Effective growth hormone replacement with once-weekly somapacitan in Japanese children with growth hormone deficiency: Results from REAL4, a phase 3 clinical trial.

OBJECTIVE: Somapacitan is a long-acting growth hormone (GH) derivative developed for the treatment of GH deficiency (GHD). This study evaluates the efficacy and tolerability of somapacitan in Japanese children with GHD after 104 weeks of treatment and after switch from daily GH. DESIGN: Subanalysis on Japanese patients from a randomised, open-labelled, controlled parallel-group phase 3 trial (REAL4, NCT03811535). PATIENTS AND MEASUREMENTS: Thirty treatment-naïve patients were randomised 2:1 to somapacitan (0.16 mg/kg/week) or daily GH (0.034 mg/kg/day) up to Week 52, after which all patients received somapacitan. Height velocity (HV; cm/year) at Weeks 52 and 104 were the primary measurements. Additional assessments included HV SD score (SDS), height SDS, bone age, insulin-like growth factor-I (IGF-I) SDS, and observer-reported outcomes. RESULTS: At Week 52, observed mean HV was similar between treatment groups (10.3 vs. 9.8 cm/year for somapacitan and daily GH, respectively). Similar HVs between groups were also observed at Week 104: 7.4 cm/year after continuous somapacitan treatment (soma/soma) and 7.9 cm/year after 1-year somapacitan treatment following switch from daily GH (switch). Other height-related endpoints supported continuous growth. IGF-I SDS increased in both groups with mean IGF-I SDS within -2 and +2 during the study. Somapacitan was well tolerated, one mild injection site reaction was reported, with no reports of injection site pain. Patient preference questionnaires showed that most patients and their caregivers (90.9%) who switched treatment at Week 52 preferred once-weekly somapacitan over daily GH treatment. CONCLUSIONS: Somapacitan showed sustained efficacy in Japanese children with GHD over 104 weeks and for 52 weeks after switching from daily GH. Somapacitan was well tolerated and preferred over daily GH.

Detection of Post-COVID-19 Lung Abnormalities: Photon-counting CT versus Same-Day Energy-integrating Detector CT.

Background Photon-counting detector (PCD) CT enables ultra-high-resolution lung imaging and may shed light on morphologic correlates of persistent symptoms after COVID-19. Purpose To compare PCD CT with energy-integrating detector (EID) CT for noninvasive assessment of post-COVID-19 lung abnormalities. Materials and Methods For this prospective study, adult participants with one or more COVID-19-related persisting symptoms (resting or exertional dyspnea, cough, fatigue) underwent same-day EID and PCD CT between April 2022 and June 2022. The 1.0-mm EID CT images and, subsequently, 1.0-, 0.4-, and 0.2-mm PCD CT images were reviewed for the presence of lung abnormalities. Subjective and objective EID and PCD CT image quality were evaluated using a five-point Likert scale (-2 to 2) and lung signal-to-noise ratios (SNRs). Results Twenty participants (mean age, 54 years ± 16 [SD]; 10 men) were included. EID CT showed post-COVID-19 lung abnormalities in 15 of 20 (75%) participants, with a median involvement of 10% of lung volume [IQR, 0%-45%] and 3.5 lobes [IQR, 0-5]. Ground-glass opacities and linear bands (10 of 20 participants [50%] for both) were the most frequent findings at EID CT. PCD CT revealed additional lung abnormalities in 10 of 20 (50%) participants, with the most common being bronchiectasis (10 of 20 [50%]). Subjective image quality was improved for 1.0-mm PCD versus 1.0-mm EID CT images (median, 1; IQR, 1-2; P < .001) and 0.4-mm versus 1.0-mm PCD CT images (median, 1; IQR, 1-1; P < .001) but not for 0.4-mm versus 0.2-mm PCD CT images (median, 0; IQR, 0-0.5; P = .26). PCD CT delivered higher lung SNR versus EID CT for 1.0-mm images (mean difference, 0.53 ± 0.96; P = .03) but lower SNR for 0.4-mm versus 1.0-mm images and 0.2-mm vs 0.4-mm images (-1.52 ± 0.68 [P < .001] and -1.15 ± 0.43 [P < .001], respectively). Conclusion Photon-counting detector CT outperformed energy-integrating detector CT in the visualization of subtle post-COVID-19 lung abnormalities and image quality. © RSNA, 2023 Supplemental material is available for this article.

Unsupervised machine learning identifies predictive progression markers of IPF.

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.

Impact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease.

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).

Ultrahigh-Resolution Photon-Counting Detector CT of the Lungs: Association of Reconstruction Kernel and Slice Thickness With Image Quality.

BACKGROUND. Prior work has shown improved image quality for photon-counting detector (PCD) CT of the lungs compared with energy-integrating detector CT. A paucity of the literature has compared PCD CT of the lungs using different reconstruction parameters. OBJECTIVE. The purpose of this study is to the compare the image quality of ultra-high-resolution (UHR) PCD CT image sets of the lungs that were reconstructed using different kernels and slice thicknesses. METHODS. This retrospective study included 29 patients (17 women and 12 men; median age, 56 years) who underwent noncontrast chest CT from February 15, 2022, to March 15, 2022, by use of a commercially available PCD CT scanner. All acquisitions used UHR mode (1024 × 1024 matrix). Nine image sets were reconstructed for all combinations of three sharp kernels (BI56, BI60, and BI64) and three slice thicknesses (0.2, 0.4, and 1.0 mm). Three radiologists independently reviewed reconstructions for measures of visualization of pulmonary anatomic structures and pathologies; reader assessments were pooled. Reconstructions were compared with the clinical reference reconstruction (obtained using the BI64 kernel and a 1.0-mm slice thickness [BI641.0-mm]). RESULTS. The median difference in the number of bronchial divisions identified versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.5), BI600.4-mm (0.3), BI640.2-mm (0.5), and BI600.2-mm (0.2) (all p < .05). The median bronchial wall sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3) and BI640.2-mm (0.3) and was lower for BI561.0-mm (-0.7) and BI560.4-mm (-0.3) (all p < .05). Median pulmonary fissure sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3), BI600.4-mm (0.3), BI560.4-mm (0.5), BI640.2-mm (0.5), BI600.2-mm (0.5), and BI560.2-mm (0.3) (all p < .05). Median pulmonary vessel sharpness versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3), BI600.4-mm (-0.3), BI560.4-mm (-0.7), BI640.2-mm (-0.7), BI600.2-mm (-0.7), and BI560.2-mm (-0.7). Median lung nodule conspicuity versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3) and BI560.4-mm (-0.3) (both p < .05). Median conspicuity of all other pathologies versus the clinical reference reconstruction was lower for reconstructions with BI561.0 mm (-0.3), BI560.4-mm (-0.3), BI640.2-mm (-0.3), BI600.2-mm (-0.3), and BI560.2-mm (-0.3). Other comparisons among reconstructions were not significant (all p > .05). CONCLUSION. Only the reconstruction using BI640.4-mm yielded improved bronchial division identification and bronchial wall and pulmonary fissure sharpness without a loss in pulmonary vessel sharpness or conspicuity of nodules or other pathologies. CLINICAL IMPACT. The findings of this study may guide protocol optimization for UHR PCD CT of the lungs.

Autologous replacement of the head of the radius-proximal fibula versus second metatarsal base: an anatomic feasibility study.

INTRODUCTION: This study investigated the anatomic feasibility of a new surgical therapy option for radial head arthrosis using an autologous vascularized bone graft of the second metatarsal and proximal fibula to recreate the proximal radiohumeral joint. MATERIALS AND METHODS: Upper and lower extremities of eleven body donors were evaluated using CT prior to anatomic dissection. Several distinct anatomic parameters were measured on the ipsi- and contralateral radial and fibular head and the second metatarsal base: bone diameter, articular surface diameter, head height, metaphyseal (neck) diameter, articular surface radius, total articular surface area, and angulation of the articular surfaces (facet). Each dissection phase was photographed in a standardized fashion and all measurements were repeated by direct caliper-measurements. RESULTS: When comparing the proximal radius and fibula to search for anatomic similarities, similar values were found in the maximum articular surface diameter and minimum and maximum measures of the neck diameter. Comparing the proximal radius and the second metatarsal, statistically similar values were found in the maximum neck diameter performing direct measurements and CT evaluation, the maximum head diameter in CT evaluation and the articular facet angulation. CONCLUSIONS: Neither the proximal fibula nor the base of the second metatarsal are ideal bone grafts for replacement of the head of the radius. The base of the second metatarsal might be a bit more suitable as a potential donor since the angulation of the proximal articular facet is similar to that of the radius. LEVEL OF EVIDENCE: Level IV, anatomic study.

Variability of computed tomography radiomics features of fibrosing interstitial lung disease: A test-retest study.

OBJECTIVES: To investigate the intra- and inter-scanner repeatability and reproducibility of CT radiomics features (RF) of fibrosing interstitial lung disease (fILD). METHODS: For this prospective, IRB-approved test-retest study, CT data of sixty fILD patients were acquired. Group A (n = 30) underwent one repeated CT scan on a single scanner. Group B (n = 30) was scanned using two different CT scanners. All CT data were reconstructed using different reconstruction kernels (soft, intermediate, sharp) and slice thicknesses (one and three millimeters), resulting in twelve datasets per patient. Following ROI placement in fibrotic lung tissue, 86 RF were extracted. Intra- and inter-scanner RF repeatability and reproducibility were assessed by calculating intraclass correlation coefficients (ICCs) for corresponding kernels and slice thicknesses, and between lung-specific and non-lung-specific reconstruction parameters. Furthermore, test-retest lung volumes were compared. RESULTS: Test-retest demonstrated a majority of RF is highly repeatable for all reconstruction parameter combinations. Intra-scanner reproducibility was negatively affected by reconstruction kernel changes, and further reduced by slice thickness alterations. Inter-scanner reproducibility was highly variable, reconstruction parameter-specific, and greatest if either soft kernels and three-millimeter slice thickness, or lung-specific reconstruction parameters were used for both scans. Test-retest lung volumes showed no significant difference. CONCLUSION: CT RF of fILD are highly repeatable for constant reconstruction parameters in a single scanner. Intra- and inter-scanner reproducibility are severely impacted by alterations in slice thickness more than reconstruction kernel, and are reconstruction parameter-specific. These findings may facilitate CT data and RF selection and assessment in future fILD radiomics studies collecting data across scanners.

[Chest radiography findings in diffuse parenchymal lung diseases]. / Röntgenbefunde bei diffusen parenchymatösen Lungenerkrankungen.

CLINICAL ISSUE: Diffuse parenchymal lung diseases include a heterogeneous group of diseases of the lung parenchyma, the alveolar spaces, the vessels and the airways, which can be triggered by various pathomechanisms, such as inflammation and fibrotic changes. Since the therapeutic approaches and prognoses differ significantly between the diseases, the correct diagnosis is of fundamental importance. In routine clinical practice, next to the patients' history, the clinical presentation, the laboratory findings and the bronchoscopy, imaging plays a central role in establishing a diagnosis. PRACTICAL RECOMMENDATIONS: The diagnosis of diffuse parenchymal lung diseases is an enormous challenge for clinicians, radiologists as well as pathologists and should therefore preferably be carried out in a multidisciplinary setting. Since patients often present with unspecific, respiratory symptoms, chest radiographs are the first imaging method used. Many patterns of diffuse parenchymal lung diseases (e.g., ground-glass opacities and consolidations), their distribution (e.g., cranial-caudal) and the presence of additional findings (e.g., mediastinal lymphadenopathy) are often already detectable on chest X­rays. However, the imaging reference standard and thus, an integral part of the assessment of diffuse parenchymal lung disease, is the chest HR-CT. In some cases, the pattern of the HR-CT is pathognomonic, in others it is unspecific for a disease, so that further diagnostic steps are necessary.

The intercondylar fossa-A narrative review.

The intercondylar fossa ("intercondylar notch," IN) is a groove at the distal end of the femur, housing important stabilizing structures: cruciate ligaments and meniscofemoral ligaments. As the risk for injury to these structures correlates with changes to the IN, exact knowledge of its morphology, possible physiological and pathological changes and different approaches for evaluating it are important. The divergent ways of assessing the IN and the corresponding measurement methods have led to various descriptions of its possible shapes. Ridges at the medial and lateral wall are considered clinically important because they can help with orientation during arthroscopy, whereas ridges at the osteochondral border could affect the risk of ligament injury. Changes related to aging and sex differences have been documented, further emphasizing the importance of individual assessment of the knee joint. Overall, it is of the utmost importance to remember the interactions between the osseous housing and the structures within.

Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma.

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.

Reliability of the MOCART (Magnetic Resonance Observation of Cartilage Repair Tissue) 2.0 knee score for different cartilage repair techniques-a retrospective observational study.

OBJECTIVES: To evaluate the reliability of the MOCART 2.0 knee score in the radiological assessment of repair tissue after different cartilage repair procedures. METHODS: A total of 114 patients (34 females) who underwent cartilage repair of a femoral cartilage lesion with at least one postoperative MRI examination were selected, and one random postoperative MRI examination was retrospectively included. Mean age was 32.5 ± 9.6 years at time of surgery. Overall, 66 chondral and 48 osteochondral lesions were included in the study. Forty-eight patients were treated with autologous chondrocyte implantation (ACI), 27 via osteochondral autologous transplantation, five using an osteochondral scaffold, and 34 underwent microfracture (MFX). The original MOCART and MOCART 2.0 knee scores were assessed by two independent readers. After a minimum 4-week interval, both readers performed a second reading of both scores. Inter- and intrarater reliabilities were assessed using intraclass correlation coefficients (ICCs). RESULTS: The MOCART 2.0 knee score showed higher interrater reliability than the original MOCART score with an ICC of 0.875 versus 0.759, ranging from 0.863 in the MFX group to 0.878 in the ACI group. Intrarater reliability was good with an overall ICC of 0.860 and 0.866, respectively. Overall, interrater reliability was higher for osteochondral lesions than for chondral lesions, with ICCs of 0.906 versus 0.786. CONCLUSIONS: The MOCART 2.0 knee score enables the assessment of cartilage repair tissue after different cartilage repair techniques (ACI, osteochondral repair techniques, MFX), as well as for different lesion types with good intra- and interrater reliability. KEY POINTS: • The MOCART 2.0 knee score provides improved intra- and interrater reliability when compared to the original MOCART score. • The MOCART 2.0 knee score enables the assessment of cartilage repair tissue after different cartilage repair techniques (ACI, osteochondral repair techniques, MFX) with similarly good intra- and interrater reliability. • The assessment of osteochondral lesions demonstrated better intra- and interrater reliability than the assessment of chondral lesions in this study.

[Morphological and functional sequelae after COVID-19 pneumonia]. / Morphologische und funktionelle Folgen nach COVID-19-Pneumonie.

BACKGROUND: Following coronavirus disease 2019 (COVID-19), a proportion of patients report prolonged or worsening symptoms and impairments. These symptoms are increasingly referred to as "long COVID" syndrome. They may be associated with radiological changes on computed tomography (CT) and pulmonary function impairment. OBJECTIVES: To discuss the role of long-term assessment of COVID-19 patients to determine which patients may benefit from follow-up. MATERIALS AND METHODS: This article presents the current results of clinical, radiological, and pulmonary function follow-up tests after COVID-19 pneumonia. RESULTS: Chronic fatigue and dyspnea are the most common persistent symptoms after COVID-19. Patients also present impaired exercise capacity. On CT, ground-glass opacities and parenchymal bands are the most common residual changes after COVID-19 pneumonia, histologically corresponding to organizing pneumonia. A proportion of patients who had severe COVID-19 pneumonia may show fibrotic-like changes during follow-up. Patients with severe acute infection may present with a restrictive syndrome with lower diffusing capacity for carbon monoxide (DLCO) and total lung capacity (TLC) values. Overall, significant and continuous improvement in all symptoms as well as radiomorphological and functional changes were observed over time. CONCLUSIONS: Patients with persistent symptoms after COVID-19 should be evaluated and treated in specialized post-COVID-19 clinics in a multidisciplinary manner.

[Radiological manifestations of pulmonary diseases in COVID-19]. / Radiologische Manifestationen von Lungenerkrankungen bei COVID-19.

CLINICAL ISSUE: Since its emergence in late 2019, the disease caused by the novel coronavirus, termed COVID-19, has been declared a pandemic by the World Health Organization. Reference standard for the diagnosis of COVID-19 is a positive reverse transcription polymerase chain reaction (RT-PCR) test. While the RT-PCR shows a high specificity, its sensitivity depends on the duration of symptoms, viral load, quality of the sample, and the assay used. STANDARD RADIOLOGICAL METHODS: Chest radiography and computed tomography (CT) of the chest are the imaging modalities primarily used for assessment of the lung manifestations, extent, and complications of COVID-19 pneumonia. PERFORMANCE: Sensitivity and specificity of chest radiography is low. While sensitivity of CT for detecting COVID-19 pneumonia is high-averaging around 90%-its specificity is low-between 25 and 33%. PRACTICAL RECOMMENDATIONS: Indications for imaging in patients with suspected or diagnosed COVID-19 infection should be carefully considered to minimize the risk of infection for medical personnel and other patients. Imaging, particularly CT, can assess disease extent, complications, and differential diagnoses. COVID-19 pneumonia typically presents with bilateral, subpleural areas of ground glass opacifications with or without consolidations. During the course of the disease features resembling organizing pneumonia can occur. Follow-up examinations after recovery from COVID-19 pneumonia should focus on fibrotic changes of the lung parenchyma.

[Machine learning in radiology : Terminology from individual timepoint to trajectory]. / Maschinelles Lernen in der Radiologie : Begriffsbestimmung vom Einzelzeitpunkt bis zur Trajektorie.

METHODICAL ISSUE: Machine learning (ML) algorithms have an increasingly relevant role in radiology tackling tasks such as the automatic detection and segmentation of diagnosis-relevant markers, the quantification of progression and response, and their prediction in individual patients. STANDARD RADIOLOGICAL METHODS: ML algorithms are relevant for all image acquisition techniques from computed tomography (CT) and magnetic resonance imaging (MRI) to ultrasound. However, different modalities result in different challenges with respect to standardization and variability. METHODICAL INNOVATIONS: ML algorithms are increasingly able to analyze longitudinal data for the training of prediction models. This is relevant since it enables the use of comprehensive information for predicting individual progression and response, and the associated support of treatment decisions by ML models. PERFORMANCE: The quality of detection and segmentation algorithms of lesions has reached an acceptable level in several areas. The accuracy of prediction models is still increasing, but is dependent on the availability of representative training data. ACHIEVEMENTS: The development of ML algorithms in radiology is progressing although many solutions are still at a validation stage. It is accompanied by a parallel and increasingly interlinked development of basic methods and techniques which will gradually be put into practice in radiology. PRACTICAL CONSIDERATIONS: Two factors will impact the relevance of ML in radiological practice: the thorough validation of algorithms and solutions, and the creation of representative diverse data for the training and validation in a realistic context.

Evaluation of age-dependent morphometrics of the meniscofemoral ligaments in reference to the posterior cruciate ligament in routine MRI.

OBJECTIVES: To quantify the morphological correlation between the posterior cruciate ligament (PCL) and the meniscofemoral ligaments (MFLs), to propose normal ranges for different age populations, and to define guidelines for correct identification and differentiation of MFLs in routine MRI. METHODS: Three hundred forty-two subjects were included retrospectively and subdivided into five age groups. Morphometrics of the PCL and the MFLs were measured on standard MRI in the sagittal, coronal, and axial planes. Student's t test, Mann-Whitney U test, and ANOVA and Kruskal-Wallis tests with Bonferroni correction were used for comparison. RESULTS: The MFLs did not vary significantly between sexes (p > 0.05) or in those older than 10 years (p > 0.05). Longitudinal MFL growth is completed before age 11 years, with cross-sectional area (CSA) increasing until age 20. The CSA of the PCL was significantly (p = 0.028) larger in knees without a pMFL (Mdn = 39.7 mm2) than with a pMFL (Mdn = 35.4 mm2). MFLs were more often detected on sagittal than coronal images. CONCLUSIONS: This study describes the morphometric relation between the PCL and the MFLs on routine MRI. When reporting imaging findings in preparation for arthroscopic knee surgery, evaluation of MFLs, first in the sagittal and then the coronal plane, will achieve the best results. KEY POINTS: • The MFLs and the PCL have distinct morphological patterns throughout life. • These patterns show intimate anatomical relationships and a potential biomechanical impact. • Those patterns and relationships can be quantified with MRI. • A correlation exists between age and morphometrics of the MFLs. • Recommendations for correct identification of the MFLs are provided.

Activity of Pembrolizumab in Recurrent Cervical Cancer: Case Series and Review of Published Data.

OBJECTIVES: Recent data support the use of pembrolizumab in cervical cancer. The aim of this study was to investigate pembrolizumab in heavily pretreated patients with recurrent cervical cancer. METHODS: Data from consecutive patients treated with pembrolizumab at a single academic institution were assessed. Programmed cell death ligand 1 (PD-L1) status and microsatellite instability were assessed from tumor samples. Irrespective of PD-L1 expression status, pembrolizumab was administered at fixed dose of 200 mg intravenously every 3 weeks. Treatment response was evaluated by computed tomography, using iRECIST (2017) criteria. Descriptive statistics were performed. Results from previous publications were summarized. RESULTS: In total, 11 heavily pretreated patients with recurrent cervical cancer received pembrolizumab. Of these, 2 (18%) patients showed partial response and 2 (18%) patients showed disease stabilization on computed tomography, resulting in a clinical benefit rate of 36%. These 4 patients are still on treatment and durable antitumor activity of up to 52 weeks was observed. Treatment was generally well tolerated with 1 patient showing dose-limiting toxicity. Median overall survival was 26 (3-53) weeks, and a 6-month overall survival rate of 65% was observed. Of the 5 patients with high PD-L1 expression, 3 showed response to treatment. CONCLUSIONS: Pembrolizumab shows promising activity in heavily pretreated patients with recurrent cervical cancer in a real-life clinical setting. Treatment was generally well tolerated, and adverse effects were manageable. Growing evidence supports the use of pembrolizumab in this group of patients.

The Femoral Intercondylar Notch During Life: An Anatomic Redefinition With Patterns Predisposing to Cruciate Ligament Impingement.

OBJECTIVE: The goals of this study were to test whether age- and sex-dependent variations in the size and shape of the intercondylar notch exist and to define the landmarks and measurements best suited for assessment of the intercondylar notch on MR images. MATERIALS AND METHODS: In this retrospective cross-sectional study, 329 patients were divided into six age groups, and their MR images (3-T coronal T2-weighted fat-suppressed spectral attenuated inversion recovery [SPAIR], sagittal proton density-weighted, axial T2-weighted fat-suppressed SPAIR) were evaluated. The intercondylar notch was measured and its shape evaluated on coronal images. Three shapes of intercondylar notch were defined. RESULTS: The intercondylar notch is subject to change throughout life, narrowing more distally and widening more proximally. Its width ranges from 16.23 ± 2.71 mm before the age of 11 years to 19.38 ± 2.90 mm in middle age and then decreases to 18.6 ± 2.36 mm after the age of 60 years. Its shape changes from an A shape in the early stages of life to an Ω shape in the later stages. CONCLUSION: The term "intercondylar space" is introduced as a morphologic description of the osseous intercondylar notch and adjacent structures. The femur as a whole is subject to substantial plastic deformation throughout life, not only in its proximal part, with respect to torsion, but also in its distal extent.

Hughes-Stovin syndrome-An important differential diagnosis in patients with suspected chronic thromboembolic pulmonary hypertension : A case report.

Hughes-Stovin syndrome (HSS) is a rare vasculitis of unknown etiology. The disease is characterized by pronounced inflammation and damage to the vessel walls, with subsequent widespread vascular thrombosis and the formation of pulmonary artery aneurysms that can lead to fatal hemoptysis. This disorder can be mistaken for other conditions, such as chronic thromboembolic pulmonary disease (CTEPD) without or with pulmonary hypertension at rest (CTEPH).We report the case of a 20-year-old female with HSS, which was misdiagnosed as CTEPH and subsequently treated with anticoagulants, which led to severe hemoptysis and eventually death of the patient. This case highlights the challenges of diagnosing HSS at early stages of the disease.HSS should be considered in young patients with signs of large vessel vasculitis in combination with thrombotic occlusions of pulmonary arteries, with or without aneurysms of the pulmonary arteries, and particularly, if there are no risk factors for thromboembolic disease.

Contrast Agent Dynamics Determine Radiomics Profiles in Oncologic Imaging.

BACKGROUND: The reproducibility of radiomics features extracted from CT and MRI examinations depends on several physiological and technical factors. The aim was to evaluate the impact of contrast agent timing on the stability of radiomics features using dynamic contrast-enhanced perfusion CT (dceCT) or MRI (dceMRI) in prostate and lung cancers. METHODS: Radiomics features were extracted from dceCT or dceMRI images in patients with biopsy-proven peripheral prostate cancer (pzPC) or biopsy-proven non-small cell lung cancer (NSCLC), respectively. Features that showed significant differences between contrast phases were identified using linear mixed models. An L2-penalized logistic regression classifier was used to predict class labels for pzPC and unaffected prostate regions-of-interest (ROIs). RESULTS: Nine pzPC and 28 NSCLC patients, who were imaged with dceCT and/or dceMRI, were included in this study. After normalizing for individual enhancement patterns by defining seven individual phases based on a reference vessel, 19, 467 and 128 out of 1204 CT features showed significant temporal dynamics in healthy prostate parenchyma, prostate tumors and lung tumors, respectively. CT radiomics-based classification accuracy of healthy and tumor ROIs was highly dependent on contrast agent phase. For dceMRI, 899 and 1027 out of 1118 features were significantly dependent on time after contrast agent injection for prostate and lung tumors. CONCLUSIONS: CT and MRI radiomics features in both prostate and lung tumors are significantly affected by interindividual differences in contrast agent dynamics.