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31.
BACKGROUND AND PURPOSE:Primary posterior fossa tumors comprise a large group of neoplasias with variable aggressiveness and short and long-term outcomes. This study aimed to validate the clinical usefulness of a radiologic decision flow chart based on previously published neuroradiologic knowledge for the diagnosis of posterior fossa tumors in children.MATERIALS AND METHODS:A retrospective study was conducted (from January 2013 to October 2019) at 2 pediatric referral centers, Children''s Hospital of Philadelphia, United States, and Great Ormond Street Hospital, United Kingdom. Inclusion criteria were younger than 18 years of age and histologically and molecularly confirmed posterior fossa tumors. Subjects with no available preoperative MR imaging and tumors located primarily in the brain stem were excluded. Imaging characteristics of the tumors were evaluated following a predesigned, step-by-step flow chart. Agreement between readers was tested with the Cohen κ, and each diagnosis was analyzed for accuracy.RESULTS:A total of 148 cases were included, with a median age of 3.4 years (interquartile range, 2.1–6.1 years), and a male/female ratio of 1.24. The predesigned flow chart facilitated identification of pilocytic astrocytoma, ependymoma, and medulloblastoma sonic hedgehog tumors with high sensitivity and specificity. On the basis of the results, the flow chart was adjusted so that it would also be able to better discriminate atypical teratoid/rhabdoid tumors and medulloblastoma groups 3 or 4 (sensitivity = 75%–79%; specificity = 92%–99%). Moreover, our adjusted flow chart was useful in ruling out ependymoma, pilocytic astrocytomas, and medulloblastoma sonic hedgehog tumors.CONCLUSIONS:The modified flow chart offers a structured tool to aid in the adjunct diagnosis of pediatric posterior fossa tumors. Our results also establish a useful starting point for prospective clinical studies and for the development of automated algorithms, which may provide precise and adequate diagnostic tools for these tumors in clinical practice.

In the past 10 years, there has been an exponential increase in knowledge of the molecular characteristics of pediatric brain tumors, which was only partially incorporated in the 2016 World Health Organization Classification of Tumors of the Central Nervous System.1 The main update in the 2016 Classification was the introduction of the molecular profile of a tumor as an important factor for predicting different biologic behaviors of entities which, on histology, look very similar or even indistinguishable.2 A typical example is the 4 main groups of medulloblastoma: wingless (WNT), sonic hedgehog (SHH) with or without the p53 mutation, group 3, and group 4. Although they may appear similar on microscopy, these categories have distinct molecular profiles, epidemiology, prognosis, and embryologic origin.3Subsequent to the publication of the 2016 World Health Organization Classification, further studies have identified even more molecular subgroups of medulloblastoma with possible prognostic implications4 and also at least 3 new molecular subgroups of atypical teratoid/rhabdoid tumor (AT/RT)5 and several subgroups of ependymoma.6 MR imaging shows promise as a technique for differentiating histologic tumors and their molecular subgroups. This capability relies on not only various imaging characteristics but also the location and spatial extension of the tumor, evident on MR imaging, which can be traced to the embryologic origin of the neoplastic cells.5,7-10One approach to the challenge of identifying imaging characteristics of different tumors in children is to use artificial intelligence. Yet despite this exciting innovation, correctly identifying the location of the mass and its possible use as an element for differential diagnosis still requires the expertise of an experienced radiologist. Previously, D''Arco et al11 proposed a flow chart (Fig 1) for the differential diagnosis of posterior fossa tumors in children based on epidemiologic, imaging signal, and location characteristics of the neoplasm. The aims of the current study were the following: 1) to validate, in a retrospective, large cohort of posterior fossa tumors from 2 separate pediatric tertiary centers, the diagnostic accuracy of that flow chart, which visually represents the neuroadiologist''s mental process in making a diagnosis of posterior fossa tumors in children, 2) to describe particular types of posterior fossa lesions that are not correctly diagnosed by the initial flow chart, and 3) to provide an improved, clinically accessible flow chart based on the results.Open in a separate windowFIG 1.Predesigned radiologic flow chart created according to the literature before diagnostic accuracy analysis. The asterisk indicates brain stem tumors excluded from the analysis. Double asterisks indicate relative to gray matter. Modified with permission from D''Arco et al.11  相似文献   
32.
BACKGROUND AND PURPOSE:Head motion causes image degradation in brain MR imaging examinations, negatively impacting image quality, especially in pediatric populations. Here, we used a retrospective motion correction technique in children and assessed image quality improvement for 3D MR imaging acquisitions.MATERIALS AND METHODS:We prospectively acquired brain MR imaging at 3T using 3D sequences, T1-weighted MPRAGE, T2-weighted TSE, and FLAIR in 32 unsedated children, including 7 with epilepsy (age range, 2–18 years). We implemented a novel motion correction technique through a modification of k-space data acquisition: Distributed and Incoherent Sample Orders for Reconstruction Deblurring by using Encoding Redundancy (DISORDER). For each participant and technique, we obtained 3 reconstructions as acquired (Aq), after DISORDER motion correction (Di), and Di with additional outlier rejection (DiOut). We analyzed 288 images quantitatively, measuring 2 objective no-reference image quality metrics: gradient entropy (GE) and MPRAGE white matter (WM) homogeneity. As a qualitative metric, we presented blinded and randomized images to 2 expert neuroradiologists who scored them for clinical readability.RESULTS:Both image quality metrics improved after motion correction for all modalities, and improvement correlated with the amount of intrascan motion. Neuroradiologists also considered the motion corrected images as of higher quality (Wilcoxon z = −3.164 for MPRAGE; z = −2.066 for TSE; z = −2.645 for FLAIR; all P < .05).CONCLUSIONS:Retrospective image motion correction with DISORDER increased image quality both from an objective and qualitative perspective. In 75% of sessions, at least 1 sequence was improved by this approach, indicating the benefit of this technique in unsedated children for both clinical and research environments.

Head motion is a common cause of image degradation in brain MR imaging. Motion artifacts negatively impact MR image quality and therefore radiologists’ capacity to read the images, ultimately affecting patient clinical care.1 Motion artifacts are more common in noncompliant patients,2 but even in compliant adults, intrascan movement is reported in at least 10% of cases.3 For children who require high-resolution MR images, obtaining optimal image quality can be challenging, owing to the requirement to stay still over long durations needed for acquisition.4 Sedation can be an option, but it carries higher risks, costs, and preparation and recovery time.5In conditions such as intractable focal epilepsy, identification of an epileptogenic lesion is clinically important to guide surgical treatment. However, these lesions can be visually subtle, particularly in children in whom subtle cortical dysplasias are more common.6 Dedicated epilepsy MR imaging protocols use high-resolution 3D sequences to allow better cortical definition and free reformatting of orientation but involve acquisition times in the order of minutes, so data collection becomes more sensitive to motion.7For children in particular, multiple strategies are available for minimizing motion during MR examinations. Collaboration with play specialists using mock scanners and training or projecting a cartoon are good approaches to reduce anxiety.8,9 These tools are not always available in clinical radiology and, even with these strategies, motion can still be an issue.10 Different scanning approaches to correct for intrascan motion have been proposed. Broadly, prospective methods track head motion in real time and modify the acquisition directions accordingly.11 These approaches are applicable to a wide range of sequences but require optical systems with external tracking markers, sometimes uncomfortable or impractical, and extra setup can ultimately result in longer examinations. Furthermore, these approaches may also not be robust to continuous motion.11-13 Retrospective techniques have also been proposed, in some cases relying on imaging navigators that are not compatible with all standard sequences or contrasts.12Here, we use a more general retrospective motion correction technique: Distributed and Incoherent Sample Orders for Reconstruction Deblurring by using Encoding Redundancy (DISORDER). In this method, k-space samples are reordered to enable retrospective motion correction during image reconstruction.14 Our hypothesis is that DISORDER improves clinical MR imaging quality and readability. To assess its use for clinical sequences, we acquired a dedicated epilepsy MR imaging protocol in 32 children across a wide age range. We used both objective image quality metrics and expert neuroradiologist ratings to evaluate the outcome after motion correction.  相似文献   
33.
AimsOrgan preservation, an important goal in the treatment of head and neck squamous cell carcinoma (HNSCC), may include induction chemotherapy and cisplatin with radiation therapy (CRT). To our knowledge, no reports have directly compared the impact of induction chemotherapy with that of CRT on health-related quality of life (HRQOL).Materials and methodsIn a phase II trial, we assessed the HRQOL of patients treated with induction chemotherapy followed by CRT. Eligible patients had stage III–IV HNSCC. HRQOL questionnaires were administered at baseline, the end of induction (EOI), the end of CRT (EOCRT) and after CRT. Functional Assessment of Cancer Therapy (FACT version 4) assessed HRQOL. We carried out a comparison of changes in HRQOL from baseline to EOI and from EOI to EOCRT. This trial is registered with ClinicalTrials.gov (NCT01566435).ResultsThirty patients were enrolled in the study. Most HRQOL questionnaires were completed (88%). The mean total FACT scores did not differ from baseline to EOI (general: 83.8 versus 79.1, P = 0.08; head and neck: 109.7 versus 105.8, P = 0.33; Total Outcome Index: 69.7 versus 62.3, P = 0.03; respectively, using P ≤ 0.01 to adjust for multiple simultaneous tests of differences). However, total FACT scores significantly worsened from EOI to EOCRT (79.1 versus 62.3, P = 0.01; 105.8 versus 74.2, P < 0.01; 62.3 versus 34.2, P = 0.01; respectively). Within domains, the head and neck cancer subscale score did not differ from baseline to EOI (median 28.5 versus 27.0, P = 0.69), but significantly worsened from EOI to EOCRT (27.0 versus 9.5, P < 0.01). Swallowing, oral pain and voice quality improved from baseline to EOI, but worsened from EOI to EOCRT. Physical and functional scores worsened from baseline to EOI and from EOI to EOCRT. The emotional well-being score improved from baseline to EOI but worsened from EOI to EOCRT.ConclusionsOverall, HRQOL did not significantly change from baseline to EOI but dramatically worsened from EOI to EOCRT.  相似文献   
34.

Background and aims

Since accelerated atherosclerosis has been reported in systemic lupus erythematosus (SLE), predictive biomarkers of cardiovascular disease (CVD) are needed. Among non-traditional risk factors, bone mineral density (BMD) has been related to CVD. However, its role in SLE remains controversial. This study aims to analyze the associations of subclinical atherosclerosis with traditional and non-traditional CV risk factors.

Methods and results

In a cross-sectional study, atherosclerosis burden was compared between 112 female SLE patients and 31 controls. Plaque number and carotid intima-media wall thickness (cIMT) were assessed by ultrasonography. In a retrospective study, BMD determinations obtained 5-years before the ultrasonography assessment were analyzed in a subgroup of 62 patients. Plaque frequency was increased in SLE, even in patients without CV events or carotid wall thickening. cIMT was increased in patients with CVD, positively correlated with body mass index (BMI). Interestingly, a paradoxical effect of BMI on carotid parameters was observed. Whereas underweight patients (BMI < 20) showed increased prevalence of carotid plaques with low cIMT, those with BMI > 30 showed higher cIMT and plaque burden. Overweight patients (25 < BMI<30) exhibited both elevated cIMT and plaque number. BMI was an independent predictor of BMD. In our retrospective study, patients with either clinical or subclinical CVD exhibited lower BMD levels than their CV-free counterparts. A low lumbar spine BMD independently predicted CVD development after adjusting for confounders.

Conclusion

SLE was associated with a higher subclinical atherosclerosis burden, a bimodal effect being observed for BMI. Decreased BMD can be a CV risk biomarker in SLE.  相似文献   
35.
BackgroundThe efficacy of ticagrelor in the long-term post–ST-segment elevation myocardial infarction (STEMI) treated with fibrinolytic therapy remains uncertain.ObjectivesThe purpose of this study was to evaluate the efficacy of ticagrelor when compared with clopidogrel in STEMI patients treated with fibrinolytic therapy.MethodsThis international, multicenter, randomized, open-label with blinded endpoint adjudication trial enrolled 3,799 patients (age <75 years) with STEMI receiving fibrinolytic therapy. Patients were randomized to ticagrelor (180-mg loading dose, 90 mg twice daily thereafter) or clopidogrel (300- to 600-mg loading dose, 75 mg daily thereafter). The key outcomes were cardiovascular mortality, myocardial infarction, or stroke, and the same composite outcome with the addition of severe recurrent ischemia, transient ischemic attack, or other arterial thrombotic events at 12 months.ResultsThe combined outcome of cardiovascular mortality, myocardial infarction, or stroke occurred in 129 of 1,913 patients (6.7%) receiving ticagrelor and in 137 of 1,886 patients (7.3%) receiving clopidogrel (hazard ratio: 0.93; 95% confidence interval: 0.73 to 1.18; p = 0.53). The composite of cardiovascular mortality, myocardial infarction, stroke, severe recurrent ischemia, transient ischemic attack, or other arterial thrombotic events occurred in 153 of 1,913 patients (8.0%) treated with ticagrelor and in 171 of 1,886 patients (9.1%) receiving clopidogrel (hazard ratio: 0.88; 95% confidence interval: 0.71 to 1.09; p = 0.25). The rates of major, fatal, and intracranial bleeding were similar between the ticagrelor and clopidogrel groups.ConclusionAmong patients age <75 years with STEMI, administration of ticagrelor after fibrinolytic therapy did not significantly reduce the frequency of cardiovascular events when compared with clopidogrel. (Ticagrelor in Patients With ST Elevation Myocardial Infarction Treated With Pharmacological Thrombolysis [TREAT]; NCT02298088)  相似文献   
36.

Purpose

To qualitatively and quantitatively compare unenhanced ultra-low-dose chest computed tomography (ULD-CT) acquired at 80 kVp and 135 kVp.

Materials and methods

Fifty-one patients referred for unenhanced chest CT were prospectively included. There were 29 men and 22 women, with a mean age of 64.7 ± 11.6 (SD) years (range: 35–91 years) and a mean body mass index of 26.2 ± 6.3 (SD) (range: 17–54.9). All patients underwent two different ULD-CT protocols (80 kVp-40 mA and 135 kVp-10 mA). Image quality of both ULD-CT examinations using a 5-level scale as well as assessability of 6 predetermined lung parenchyma lesions were blindly evaluated by three radiologists and compared using a logistic regression model. Image noise of the two protocols was compared with Wilcoxon signed-rank test.

Results

The mean dose-length product at 80 kVp and at 135 kVp were 14.7 ± 1.8 (SD) mGy.cm and 15.6 ± 1.9 (SD) mGy.cm, respectively (P < 0.001). Image noise was significantly lower at 135 kVp (58.9 ± 12.4) than at 80 kVp (74.7 ± 14.5) (P < 0.001). For all readers and for all examinations, the 135 kVp protocol yielded better image quality than 80 kVp protocol, with a mean qualitative score of 4.5 ± 0.7 versus 3.9 ± 0.8 (P < 0.001). The 135 kVp protocol was significantly more often of diagnostic quality than the 80 kvp protocol (92.3% versus 77.8%, respectively) (P < 0.001) and was less prone to image quality deterioration in obese patients. Parenchymal lesions were never better depicted on the 80 kVp protocol than with the 135 kVp protocol.

Conclusion

Unenhanced chest ULD-CT should be acquired at a high kilovoltage and low current, such as 135 kVp-10 mA, over a low kilovoltage and high current protocol.  相似文献   
37.

Purpose

The purpose of this study was to assess the potential of a deep learning model to discriminate between benign and malignant breast lesions using magnetic resonance imaging (MRI) and characterize different histological subtypes of breast lesions.

Materials and methods

We developed a deep learning model that simultaneously learns to detect lesions and characterize them. We created a lesion-characterization model based on a single two-dimensional T1-weighted fat suppressed MR image obtained after intravenous administration of a gadolinium chelate selected by radiologists. The data included 335 MR images from 335 patients, representing 17 different histological subtypes of breast lesions grouped into four categories (mammary gland, benign lesions, invasive ductal carcinoma and other malignant lesions). Algorithm performance was evaluated on an independent test set of 168 MR images using weighted sums of the area under the curve (AUC) scores.

Results

We obtained a cross-validation score of 0.817 weighted average receiver operating characteristic (ROC)-AUC on the training set computed as the mean of three-shuffle three-fold cross-validation. Our model reached a weighted mean AUC of 0.816 on the independent challenge test set.

Conclusion

This study shows good performance of a supervised-attention model with deep learning for breast MRI. This method should be validated on a larger and independent cohort.  相似文献   
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