Search

Objectives: To determine, in patients with melanoma, the dependence of PET sensitivity on pulmonary metastasis size, and to determine patients who require further evaluation for definite staging.Methods: Of 183 melanoma patients who underwent (18)F-fluorodeoxyglucose PET/computed tomography (CT) for staging or follow-up between January 2008 and June 2011, 38 patients (18 women and 20 men; mean age 62.0 ± 14.7 years) with one or more pulmonary metastases visible on CT were included in the retrospective study. Each pulmonary metastasis was rated as positive or negative on PET, and lesion size (maximum transverse diameter) was assessed on CT. PET sensitivity was calculated according to the lesions' size, in 2-mm steps.Results: A total of 181 pulmonary metastases were analysed. PET sensitivity was 7.9 % for lesions of 4-5 mm; 33.3 % for lesions of 6-7 mm; 56.8 % for lesions of 8-9 mm; 63.6 % for lesions of 10-11 mm; 100 % for lesions of 12-14 mm; and 100 % for lesions of at least 15 mm. The differences in sensitivity between the size groups were significant (P < 0.001) CONCLUSIONS: With current state-of-the-art PET/CT technology, additional tests are necessary for definitive staging of melanoma patients who have one or more PET-negative lung nodules less than 12 mm in diameter on expiratory CT.Key Points: • PET cannot rule out malignancy in pulmonary nodules less than 12 mm on expiratory CT. • Melanoma patients with PET-negative pulmonary nodules less than 12 mm require additional tests. • Knowledge of these factors can help interpretation of PET and PET/CT findings. [ABSTRACT FROM AUTHOR]

Objective: This study assessed the feasibility of telecytological evaluation of samples from CT-guided lung biopsies using a dynamic telecytological system in which the microscope was operated by personnel from the radiology department at the site of the biopsy and a cytologist off-site diagnosed the biopsy sample.Materials and Methods: 45 imprint samples from CT-guided biopsies of lung lesions were reviewed by two cytologists using a telecytological microscope (Olympus BX51, Tokyo, Japan). The telecytological microscope was operated by one radiologist and one radiology technician. The cytological samples were classified by a cytologist into four categories: benign, malignant, atypical cells of undetermined significance, and non-diagnostic. The results were compared with those of a previous consensus reading of two independent cytologists (gold standard).Results: When the radiologist was operating the microscope, the diagnostic accuracy was 100% as both cytologists came to the correct diagnosis in all samples. When the technician operated the microscope, two diagnoses of cyotologist 1 differed from the gold standard. Thus, the accuracy for the technician was 95.56%.Conclusion: Telecytological evaluation of imprint samples from CT-guided lung biopsies is feasible because it can be performed with high diagnostic accuracy if personnel from the radiology department operate the microscope. [ABSTRACT FROM AUTHOR]

Objectives: To conduct an intrapatient comparison of ultra-low-dose computed tomography (ULDCT) and standard-of-care-dose CT (SDCT) of the chest in terms of the diagnostic accuracy of ULDCT and intrareader agreement in patients with post-COVID conditions., Methods: We prospectively included 153 consecutive patients with post-COVID-19 conditions. All participants received an SDCT and an additional ULDCT scan of the chest. SDCTs were performed with standard imaging parameters and ULDCTs at a fixed tube voltage of 100 kVp (with tin filtration), 50 ref. mAs (dose modulation active), and iterative reconstruction algorithm level 5 of 5. All CT scans were separately evaluated by four radiologists for the presence of lung changes and their consistency with post-COVID lung abnormalities. Radiation dose parameters and the sensitivity, specificity, and accuracy of ULDCT were calculated., Results: Of the 153 included patients (mean age 47.4 ± 15.3 years; 48.4% women), 45 (29.4%) showed post-COVID lung abnormalities. In those 45 patients, the most frequently detected CT patterns were ground-glass opacities (100.0%), reticulations (43.5%), and parenchymal bands (37.0%). The accuracy, sensitivity, and specificity of ULDCT compared to SDCT for the detection of post-COVID lung abnormalities were 92.6, 87.2, and 94.9%, respectively. The median total dose length product (DLP) of ULDCTs was less than one-tenth of the radiation dose of our SDCTs (12.6 mGy*cm [9.9; 15.5] vs. 132.1 mGy*cm [103.9; 160.2]; p < 0.001)., Conclusion: ULDCT of the chest offers high accuracy in the detection of post-COVID lung abnormalities compared to an SDCT scan at less than one-tenth the radiation dose, corresponding to only twice the dose of a standard chest radiograph in two views., Clinical Relevance Statement: Ultra-low-dose CT of the chest may provide a favorable, radiation-saving alternative to standard-dose CT in the long-term follow-up of the large patient cohort of post-COVID-19 patients., (© 2024. The Author(s).)

Objective: Distinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities (ILA) on CT can be challenging if clinical information is limited. This study aimed to evaluate the diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from ILA., Methods: This multi-reader, multi-case study included 60 age- and sex-matched subjects with chest CT scans. There were 40 cases of ILA (20 fibrotic and 20 non-fibrotic) and 20 cases of post-COVID-19 residual abnormalities. Fifteen radiologists from multiple nations with varying levels of experience independently rated suspicion scores on a 5-point scale to distinguish post-COVID-19 residual abnormalities from fibrotic ILA or non-fibrotic ILA. Interobserver agreement was assessed using the weighted κ value, and the scores of individual readers were compared with the consensus of all readers. Receiver operating characteristic curve analysis was conducted to evaluate the diagnostic performance of suspicion scores for distinguishing post-COVID-19 residual abnormalities from ILA and for differentiating post-COVID-19 residual abnormalities from both fibrotic and non-fibrotic ILA., Results: Radiologists' diagnostic performance for distinguishing post-COVID-19 residual abnormalities from ILA was good (area under the receiver operating characteristic curve (AUC) range, 0.67-0.92; median AUC, 0.85) with moderate agreement (κ = 0.56). The diagnostic performance for distinguishing post-COVID-19 residual abnormalities from non-fibrotic ILA was lower than that from fibrotic ILA (median AUC = 0.89 vs. AUC = 0.80, p = 0.003)., Conclusion: Radiologists demonstrated good diagnostic performance and moderate agreement in distinguishing post-COVID-19 residual abnormalities from ILA, but careful attention is needed to avoid misdiagnosing them as non-fibrotic ILA., Key Points: Question How good are radiologists at differentiating interstitial lung abnormalities (ILA) from changes related to COVID-19 infection? Findings Radiologists had a median AUC of 0.85 in distinguishing post-COVID-19 abnormalities from ILA with moderate agreement (κ = 0.56). Clinical relevance Radiologists showed good diagnostic performance and moderate agreement in distinguishing post-COVID-19 residual abnormalities from ILA; nonetheless, caution is needed in distinguishing residual abnormalities from non-fibrotic ILA., (© 2024. The Author(s).)

Fibrotic lung diseases (FLDs) represent a subgroup of interstitial lung diseases (ILDs), which can progress over time and carry a poor prognosis. Imaging has increased diagnostic discrimination in the evaluation of FLDs. International guidelines have stated the role of radiologists in the diagnosis and management of FLDs, in the context of the interdisciplinary discussion. Chest computed tomography (CT) with high-resolution technique is recommended to correctly recognise signs, patterns, and distribution of individual FLDs. Radiologists may be the first to recognise the presence of previously unknown interstitial lung abnormalities (ILAs) in various settings. A systematic approach to CT images may lead to a non-invasive diagnosis of FLDs. Careful comparison of serial CT exams is crucial in determining either disease progression or supervening complications. This 'Essentials' aims to provide radiologists a concise and practical approach to FLDs, focusing on CT technical requirements, pattern recognition, and assessment of disease progression and complications. Hot topics such as ILAs and progressive pulmonary fibrosis (PPF) are also discussed. KEY POINTS: Chest CT with high-resolution technique is the recommended imaging modality to diagnose pulmonary fibrosis. CT pattern recognition is central for an accurate diagnosis of fibrotic lung diseases (FLDs) by interdisciplinary discussion. Radiologists are to evaluate disease behaviour by accurately comparing serial CT scans., (© 2024. The Author(s).)

This statement from the European Society of Thoracic imaging (ESTI) explains and summarises the essentials for understanding and implementing Artificial intelligence (AI) in clinical practice in thoracic radiology departments. This document discusses the current AI scientific evidence in thoracic imaging, its potential clinical utility, implementation and costs, training requirements and validation, its' effect on the training of new radiologists, post-implementation issues, and medico-legal and ethical issues. All these issues have to be addressed and overcome, for AI to become implemented clinically in thoracic radiology. KEY POINTS: • Assessing the datasets used for training and validation of the AI system is essential. • A departmental strategy and business plan which includes continuing quality assurance of AI system and a sustainable financial plan is important for successful implementation. • Awareness of the negative effect on training of new radiologists is vital., (© 2023. The Author(s).)

Objectives: To assess the reproducibility of radiomics features extracted from the developing lung in repeated in-vivo fetal MRI acquisitions., Methods: In-vivo MRI (1.5 Tesla) scans of 30 fetuses, each including two axial and one coronal T2-weighted sequences of the whole lung with all other acquisition parameters kept constant, were retrospectively identified. Manual segmentation of the lungs was performed using ITK-Snap. One hundred radiomics features were extracted from fetal lung MRI data using Pyradiomics, resulting in 90 datasets. Intra-class correlation coefficients (ICC) of radiomics features were calculated between baseline and repeat axial acquisitions and between baseline axial and coronal acquisitions., Results: MRI data of 30 fetuses (12 [40%] females, 18 [60%] males) at a median gestational age of 24 + 5 gestational weeks plus days (GW) (interquartile range [IQR] 3 + 3 GW, range 21 + 1 to 32 + 6 GW) were included. Median ICC of radiomics features between baseline and repeat axial MR acquisitions was 0.92 (IQR 0.13, range 0.33 to 1), with 60 features exhibiting excellent (ICC > 0.9), 27 good (> 0.75-0.9), twelve moderate (0.5-0.75), and one poor (ICC < 0.5) reproducibility. Median ICC of radiomics features between baseline axial and coronal MR acquisitions was 0.79 (IQR 0.15, range 0.2 to 1), with 20 features exhibiting excellent, 47 good, 29 moderate, and four poor reproducibility., Conclusion: Standardized in-vivo fetal MRI allows reproducible extraction of lung radiomics features. In the future, radiomics analysis may improve diagnostic and prognostic yield of fetal MRI in normal and pathologic lung development., Key Points: • Non-invasive fetal MRI acquired using a standardized protocol allows reproducible extraction of radiomics features from the developing lung for objective tissue characterization. • Alteration of imaging plane between fetal MRI acquisitions has a negative impact on lung radiomics feature reproducibility. • Fetal MRI radiomics features reflecting the microstructure and shape of the fetal lung could complement observed-to-expected lung volume in the prediction of postnatal outcome and optimal treatment of fetuses with abnormal lung development in the future., (© 2023. The Author(s).)

Objectives: To identify and evaluate predictive lung imaging markers and their pathways of change during progression of idiopathic pulmonary fibrosis (IPF) from sequential data of an IPF cohort. To test if these imaging markers predict outcome., Methods: We studied radiological disease progression in 76 patients with IPF, including overall 190 computed tomography (CT) examinations of the chest. An algorithm identified candidates for imaging patterns marking progression by computationally clustering visual CT features. A classification algorithm selected clusters associated with radiological disease progression by testing their value for recognizing the temporal sequence of examinations. This resulted in radiological disease progression signatures, and pathways of lung tissue change accompanying progression observed across the cohort. Finally, we tested if the dynamics of marker patterns predict outcome, and performed an external validation study on a cohort from a different center., Results: Progression marker patterns were identified and exhibited high stability in a repeatability experiment with 20 random sub-cohorts of the overall cohort. The 4 top-ranked progression markers were consistently selected as most informative for progression across all random sub-cohorts. After spatial image registration, local tracking of lung pattern transitions revealed a network of tissue transition pathways from healthy to a sequence of disease tissues. The progression markers were predictive for outcome, and the model achieved comparable results on a replication cohort., Conclusions: Unsupervised learning can identify radiological disease progression markers that predict outcome. Local tracking of pattern transitions reveals pathways of radiological disease progression from healthy lung tissue through a sequence of diseased tissue types., Key Points: • Unsupervised learning can identify radiological disease progression markers that predict outcome in patients with idiopathic pulmonary fibrosis. • Local tracking of pattern transitions reveals pathways of radiological disease progression from healthy lung tissue through a sequence of diseased tissue types. • The progression markers achieved comparable results on a replication cohort., (© 2022. The Author(s).)

Objectives: Content-based image retrieval systems (CBIRS) are a new and potentially impactful tool for radiological reporting, but their clinical evaluation is largely missing. This study aimed at assessing the effect of CBIRS on the interpretation of chest CT scans from patients with suspected diffuse parenchymal lung disease (DPLD)., Materials and Methods: A total of 108 retrospectively included chest CT scans with 22 unique, clinically and/or histopathologically verified diagnoses were read by eight radiologists (four residents, four attending, median years reading chest CT scans 2.1± 0.7 and 12 ± 1.8, respectively). The radiologists read and provided the suspected diagnosis at a certified radiological workstation to simulate clinical routine. Half of the readings were done without CBIRS and half with the additional support of the CBIRS. The CBIRS retrieved the most likely of 19 lung-specific patterns from a large database of 6542 thin-section CT scans and provided relevant information (e.g., a list of potential differential diagnoses)., Results: Reading time decreased by 31.3% (p < 0.001) despite the radiologists searching for additional information more frequently when the CBIRS was available (154 [72%] vs. 95 [43%], p < 0.001). There was a trend towards higher overall diagnostic accuracy (42.2% vs 34.7%, p = 0.083) when the CBIRS was available., Conclusion: The use of the CBIRS had a beneficial impact on the reading time of chest CT scans in cases with DPLD. In addition, both resident and attending radiologists were more likely to consult informational resources if they had access to the CBIRS. Further studies are needed to confirm the observed trend towards increased diagnostic accuracy with the use of a CBIRS in practice., Key Points: • A content-based image retrieval system for supporting the diagnostic process of reading chest CT scans can decrease reading time by 31.3% (p < 0.001). • The decrease in reading time was present despite frequent usage of the content-based image retrieval system. • Additionally, a trend towards higher diagnostic accuracy was observed when using the content-based image retrieval system (42.2% vs 34.7%, p = 0.083)., (© 2022. The Author(s).)

Objectives: Acute respiratory distress syndrome (ARDS) constitutes a major factor determining the clinical outcome in polytraumatized patients. Early prediction of ARDS is crucial for timely supportive therapy to reduce morbidity and mortality. The objective of this study was to develop and test a machine learning-based method for the early prediction of ARDS derived from the first computed tomography scan of polytraumatized patients after admission to the hospital., Materials and Methods: One hundred twenty-three patients (86 male and 37 female, age 41.2 ± 16.4) with an injury severity score (ISS) of 16 or higher (31.9 ± 10.9) were prospectively included and received a CT scan within 1 h after the accident. The lungs, including air pockets and pleural effusions, were automatically segmented using a deep learning-based algorithm. Subsequently, we extracted radiomics features from within the lung and trained an ensemble of gradient boosted trees (GBT) to predict future ARDS., Results: Cross-validated ARDS prediction resulted in an area under the curve (AUC) of 0.79 for the radiomics score compared to 0.66 for ISS, and 0.68 for the abbreviated injury score of the thorax (AIS-thorax). Prediction using the radiomics score yielded an f1-score of 0.70 compared to 0.53 for ISS and 0.57 for AIS-thorax. The radiomics score achieved a sensitivity and specificity of 0.80 and 0.76., Conclusions: This study proposes a radiomics-based algorithm for the prediction of ARDS in polytraumatized patients at the time of admission to hospital with an accuracy that competes and surpasses conventional scores despite the heterogeneous, and therefore more realistic, scanning protocols., Key Points: • Early prediction of acute respiratory distress syndrome in polytraumatized patients is possible, even when using heterogenous data. • Radiomics-based prediction resulted in an area under the curve of 0.79 compared to 0.66 for the injury severity score, and 0.68 for the abbreviated injury score of the thorax. • Highlighting the most relevant lung regions for prediction facilitates the understanding of machine learning-based prediction., (© 2021. The Author(s).)

This document from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI) aims to present the main imaging features, and the role of CT scan in the early diagnosis of COVID-19, describing, in particular, the typical findings which make it possible to identify the disease and distinguish it from bacterial causes of infection, and to define which category of patients may benefit from CT imaging. The precautions that must be taken when performing scans to protect radiologists and technologists from infection will be described. The organisational measures that can be taken within radiology departments in order to cope with the influx of patients, while continuing to manage other emergency and time-sensitive activity (e.g. oncology, other infectious diseases etc.), will be discussed. KEY POINTS: • Bilateral ground glass opacities are typical CT manifestations of COVID-19. • Crazy paving and organising pneumonia pattern are seen at a later stage. • Extensive consolidation is associated with a poor prognosis.

Objectives: While magnetic resonance imaging (MRI) is considered a helpful diagnostic tool in breast imaging, discussions are ongoing about appropriate protocols and indications. The European Society of Breast Imaging (EUSOBI) launched a survey to evaluate the utilisation of breast MRI in clinical practice., Methods: An online survey reviewed by the EUSOBI board and committees was distributed amongst members. The questions encompassed: training and experience; annual breast MRI and MRI-guided-intervention workload; examination protocols; indications; reporting habits and preferences. Data were summarised and subgroups compared using χ 2 test., Results: Of 647 EUSOBI members, 177 (27.4%) answered the survey. The majority were radiologists (90.5%), half of them based in academic centres (51.9%). Common indications for MRI included cancer staging, treatment monitoring, high-risk screening and problem-solving, and differed significantly between countries (p≤0.03). Structured reporting and BI-RADS were mostly used. Breast radiologists with ≤10 years of experience preferred inclusion of additional techniques, such as T2/STIR (p=0.03) and DWI (p=0.08) in the scan protocol. MRI-guided interventions were performed by a minority of participants (35.4%)., Conclusions: The utilisation of breast MRI in clinical practice is generally in line with international recommendations. There are substantial differences between countries. MRI-guided interventions and functional MRI parameters are not widely available., Key Points: • MRI is commonly used for the detection and characterisation of breast lesions. • Clinical practice standards are generally in line with current recommendations. • Standardised criteria and diagnostic categories (mainly BI-RADS) are widely adopted. • Younger radiologists value additional techniques, such as T2/STIR and DWI. • MRI-guided breast biopsy is not widely available.

Objective: To assess a radiologist's detection rate of rib fractures in trauma CT when reading curved planar reformats (CPRs) of the ribs compared to reading standard MPRs., Methods: Two hundred and twenty trauma CTs (146 males, 74 females) were retrospectively subjected to a software algorithm to generate CPRs of the ribs. Patients were split into two equal groups. Sixteen patients were excluded due to insufficient segmentation, leaving 107 patients in group A and 97 patients in group B. Two radiologists independently evaluated group A using CPRs and group B using standard MPRs. Two different radiologists reviewed both groups with the inverse methods setting. Results were compared to a standard of reference created by two senior radiologists., Results: The reference standard identified 361 rib fractures in 61 patients. Reading CPRs showed a significantly higher overall sensitivity (P < 0.001) for fracture detection than reading standard MPRs, with 80.9% (584/722) and 71.5% (516/722), respectively. Mean reading time was significantly shorter for CPRs (31.3 s) compared to standard MPRs (60.7 s; P < 0.001)., Conclusion: Using CPRs for the detection of rib fractures accelerates the reading of trauma patient chest CTs, while offering an increased overall sensitivity compared to conventional standard MPRs., Key Points: • In major blunt trauma, rib fractures are diagnosed with Computed Tomography. • Image processing can unfold all ribs into a single plane. • Unfolded ribs can be read twice as fast as axial images. • Unfolding the ribs allows a more accurate diagnosis of rib fractures.

Purpose: The aim of this study was to survey the current CT protocols used by members of the European Society of Thoracic Imaging (ESTI) to evaluate patients with interstitial lung diseases (ILD)., Methods: A questionnaire was e-mailed to 173 ESTI members. The survey focussed on CT acquisition and reconstruction techniques. In particular, questions referred to the use of discontinuous HRCT or volume CT protocols, the acquisition of additional acquisitions in expiration or in the prone position, and methods of radiation dose reduction and on reconstruction algorithms., Results: The overall response rate was 37 %. Eighty-five percent of the respondents used either volume CT alone or in combination with discontinuous HRCT. Forty-five percent of the respondents adapt their CT protocols to the patient's weight and/or age. Expiratory CT or CT in the prone position was performed by 58 % and 59 % of the respondents, respectively. The number of reconstructed series ranged from two to eight., Conclusion: Our survey showed that radiologists with a special interest and experience in chest radiology use a variety of CT protocols for the evaluation of ILD. There is a clear preference for volumetric scans and a strong tendency to use the 3D information., Key Points: • Experienced thoracic radiologists use various CT protocols for evaluating interstitial lung diseases. • Most workers prefer volumetric CT acquisitions, making use of the 3D information • More attention to reducing the radiation dose appears to be needed.