To compare computer-based 3D-analysis for quantification of the femorotibial joint space width (JSW) using weight-bearing cone beam CT (WB-CT), non-weight-bearing multi-detector CT (NWB-CT), and ...weight-bearing conventional radiographs (WB-XR).
Twenty-six participants prospectively underwent NWB-CT, WB-CT, and WB-XR of the knee. For WB-CT and NWB-CT, the average and minimal JSW was quantified by 3D-analysis of the minimal distance of any point of the subchondral tibial bone surface and the femur. Associations with mechanical leg axes and osteoarthritis were evaluated. Minimal JSW of WB-CT was further compared to WB-XR. Two-tailed p-values of <0.05 were considered significant.
Significant differences existed of the average medial and lateral JSW between WB-CT and NWB-CT (medial: 4.7 vs 5.1 mm P = 0.028, lateral: 6.3 vs 6.8 mm P = 0.008). The minimal JSW on WB-XR (medial:3.1 mm, lateral:5.8 mm) were significantly wider compared to WB-CT and NWB-CT (both medial:1.8 mm, lateral:2.9 mm, all p < 0.001), but not significantly different between WB-CT and NWB-CT (all p ≥ 0.869). Significant differences between WB-CT and NWB-CT existed in participants with varus knee alignment for the average and the minimal medial JSW (p = 0.004 and p = 0.011) and for participants with valgus alignment for the average lateral JSW (p = 0.013). On WB-CT, 25% of the femorotibial compartments showed bone-on-bone apposition, which was significantly higher when compared to NWB-CT (10%,P = 0.008) and WB-XR (8%,P = 0.012).
Combining WB-CT with 3D-based assessment allows detailed quantification of the femorotibial joint space and the effect of knee alignment on JSW. WB-CT demonstrates significantly more bone-on-bone appositions, which are underestimated or even undetectable on NWB-CT and WB-XR.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
OBJECTIVESThe aim of this study was to clinically validate a Deep Convolutional Neural Network (DCNN) for the detection of surgically proven anterior cruciate ligament (ACL) tears in a large patient ...cohort and to analyze the effect of magnetic resonance examinations from different institutions, varying protocols, and field strengths.
MATERIALS AND METHODSAfter ethics committee approval, this retrospective analysis of prospectively collected data was performed on 512 consecutive subjects, who underwent knee magnetic resonance imaging (MRI) in a total of 59 different institutions followed by arthroscopic knee surgery at our institution. The DCNN and 3 fellowship-trained full-time academic musculoskeletal radiologists evaluated the MRI examinations for full-thickness ACL tears independently. Surgical reports served as the reference standard. Statistics included diagnostic performance metrics, including sensitivity, specificity, area under the receiver operating curve (“AUC ROC”), and kappa statistics. P values less than 0.05 were considered to represent statistical significance.
RESULTSAnterior cruciate ligament tears were present in 45.7% (234/512) and absent in 54.3% (278/512) of the subjects. The DCNN had a sensitivity of 96.1%, which was not significantly different from the readers (97.5%–97.9%; all P ≥ 0.118), but significantly lower specificity of 93.1% (readers, 99.6%–100%; all P < 0.001) and “AUC ROC” of 0.935 (readers, 0.989–0.991; all P < 0.001) for the entire cohort. Subgroup analysis showed a significantly lower sensitivity, specificity, and “AUC ROC” of the DCNN for outside MRI (92.5%, 87.1%, and 0.898, respectively) than in-house MRI (99.0%, 94.4%, and 0.967, respectively) examinations (P = 0.026, P = 0.043, and P < 0.05, respectively). There were no significant differences in DCNN performance for 1.5-T and 3-T MRI examinations (all P ≥ 0.753, respectively).
CONCLUSIONSDeep Convolutional Neural Network performance of ACL tear diagnosis can approach performance levels similar to fellowship-trained full-time academic musculoskeletal radiologists at 1.5 T and 3 T; however, the performance may decrease with increasing MRI examination heterogeneity.
Objective
To prospectively assess the evolution of postoperative MRI findings in asymptomatic patients after total hip arthroplasty (THA) over 24 months (mo).
Methods
This prospective cohort study ...included 9 asymptomatic patients (56.7 ± 15.0 years) after THA. Metal artifact–reduced 1.5-T MRI was performed at 3, 6, 12, and 24 mo after surgery. The femoral stem and acetabular cup were assessed by two readers for bone marrow edema (BME), periprosthetic bone resorption, and periosteal edema in addition to periarticular soft tissue edema and joint effusion.
Results
BME was common around the femoral stem in all Gruen zones after 3 mo (range: 50–100%) and 6 mo (range: 33–100%) and in the acetabulum in DeLee and Charnley zone II after 3 mo (100%) and 6 mo (33%). BME decreased substantially after 12 mo (range: 0–78%) and 24 mo (range: 0–50%), may however persist in particular in Gruen zones 1 + 7. Periosteal edema along the stem was common 3 mo postoperatively (range: 63–75%) and rare after 24 mo: 13% only in Gruen zones 2 and 5. Twelve months and 24 mo postoperatively, periprosthetic bone resorption was occasionally present around the femoral stem (range: 11–33% and 13–38%, respectively). Soft tissue edema occurred exclusively along the surgical access route after 3 mo (100%) and 6 mo (89%) and never at 12 mo or 24 mo (0%).
Conclusion
Around the femoral stem, BME (33–100%) and periosteal edema (0–75%) are common until 6 mo after THA, decreasing substantially in the following period, may however persist up to 24 mo (BME: 0–50%; periosteal edema: 0–13%) in few non-adjoining Gruen zones. Soft tissue edema along the surgical access route should have disappeared 12 mo after surgery.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
Objective
To clinically validate a fully automated deep convolutional neural network (DCNN) for detection of surgically proven meniscus tears.
Materials and methods
One hundred consecutive patients ...were retrospectively included, who underwent knee MRI and knee arthroscopy in our institution. All MRI were evaluated for medial and lateral meniscus tears by two musculoskeletal radiologists independently and by DCNN. Included patients were not part of the training set of the DCNN. Surgical reports served as the standard of reference. Statistics included sensitivity, specificity, accuracy, ROC curve analysis, and kappa statistics.
Results
Fifty-seven percent (57/100) of patients had a tear of the medial and 24% (24/100) of the lateral meniscus, including 12% (12/100) with a tear of both menisci. For medial meniscus tear detection, sensitivity, specificity, and accuracy were for reader 1: 93%, 91%, and 92%, for reader 2: 96%, 86%, and 92%, and for the DCNN: 84%, 88%, and 86%. For lateral meniscus tear detection, sensitivity, specificity, and accuracy were for reader 1: 71%, 95%, and 89%, for reader 2: 67%, 99%, and 91%, and for the DCNN: 58%, 92%, and 84%. Sensitivity for medial meniscus tears was significantly different between reader 2 and the DCNN (
p
= 0.039), and no significant differences existed for all other comparisons (all
p
≥ 0.092). The AUC-ROC of the DCNN was 0.882, 0.781, and 0.961 for detection of medial, lateral, and overall meniscus tear. Inter-reader agreement was very good for the medial (kappa = 0.876) and good for the lateral meniscus (kappa = 0.741).
Conclusion
DCNN-based meniscus tear detection can be performed in a fully automated manner with a similar specificity but a lower sensitivity in comparison with musculoskeletal radiologists.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
Objectives
To compare ultra-low-dose CT (ULD-CT) of the osseous pelvis with tin filtration to standard clinical CT (CT), and to assess the quality of computed virtual pelvic radiographs (VRs).
...Methods
CT protocols were optimized in a phantom and three pelvic cadavers. Thirty prospectively included patients received both standard CT (automated tube voltage selection and current modulation) and tin-filtered ULD-CT of the pelvis (Sn140kV/50mAs). VRs of ULD-CT data were computed using an adapted cone beam–based projection algorithm and were compared to digital radiographs (DRs) of the pelvis. CT and DR dose parameters and quantitative and qualitative measures (1 = worst, 4 = best) were compared. CT and ULD-CT were assessed for osseous pathologies.
Results
Dose reduction of ULD-CT was 84% compared to CT, with a median effective dose of 0.38 mSv (quartile 1–3: 0.37–0.4 mSv) versus 2.31 mSv (1.82–3.58 mSv;
p
< .001), respectively. Mean dose of DR was 0.37 mSv (± 0.14 mSv). The median signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were significantly higher for CT (64.3 and 21.5, respectively) compared to ULD-CT (50.4 and 18.8;
p
≤ .01), while ULD-CT was significantly more dose efficient (figure of merit (FOM) 927.6) than CT (FOM 167.6;
p
< .001). Both CT and ULD-CT were of good image quality with excellent depiction of anatomy, with a median score of 4 (4–4) for both methods (
p
= .1). Agreement was perfect between both methods regarding the prevalence of assessed osseous pathologies (
p
> .99). VRs were successfully calculated and were equivalent to DRs.
Conclusion
Tin-filtered ULD-CT of the pelvis at a dose equivalent to standard radiographs is adequate for assessing bone anatomy and osseous pathologies and had a markedly superior dose efficiency than standard CT.
Key Points
• Ultra-low-dose pelvic CT with tin filtration (0.38 mSv) can be performed at a dose of digital radiographs (0.37 mSv), with a dose reduction of 84% compared to standard CT (2.31 mSv).
• Tin-filtered ultra-low-dose CT had lower SNR and CNR and higher image noise than standard CT, but showed clear depiction of anatomy and accurate detection of osseous pathologies.
• Virtual pelvic radiographs were successfully calculated from ultra-low-dose CT data and were equivalent to digital radiographs.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
Objective
In total hip arthroplasty (THA), surgeons attempt to achieve a physiological antetorsion. However, postoperative antetorsion of the femoral stem is known to show large variabilities. The ...purpose of this study was to assess whether postoperative antetorsion is influenced by stem design or cementation.
Materials and methods
This retrospective study included 227 patients with a hip prosthesis with five different stem designs (S1: short curved, S2 and S3: standard straight, S4: standard straight collared, S5: cemented straight), who had metal suppressed 1.5T-MRI of the hip between February 2015 and October 2019. Measurement of femoral antetorsion was done independently by two fellowship-trained radiologists on axial images by measuring the angle between the long axis of the femoral neck and the posterior condylar tangent of the knee. Measured angles in the different groups were compared using the
t
test for independent samples.
Results
The cementless collared stem S4 showed the highest antetorsion with 18.1° (± 10.5°; range –10°–45°), which was significantly higher than the antetorsion of the collarless S3 with 13.3° (± 8.4°; − 4°–29°) and the cemented S5 with 12.7° (± 7.7°; − 3°–27°) with
p
= 0.012 and
p
= 0.007, respectively. S1 and S2 showed an antetorsion of 14.8° (± 10.0°; 1°–37°) and 14.1° (± 12.2°; − 20°–41°). The torsional variability of the cementless stems (S1–4) was significantly higher compared with that of the cemented S5 with a combined standard deviation of 10.5° and 7.7° (
p
= 0.019).
Conclusion
Prosthesis design impacts the postoperative femoral antetorsion, with the cementless collared stem showing the highest antetorsion. Cemented stems demonstrated significantly lower variability, suggesting the lowest rate of inadvertent malrotation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
OBJECTIVESThe aim of this study was to assess the interreader agreement and diagnostic accuracy of morphologic magnetic resonance imaging (MRI) analysis and quantitative MRI-based texture analysis ...(TA) for grading of cartilaginous bone tumors.
MATERIALS AND METHODSThis retrospective study was approved by our local ethics committee. Magnetic resonance imaging scans of 116 cartilaginous bone neoplasms were included (53 chondromas, 26 low-grade chondrosarcomas, 37 high-grade chondrosarcomas). Two musculoskeletal radiologists blinded to patient data separately analyzed 14 morphologic MRI features consisting of tumor and peritumoral characteristics. In addition, 2 different musculoskeletal radiologists separately performed TA including 19 quantitative TA parameters in a similar fashion. Interreader reliability, univariate, multivariate, and receiver operating characteristics analyses were performed for MRI and TA parameters separately and for combined models to determine independent predictors and diagnostic accuracy for grading of cartilaginous neoplasms. P values of 0.05 and less were considered statistically significant.
RESULTSBetween both readers, MRI and TA features showed a mean kappa value of 0.49 (range, 0.08–0.82) and a mean intraclass correlation coefficient of 0.79 (range, 0.43–0.99), respectively. Independent morphological MRI predictors for grading of cartilaginous neoplasms were bone marrow edema, soft tissue mass, maximum tumor extent, and active periostitis, whereas TA predictors consisted of short-run high gray-level emphasis, skewness, and gray-level and run-length nonuniformity. Diagnostic accuracies for differentiation of benign from malignant as well as for benign from low-grade cartilaginous lesions were 87.0% and 77.4% using MRI predictors exclusively, 89.8% and 89.5% using TA predictors exclusively, and 92.9% and 91.2% using a combined model of MRI and TA predictors, respectively. For differentiation of low-grade from high-grade chondrosarcoma, no statistically significant independent TA predictors existed, whereas a model containing MRI predictors exclusively had a diagnostic accuracy of 84.8%.
CONCLUSIONSTexture analysis improves diagnostic accuracy for differentiation of benign and malignant as well as for benign and low-grade cartilaginous lesions when compared with morphologic MRI analysis.
Objective
To evaluate the prevalence, morphology, and clinical significance of a repeatedly observed yet not examined circumscript osseous defect at the anteroinferior aspect of the femoral head, ...termed femoral head defect.
Materials and methods
Retrospective study with approval of the institutional review board. There was informed consent by all individuals. Magnetic resonance imaging (MRI) hip examinations of 970 individuals (age 15 to 55) were analyzed for femoral head defect. Patients with femoral head defect were matched for age and gender with patients without defect. Two readers independently assessed MRI images regarding presence, location, and morphology of the defect. MR images and radiographs were analyzed for findings of femoroacetabular impingement (FAI). Femoral torsion was measured. Independent
t
test and chi-square test were used for statistics.
Results
Sixty-eight (7%) of 970 MRI examinations exhibited a femoral head defect in an anteroinferior location of the femoral head (29/400 men, 7.3%; 39/570 women, 6.8%;
p =
0.8). The most frequent morphology of femoral head defect was type I, dent-like (34; 50%), followed by type II, crater-like (27; 40%), and III, cystic (7; 10%). Femoral head defect was slightly more common on the right hip (39 individuals; 57%) compared to left (29 individuals; 43%), non-significantly (
p =
0.115). There was no association between FAI or its subtypes and the presence of femoral head defect (
p =
0.890). Femoral antetorsion was reduced in patients with femoral head defect (12.9° ± 8.6) compared to patients without defect (15.2° ± 8.5), without statistical significance (
p =
0.121).
Conclusion
The femoral head defect is a common finding in MRI examinations of the hip and is situated in the anteroinferior location. There was no association with FAI yet a non-significant trend towards lower femoral antetorsion in patients with femoral head defects.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
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