating characteristic curve (AUC) and compared by Delong test. Preoperative neuron-specific enolase (NSE) levels were collected as a clinical predictor.
UNASSIGNED: In the training set, the AUCs of the radiomics model (0.878 [95% CI: 0.836, 0.915]) and merged model (0.884 [95% CI: 0.844, 0.919]) significantly outperformed the semantic model (0.718 [95% CI: 0.663, 0.769], p both<.001). In the external test set, the AUCs of the radiomics model (0.787 [95% CI: 0.696, 0.871]), merged model (0.807 [95%CI: 0.720, 0.889]) and semantic model (0.729 [95% CI: 0.631, 0.811]) did not exhibit statistical differences. The radiomics model outperformed NSE in sensitivity in the training set (85.3% vs 20.0%; p <.001) and external test set (88.9% vs 40.7%; p = .002).
UNASSIGNED: The CT radiomics model could non-invasively, effectively and sensitively predict LNEN and LADC presenting as a PSN to assist in treatment strategy selection.