Naveen Subhas1, Joshua M Polster1, Nancy A Obuchowski2, Andrew N Primak3, Frank F Dong4, Brian R Herts1, Joseph P Iannotti5. 1. 1 Department of Radiology, Cleveland Clinic, 9500 Euclid Ave, Ste A21, Cleveland, OH 44195. 2. 2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH. 3. 3 Siemens Healthcare, Malvern, PA. 4. 4 Section of Medical Physics, Cleveland Clinic, Cleveland, OH. 5. 5 Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
Abstract
OBJECTIVE: The purpose of this study was to compare iterative metal artifact reduction (iMAR), a new single-energy metal artifact reduction technique, with filtered back projection (FBP) in terms of attenuation values, qualitative image quality, and streak artifacts near shoulder and hip arthroplasties and observer ability with these techniques to detect pathologic lesions near an arthroplasty in a phantom model. MATERIALS AND METHODS: Preoperative and postoperative CT scans of 40 shoulder and 21 hip arthroplasties were reviewed. All postoperative scans were obtained using the same technique (140 kVp, 300 quality reference mAs, 128 × 0.6 mm detector collimation) on one of three CT scanners and reconstructed with FBP and iMAR. The attenuation differences in bones and soft tissues between preoperative and postoperative scans at the same location were compared; image quality and streak artifact for both reconstructions were qualitatively graded by two blinded readers. Observer ability and confidence to detect lesions near an arthroplasty in a phantom model were graded. RESULTS: For both readers, iMAR had more accurate attenuation values (p < 0.001), qualitatively better image quality (p < 0.001), and less streak artifact (p < 0.001) in all locations near arthroplasties compared with FBP. Both readers detected more lesions (p ≤ 0.04) with higher confidence (p ≤ 0.01) with iMAR than with FBP in the phantom model. CONCLUSION: The iMAR technique provided more accurate attenuation values, better image quality, and less streak artifact near hip and shoulder arthroplasties than FBP; iMAR also increased observer ability and confidence to detect pathologic lesions near arthroplasties in a phantom model.
OBJECTIVE: The purpose of this study was to compare iterative metal artifact reduction (iMAR), a new single-energy metal artifact reduction technique, with filtered back projection (FBP) in terms of attenuation values, qualitative image quality, and streak artifacts near shoulder and hip arthroplasties and observer ability with these techniques to detect pathologic lesions near an arthroplasty in a phantom model. MATERIALS AND METHODS: Preoperative and postoperative CT scans of 40 shoulder and 21 hip arthroplasties were reviewed. All postoperative scans were obtained using the same technique (140 kVp, 300 quality reference mAs, 128 × 0.6 mm detector collimation) on one of three CT scanners and reconstructed with FBP and iMAR. The attenuation differences in bones and soft tissues between preoperative and postoperative scans at the same location were compared; image quality and streak artifact for both reconstructions were qualitatively graded by two blinded readers. Observer ability and confidence to detect lesions near an arthroplasty in a phantom model were graded. RESULTS: For both readers, iMAR had more accurate attenuation values (p < 0.001), qualitatively better image quality (p < 0.001), and less streak artifact (p < 0.001) in all locations near arthroplasties compared with FBP. Both readers detected more lesions (p ≤ 0.04) with higher confidence (p ≤ 0.01) with iMAR than with FBP in the phantom model. CONCLUSION: The iMAR technique provided more accurate attenuation values, better image quality, and less streak artifact near hip and shoulder arthroplasties than FBP; iMAR also increased observer ability and confidence to detect pathologic lesions near arthroplasties in a phantom model.
Authors: Eric T Ricchetti; Bong-Jae Jun; Yuxuan Jin; Jason C Ho; Thomas E Patterson; Jarrod E Dalton; Kathleen A Derwin; Joseph P Iannotti Journal: J Bone Joint Surg Am Date: 2021-08-04 Impact factor: 6.558
Authors: Angeliki Neroladaki; Steve Philippe Martin; Ilias Bagetakos; Diomidis Botsikas; Marion Hamard; Xavier Montet; Sana Boudabbous Journal: Medicine (Baltimore) Date: 2019-02 Impact factor: 1.817