Context-dependent roles for autophagy in myeloid cells in tumor progression.

Autophagy is known to suppress tumor initiation by removing genotoxic stresses in normal cells. Conversely, autophagy is also known to support tumor progression by alleviating metabolic stresses in neoplastic cells. Centered on this pro-tumor role of autophagy, there have been many clinical trials to treat cancers through systemic blocking of autophagy. Such systemic inhibition affects both tumor cells and non-tumor cells, and the consequence of blocked autophagy in non-tumor cells in the context of tumor microenvironment is relatively understudied. Here, we examined the effect of autophagy-deficient myeloid cells on the progression of autophagy-competent tumors. We found that blocking autophagy only in myeloid cells modulated tumor progression markedly but such effects were context dependent. In a tumor implantation model, the growth of implanted tumor cells was substantially reduced in mice with autophagy-deficient myeloid cells; T cells infiltrated deeper into the tumors and were responsible for the reduced growth of the implanted tumor cells. In an oncogene-driven tumor induction model, however, tumors grew faster and metastasized more in mice with autophagy-deficient myeloid cells. These data demonstrate that the autophagy status of myeloid cells plays a critical role in tumor progression, promoting or suppressing tumor growth depending on the context of tumor-myeloid cell interactions. This study indicates that systemic use of autophagy inhibitors in cancer therapy may have differential effects on rates of tumor progression in patients due to effects on myeloid cells and that this warrants more targeted use of selective autophagy inhibitors in a cancer therapy in a clinical setting.

Fat quantification of the rotator cuff muscles using CT histogram analysis in comparison with Dixon MRI sequence.

OBJECTIVES: To quantify the proportion of fat within the rotator cuff muscles using CT histogram analysis (HA) and to compare fat fraction (FF) values obtained from CT and T2*-corrected 6-echo three-dimensional gradient-echo Dixon sequences. METHODS: Twenty-six patients who underwent both shoulder CT and MRI were enrolled. The FF of rotator cuff muscles was measured on FF maps of the Dixon technique. Using CT, the FF values were obtained in two ways: 1) CT mean Hounsfield Unit (HU) measurement-based fat quantification using subcutaneous fat and the teres major muscle as internal standards; and 2) CT HA-based fat quantification in which pixels from -190 to -30 HU were arbitrarily classified as fat, and those from -30 to 150 HU as muscle. Afterward, the relationship between FF values from MRI (FF-MR), CT mean HU-based analysis (FF-HU), and CT HA (FF-HA) was assessed. RESULTS: There were strong positive correlations (p < 0.001) between FF-MR and FF-HA, which were higher when compared with FF-HU (r = 0.90 vs. 0.77 for total). For a total of 104 rotator cuff muscles, the intraclass correlation between FF-MR and FF-HA was excellent (ICC, 0.90), which was higher than that between FF-MR and FF-HU (ICC, 0.76). The ICCs showed excellent interobserver agreement between FF-MR, FF-HU, and FF-HA (ICCs, 0.93-0.96). CONCLUSIONS: Fat quantification within the rotator cuff muscles using CT HA is both feasible and reliable. ADVANCES IN KNOWLEDGE: CT HA provides reliable quantification of intramuscular fat and has strengths regarding its retrospective applicability to conventional CT studies without additional radiation dose to subjecting patients.

Feasibility and clinical usefulness of deep learning-accelerated MRI for acute painful fracture patients wearing a splint: A prospective comparative study.

OBJECTIVE: To evaluate the feasibility and clinical usefulness of deep learning (DL)-accelerated turbo spin echo (TSEDL) sequences relative to standard TSE sequences (TSES) for acute radius fracture patients wearing a splint. METHODS: This prospective consecutive study investigated 50 patients' preoperative wrist MRI scans acquired between July 2021 and January 2022. Examinations were performed at 3 Tesla MRI with body array coils due to the wrist splint. Besides TSES obtained according to the routine protocol, TSEDL sequences for axial T2-, coronal T1-, and coronal PD-weighted TSE sequences were scanned for comparison. For quantitative assessment, the relative signal-to-noise ratio (rSNR), the relative contrast-to-noise ratio (rCNR), and the relative contrast ratio (rCR) were measured. For qualitative assessment, all images were assessed by two independent musculoskeletal radiologists in terms of perceived SNR, image contrast, image sharpness, artifacts disturbing evaluation, overall image quality and diagnostic confidence for injuries using a four- or five-point Likert scale. RESULTS: The scan time was shortened approximately by a factor of two for TSEDL compared to TSES. TSEDL images showed significantly better rSNR, rCNR, and rCR values for all sequences, and scored significantly better in terms of both image quality and diagnostic confidence for both readers than TSES images (all p < .05). Interrater reliabilities were in almost perfect agreement. CONCLUSION: The DL-accelerated technique proved to be very helpful not only to reduce scan time but also to improve image quality for acute painful fracture patients wearing a splint despite using body array coils instead of a wrist-specific coil. Based on our study, the DL-accelerated technique can be very useful for MRI of any part of the extremities in trauma settings just with body array coils.

Comparison of Metal Artifact Reduction Algorithms in Patients with Hip Prostheses: Virtual Monoenergetic Images vs. Orthopedic Metal Artifact Reduction.

Purpose: To assess the usefulness of various metal artifact reduction (MAR) methods in patients with hip prostheses. Materials and Methods: This retrospective study included 47 consecutive patients who underwent hip arthroplasty and dual-energy CT. Conventional polyenergetic image (CI), orthopedic-MAR (O-MAR), and virtual monoenergetic image (VMI, 50-200 keV) were tested for MAR. Quantitative analysis was performed in seven regions around the prostheses. Qualitative assessments included evaluation of the degree of artifacts and the presence of secondary artifacts. Results: The lowest amount of image noise was observed in the O-MAR, followed by the VMI. O-MAR also showed the lowest artifact index, followed by high-keV VMI in the range of 120-200 keV (soft tissue) or 200 keV (bone). O-MAR had the highest contrast-to-noise ratio (CNR) in regions with severe hypodense artifacts, while VMI had the highest CNR in other regions, including the periprosthetic bone. On assessment of the CI of pelvic soft tissues, VMI showed a higher structural similarity than O-MAR. Upon qualitative analysis, metal artifacts were significantly reduced in O-MAR, followed by that in VMI, while secondary artifacts were the most frequently found in the O-MAR (p < 0.001). Conclusion: O-MAR is the best technique for severe MAR, but it can generate secondary artifacts. VMI at high keV can be advantageous for evaluating periprosthetic bone.

Deep Radiomics-based Approach to the Diagnosis of Osteoporosis Using Hip Radiographs.

Purpose: To develop and validate deep radiomics models for the diagnosis of osteoporosis using hip radiographs. Materials and Methods: A deep radiomics model was developed using 4924 hip radiographs from 4308 patients (3632 women; mean age, 62 years ± 13 [SD]) obtained between September 2009 and April 2020. Ten deep features, 16 texture features, and three clinical features were used to train the model. T score measured with dual-energy x-ray absorptiometry was used as a reference standard for osteoporosis. Seven deep radiomics models that combined different types of features were developed: clinical (model C); texture (model T); deep (model D); texture and clinical (model TC); deep and clinical (model DC); deep and texture (model DT); and deep, texture, and clinical features (model DTC). A total of 444 hip radiographs obtained between January 2019 and April 2020 from another institution were used for the external test. Six radiologists performed an observer performance test. The area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic performance. Results: For the external test set, model D (AUC, 0.92; 95% CI: 0.89, 0.95) demonstrated higher diagnostic performance than model T (AUC, 0.77; 95% CI: 0.70, 0.83; adjusted P < .001). Model DC (AUC, 0.95; 95% CI: 0.92, 0.97; adjusted P = .03) and model DTC (AUC, 0.95; 95% CI: 0.92, 0.97; adjusted P = .048) showed improved diagnostic performance compared with model D. When observer performance without and with the assistance of the model DTC prediction was compared, performance improved from a mean AUC of 0.77 to 0.87 (P = .002). Conclusion: Deep radiomics models using hip radiographs could be used to diagnose osteoporosis with high performance.Keywords: Skeletal-Appendicular, Hip, Absorptiometry/Bone Densitometry© RSNA, 2022.

Deep learning-based fully automated body composition analysis of thigh CT: comparison with DXA measurement.

OBJECTIVES: To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition. METHODS: This prospective study was performed from January 2019 to December 2020. The participants underwent DXA to determine the body composition of the whole body and thigh. CT was performed in the thigh region; the images were automatically segmented into three muscle groups and adipose tissue by custom-developed DL-based automated segmentation software. Subsequently, the program reported the tissue composition of the thigh. The correlation and agreement between variables measured by DXA and CT were assessed. Then, CT thigh tissue volume prediction equations based on DXA-derived thigh tissue mass were developed using a general linear model. RESULTS: In total, 100 patients (mean age, 44.9 years; 60 women) were evaluated. There was a strong correlation between the CT and DXA measurements (R = 0.813~0.98, p < 0.001). There was no significant difference in total soft tissue mass between DXA and CT measurement (p = 0.183). However, DXA overestimated thigh lean (muscle) mass and underestimated thigh total fat mass (p < 0.001). The DXA-derived lean mass was an average of 10% higher than the CT-derived lean mass and 47% higher than the CT-derived lean muscle mass. The DXA-derived total fat mass was approximately 20% lower than the CT-derived total fat mass. The predicted CT tissue volume using DXA-derived data was highly correlated with actual CT-measured tissue volume in the validation group (R2 = 0.96~0.97, p < 0.001). CONCLUSIONS: Volumetric CT measurements with DL-based fully automated segmentation are a rapid and more accurate method for measuring thigh tissue composition. KEY POINTS: • There was a positive correlation between CT and DXA measurements in both the whole body and thigh. • DXA overestimated thigh lean mass by 10%, lean muscle mass by 47%, but underestimated total fat mass by 20% compared to the CT method. • The equations for predicting CT volume (cm3) were developed using DXA data (g), age, height (cm), and body weight (kg) and good model performance was proven in the validation study.

Improved diagnostic performance of plain radiography for cervical ossification of the posterior longitudinal ligament using deep learning.

BACKGROUND: A high false-negative rate has been reported for the diagnosis of ossification of the posterior longitudinal ligament (OPLL) using plain radiography. We investigated whether deep learning (DL) can improve the diagnostic performance of radiologists for cervical OPLL using plain radiographs. MATERIALS AND METHODS: The training set consisted of 915 radiographs from 207 patients diagnosed with OPLL. For the test set, we used 200 lateral cervical radiographs from 100 patients with cervical OPLL and 100 patients without OPLL. An observer performance study was conducted over two reading sessions. In the first session, we compared the diagnostic performance of the DL-model and the six observers. The diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC) at the vertebra and patient level. The sensitivity and specificity of the DL model and average observers were calculated in per-patient analysis. Subgroup analysis was performed according to the morphologic classification of OPLL. In the second session, observers evaluated the radiographs by referring to the results of the DL-model. RESULTS: In the vertebra-level analysis, the DL-model showed an AUC of 0.854, which was higher than the average AUC of observers (0.826), but the difference was not significant (p = 0.292). In the patient-level analysis, the performance of the DL-model had an AUC of 0.851, and the average AUC of observers was 0.841 (p = 0.739). The patient-level sensitivity and specificity were 91% and 69% in the DL model, and 83% and 68% for the average observers, respectively. Both the DL-model and observers showed decreases in overall performance in the segmental and circumscribed types. With knowledge of the results of the DL-model, the average AUC of observers increased to 0.893 (p = 0.001) at the vertebra level and 0.911 (p < 0.001) at the patient level. In the subgroup analysis, the improvement was largest in segmental-type (AUC difference 0.087; p = 0.002). CONCLUSIONS: The DL-based OPLL detection model can significantly improve the diagnostic performance of radiologists on cervical radiographs.

Using Convolutional Neural Network with Taguchi Parametric Optimization for Knee Segmentation from X-Ray Images.

Loss of knee cartilage can cause intense pain at the knee epiphysis and this is one of the most common diseases worldwide. To diagnose this condition, the distance between the femur and tibia is calculated based on X-ray images. Accurate segmentation of the femur and tibia is required to assist in the calculation process. Several studies have investigated the use of automatic knee segmentation to assist in the calculation process, but the results are of limited value owing to the complexity of the knee. To address this problem, this study exploits deep learning for robust segmentation not affected by the environment. In addition, the Taguchi method is applied to optimize the deep learning results. Deep learning architecture, optimizer, and learning rate are considered for the Taguchi table to check the impact and interaction of the results. When the Dilated-Resnet architecture is used with the Adam optimizer and a learning rate of 0.001, dice coefficients of 0.964 and 0.942 are obtained for the femur and tibia for knee segmentation. The implemented procedure and the results of this investigation may be beneficial to help in determining the correct margins for the femur and tibia and can be the basis for developing an automatic diagnosis algorithm for orthopedic diseases.

CT Hounsfield unit and histogram analysis for differentiation of recent versus remote vertebral compression fractures.

OBJECTIVES: The purpose of this study was to analyze the intraosseous tissue changes in recent vertebral compression fractures (VCFs) and to differentiate recent from remote VCFs using CT Hounsfield unit histogram analysis (HUHA). METHODS: 65 patients with T11 to L3 VCFs were included. HUHA of 2 vertebral bodies (VBs)- a fractured VB and the closest lower-level unaffected VB-was done. The mean Hounsfield unit (HU) value and HU proportions of 5 ranges (HU ≤ 0, 0 < HU ≤ 50, 50 < HU ≤ 100, 100 < HU ≤ 150, and HU > 150) were obtained. Then, ΔHU value and ΔHU proportion were calculated by subtracting the values from the two vertebrae. Finally, the obtained values were compared between the recent and remote VCF groups and subjected to ROC curve analysis. RESULTS: In recent VCF group, the ΔHU proportion (HU ≤ 0) corresponding to normal fatty marrow was lower (-0.17 vs 0.01) and the ΔHU proportion (HU > 150) representing trabecular bone was higher (0.23 vs 0.04) than in remote VCF group (p < 0.001). In the differentiation of recent from remote VCF, the ΔHU value and ΔHU proportion (HU > 150) showed high area under the curve (AUC, 0.939 and 0.912, respectively). CONCLUSION: CT HUHA demonstrated both trabecular bone and bone marrow changes in recent VCFs, and showed high diagnostic performance in differentiating between recent and remote VCFs. ADVANCES IN KNOWLEDGE: With its vendor neutral applicability, CT HUHA can be used for the differentiation of recent and remote VCFs.

Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images: A Pilot Study Using Lumbar Spine CT.

OBJECTIVE: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. MATERIALS AND METHODS: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI™, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. RESULTS: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). CONCLUSION: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.

Fat-suppressed T2 mapping of human knee femoral articular cartilage: comparison with conventional T2 mapping.

BACKGROUND: There is paucity of studies applying fat suppressed (FS) technique to T2 mapping to overcome chemical shift artifacts. The purpose of the study is to difference between FS T2 and conventional T2 mapping and reproducibility of FS T2 mapping in the femoral articular cartilage. METHODS: Eighteen patients who had normal-looking femoral cartilage and underwent knee MRI with conventional T2 and FS T2 mapping were included. T2 values of each mapping were measured by two readers independently from nine regions in the medial femoral condyle (MFC) and lateral femoral condyle (LFC). Each anatomical region was divided by lines at ± 10°, 30°, 50°, 70°, 90°, and 110°. Comparisons of T2 values between conventional and FS T2 mapping were statistically analyzed. The T2 values between FS and conventional T2 mapping in the anterior, central and posterior femoral condyles were compared. RESULTS: The overall femoral condyle T2 values from the FS T2 map were significantly lower than those from the conventional T2 map (48.5ms vs. 51.0ms, p < 0.001). The differences in the T2 values between the two maps were significantly different among the three divisions of the LFC (p = 0.009) and MFC (p = 0.031). The intra-class correlation coefficients indicated higher agreement in the FS T2 map than in the conventional T2 map (0.943 vs. 0.872). CONCLUSIONS: The T2 values of knee femoral cartilage are significantly lower on FS T2 mapping than on conventional T2 mapping. FS T2 mapping is a more reproducible method for evaluating knee femoral cartilage.

Dual-Layer Detector CT With Virtual Noncalcium Imaging: Diagnostic Performance in Patients With Suspected Wrist Fractures.

OBJECTIVE. The purpose of this study was to evaluate the diagnostic utility of dual-layer CT (DLCT) for evaluating wrist injuries and to compare it with MRI. MATERIALS AND METHODS. The cases of 62 patients with suspected wrist fractures who underwent imaging with both DLCT and MRI from January 2018 through February 2019 were retrospectively reviewed. By means of a calcium suppression algorithm, virtual noncalcium (VNCa) image reconstruction was performed, and the images were reviewed by two readers to identify fractures, bone contusions, and nontraumatic lesions in the radius, ulna, and carpal bones. Sensitivity, specificity, PPV, and NPV were calculated and compared between standard CT and VNCa images with a combination of standard CT and MRI as the reference standard. RESULTS. Use of DLCT with VNCa reconstruction increased the sensitivity of diagnosis of fractures in the radius and carpal bones over that of standard CT alone; occult fractures were detected that were not seen with standard CT. The sensitivity and specificity for detecting radius fracture were 98.1% and 93.8% for DLCT and 96.3% and 93.8% for standard CT. For detecting carpal bone fracture, sensitivity and specificity were 100% and 98.9% for DLCT and 93.8% and 100% for standard CT. VNCa reconstruction also had good diagnostic accuracy with regard to diagnosing nonfracture bone contusions in carpal bones. The accuracy was comparable to that of MRI with sensitivity of 92.9% and specificity of 94.5%. Interreader agreement in interpreting VNCa images was generally good to excellent. CONCLUSION. DLCT with VNCa reconstruction is a promising tool for identifying occult wrist fractures and nonfracture contusion injuries in patients with wrist trauma.

Radiographic Follow-Up of Fibrous Dysplasia in 138 Patients.

OBJECTIVE. The purpose of this study was to explore the temporal changes in fibrous dysplasia (FD) at radiographic follow-up. MATERIALS AND METHODS. A total of 138 patients with FD who had undergone extremity radiography at least twice with a minimum 12-month interval between examinations were enrolled in this study. FD was monostotic in 99 patients and polyostotic in 39 patients. Patients were also classified according to skeletal maturity as follows: Patients 16 years old or younger were classified in the skeletally immature group (n = 34), and patients 17 years old or older were classified in the skeletally mature group (n = 104). We compared the initial and follow-up radiographs for the following findings: lesion size, opacity, sclerotic rim, calcification, and trabeculation. RESULTS. Of the 138 patients, radiographic follow-up showed no change in lesion size in 101 patients (73.2%), progression in 31 (22.5%), and regression in six (4.3%). FD in immature bones progressed more often than FD in mature bones (23/34 [67.6%] vs 8/104 [7.7%], respectively; p = 0.000), and polyostotic FD had a greater chance of regressing than monostotic FD (4/39 [10.3%] vs 2/99 [2.0%]; p = 0.032). A temporal change in FD lesion opacity was noticed in a minority of patients (19/138, 13.8%). Variable changes were observed in the sclerotic rim, calcification, and trabeculation. CONCLUSION. The radiographic follow-up of FD showed that approximately a quarter of lesions changed in size over time. Regardless of the change in lesion size, opacity and several morphologic features of FD changed during the follow-up period, which might reflect the histopathologic evolution of FD.

Two-Dimensional Image-Based Screening Tool for Infants with Positional Cranial Deformities: A Machine Learning Approach.

Positional cranial deformities are relatively common conditions, characterized by asymmetry and changes in skull shape. Although three-dimensional (3D) scanning is the gold standard for diagnosing such deformities, it requires expensive laser scanners and skilled maneuvering. We therefore developed an inexpensive, fast, and convenient screening method to classify cranial deformities in infants, based on single two-dimensional vertex cranial images. In total, 174 measurements from 80 subjects were recorded. Our screening software performs image processing and machine learning-based estimation related to the deformity indices of the cranial ratio (CR) and cranial vault asymmetry index (CVAI) to determine the severity levels of brachycephaly and plagiocephaly. For performance evaluations, the estimated CR and CVAI values were compared to the reference data obtained using a 3D cranial scanner. The CR and CVAI correlation coefficients obtained via support vector regression were 0.85 and 0.89, respectively. When the trained model was evaluated using the unseen test data for the three CR and three CVAI classes, an 86.7% classification accuracy of the proposed method was obtained for both brachycephaly and plagiocephaly. The results showed that our method for screening cranial deformities in infants could aid clinical evaluations and parental monitoring of the progression of deformities at home.

CD300LF Polymorphisms of Inbred Mouse Strains Confer Resistance to Murine Norovirus Infection in a Cell Type-Dependent Manner.

Human norovirus is the leading cause of gastroenteritis worldwide, yet basic questions about its life cycle remain unanswered due to an historical lack of robust experimental systems. Recent studies on the closely related murine norovirus (MNV) have identified CD300LF as an indispensable entry factor for MNV. We compared the MNV susceptibilities of cells from different mouse strains and identified polymorphisms in murine CD300LF which are critical for its function as an MNV receptor. Bone marrow-derived macrophages (BMDMs) from I/LnJ mice were resistant to infection from multiple MNV strains which readily infect BMDMs from C57BL/6J mice. The resistance of I/LnJ BMDMs was specific to MNV, since the cells supported infection of other viruses comparably to C57BL/6J BMDMs. Transduction of I/LnJ BMDMs with C57BL/6J CD300LF made the cells permissible to MNV infection, suggesting that the cause of resistance lies in the entry step of MNV infection. In fact, we mapped this phenotype to a 4-amino-acid difference at the CC' loop of CD300LF; swapping of these amino acids between C57BL/6J and I/LnJ CD300LF proteins made the mutant C57BL/6J CD300LF functionally impaired and the corresponding mutant of I/LnJ CD300LF functional as an MNV entry factor. Surprisingly, expression of the I/LnJ CD300LF in other cell types made the cells infectible by MNV, even though the I/LnJ allele did not function as an MNV receptor in macrophage-like cells. Correspondingly, I/LnJ CD300LF bound MNV virions in permissive cells but not in nonpermissive cells. Collectively, our data suggest the existence of a cell type-specific modifier of MNV entry.IMPORTANCE MNV is a prevalent model system for studying human norovirus, which is the leading cause of gastroenteritis worldwide and thus a sizeable public health burden. Elucidating mechanisms underlying susceptibility of host cells to MNV infection can lead to insights on the roles that specific cell types play during norovirus pathogenesis. Here, we show that different alleles of the proteinaceous receptor for MNV, CD300LF, function in a cell type-dependent manner. In contrast to the C57BL/6J allele, which functions as an MNV entry factor in all tested cell types, including human cells, I/LnJ CD300LF does not function as an MNV entry factor in macrophage-like cells but does allow MNV entry in other cell types. Together, these observations indicate the existence of cell type-specific modifiers of CD300LF-dependent MNV entry.

Combined use of virtual monochromatic images and projection-based metal artifact reduction methods in evaluation of total knee arthroplasty.

OBJECTIVES: To evaluate the effect of the combined use of virtual monochromatic imaging (VMI) and projection-based metal artifact reduction (PB-MAR) methods on further artifact reduction and image quality in total knee arthroplasty (TKA) patients. METHODS: Fifty-seven knee joints from 36 patients who had a previous history of TKA for bilateral or unilateral knee joints were included in this study. Four sets of images were compared between non-MAR, PB-MAR, VMI, and VMI + PB-MAR. For quantitative analysis, the area, mean attenuation, artifact index (AI), and contrast-to-noise ratio (CNR) were calculated for each protocol. Regarding qualitative analysis, overall artifact and depiction of soft tissue and bony structure were compared using relative visual grading analysis. RESULTS: In the femoral region, the VMI + PB-MAR protocol showed the best MAR performance in quantitative measures including area, mean attenuation, and AI (p < .001). However, MAR protocols with VMI showed significantly lower CNRs than did the protocols without VMI in the tibial region (p < .001). On qualitative analysis, VMI + PB-MAR also showed fewer overall artifacts than did the other two MAR protocols. Soft tissue was best depicted in VMI + PB-MAR protocol, and PB-MAR showed the best performance for the depiction of bony structure (p < .001). CONCLUSIONS: The combined use of VMI and PB-MAR showed better MAR performance than did PB-MAR or VMI alone. In areas with severe metal artifacts, the VMI + PB-MAR and PB-MAR protocols were useful for the evaluation of soft tissue and bone structure, respectively. KEY POINTS: • The combination of artifact reduction methods is effective in reducing metal artifacts in CT. • Soft tissue was best depicted in the combined protocol of projection- and dual-energy-based methods, and projection-based protocol showed the best performance for the depiction of bone structure in case of severe metal artifacts.

Engineered cartilage utilizing fetal cartilage-derived progenitor cells for cartilage repair.

The aim of this study was to develop a fetal cartilage-derived progenitor cell (FCPC) based cartilage gel through self-assembly for cartilage repair surgery, with clinically useful properties including adhesiveness, plasticity, and continued chondrogenic remodeling after transplantation. Characterization of the gels according to in vitro self-assembly period resulted in increased chondrogenic features over time. Adhesion strength of the cartilage gels were significantly higher compared to alginate gel, with the 2-wk group showing a near 20-fold higher strength (1.8 ± 0.15 kPa vs. 0.09 ± 0.01 kPa, p < 0.001). The in vivo remodeling process analysis of the 2 wk cultured gels showed increased cartilage repair characteristics and stiffness over time, with higher integration-failure stress compared to osteochondral autograft controls at 4 weeks (p < 0.01). In the nonhuman primate investigation, cartilage repair scores were significantly better in the gel group compared to defects alone after 24 weeks (p < 0.001). Cell distribution analysis at 24 weeks showed that human cells remained within the transplanted defects only. A self-assembled, FCPC-based cartilage gel showed chondrogenic repair potential as well as adhesive properties, beneficial for cartilage repair.

Atypical infectious spondylitis with reduced bone marrow enhancement: "black vertebra sign".

BACKGROUND: A few patients suspected of having infectious spondylitis exhibited a reduced enhancement pattern on postcontrast T1-weighted (T1W) magnetic resonance imaging (MRI). PURPOSE: To investigate the characteristics of infectious spondylitis patients who exhibited reduced vertebral enhancement. MATERIAL AND METHODS: From January 2010 to November 2017, 456 patients with findings suspicious for infectious spondylitis on 706 postcontrast T1W imaging were retrospectively evaluated. When an affected vertebra exhibited markedly reduced enhancement compared to normal bone marrow (BM), the vertebra was termed a "black vertebra." MRI and computed tomography (CT) imaging findings within two-week intervals and the patients' clinical characteristics were reviewed. RESULTS: Ten patients (5 men, 5 women; mean age 66.4 years) whose MRI scans revealed the black vertebra sign were included. Among the 10 patients with black vertebrae, six patients exhibited signal voids in or around the affected vertebral bodies on T2-weighted (T2W) images. Eight patients showed air bubbles on CT images, suggestive of emphysematous infection. However, the typical image findings of infectious spondylitis were uncommon, namely, low BM signal intensity (SI) on T1W images (n=1) and intradiscal fluid-equivalent SI on T2W images (n=5) at an early stage. On follow-up MRI (average interval 7.2 weeks from initial MRI), available for five patients, marked progression of infection was evidenced by increased numbers of affected segments (n=3), low T1 SIs of the affected vertebrae (n=5), and increased contrast enhancement (n=3). Five patients underwent surgery to treat infections not controlled by antibiotics. CONCLUSION: A black vertebra sign on postcontrast T1W imaging seems to reflect an early emphysematous infection.

Ultrasound and Magnetic Resonance Imaging Features of Calcifying Aponeurotic Fibromas.

OBJECTIVES: To report characteristic imaging findings of calcifying aponeurotic fibromas (CAFs) on ultrasound (US) and magnetic resonance imaging (MRI). METHODS: Eight patients with CAF based on our institutional pathology database from 2000 to 2019 were consecutively included. Images were assessed as follows: with plain radiographs for the presence of soft tissue calcifications; with US for the presence of microlithiasis (a nonshadowing hyperechoic focus <3 mm) and discrete calcifications, size, location, margin, echogenicity, and relationship with surrounding structures; and with MRI for the presence of MRI microlithiasis (scattered tiny signal-void dots), margin, signal intensity, contrast enhancement pattern, and relationship with surrounding structures. RESULTS: Calcifying aponeurotic fibromas occurred most commonly in the foot (n = 5), followed by the hand, ankle, and knee, respectively. Half of the lesions (n = 4) showed intralesional calcifications on plain radiographs. On US, all lesions showed microlithiasis. They involved the subcutaneous (n = 5), perifascial (n = 2), and intermuscular (n = 1) layers. Margins were circumscribed (n = 3) or irregular (n = 5), whereas the echogenicity of the underlying tumor matrix was hyperechoic (n = 4), isoechoic (n = 2), or hypoechoic (n = 2). All lesions were abutting (n = 7) or encasing (n = 1) an adjacent tendon. On MRI, all CAFs showed tiny signal-void dots and irregular margins. Signal intensity was mostly hyperintense (n = 5) on T2-weighted images and all hypointense on T1-weighted images. Three lesions showed heterogeneous contrast enhancement, and 3 showed uneven marginal enhancement. CONCLUSIONS: A CAF should be considered a differential diagnosis if a soft tissue mass abutting or encasing the tendon or fascia shows US or MRI microlithiasis.

The Effect of Computed Tomography-Guided Botulinum Toxin Injection on Cervical Dystonia, Confirmed by a 9-Month Follow-Up Using Positron Emission Tomography/Computed Tomography.

Although accurate targeting of the causative muscles is of paramount importance in the treatment of focal dystonia, this is often challenging because of distortion of the affected anatomical structures and difficulty in proper positioning of injections. We report a case of idiopathic cervical dystonia that was treated by computed tomography-guided injection of botulinum toxin into multiple deep muscles. Based on clinical presentation of combined torticollis and retrocollis, and needle electromyography results, botulinum toxin was injected under electromyography guidance. This treatment resulted in no improvement. Subsequently, target muscles were identified using F-fludeoxyglucose fusion positron emission tomography/computed tomography. botulinum toxin was injected into the hypermetabolic muscles guided by computed tomography. This injection successfully relieved the symptoms, and nine months of follow-up using positron emission tomography/computed tomography confirmed that hypermetabolic muscles had been normalized. This case indicated that computed tomography guidance may facilitate accurate targeting of botulinum toxin injection. To the authors' knowledge, this is the first case reporting a positive effect of botulinum toxin on cervical dystonia symptoms that lasted 9 mos, confirmed by follow-up positron emission tomography/computed tomography.