MRI of the anatomical structures of the knee: the proton density-weighted fast spin-echo sequence<i>vs</i>the proton density-weighted fast-recovery fast spin-echo sequence

Tokuda, Osamu; Harada, Yasuhiro; Shiraishi, Gen; Motomura, Tetsuhisa; Fukuda, Kouji; Kimura, Masashi; Matsunaga, Naofumi

doi:10.1259/bjr/99570113

Cited by 6 publications

(6 citation statements)

References 19 publications

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“…A proton density weighted (PDW) contrast MRI sequence was chosen in this study as it is frequently used to assess pathologies of the knee in a clinical setting [ 11 , 21 ]. The PDW contrast provides data in which the ligaments, menisci and cartilage can be simultaneously assessed for diagnosis with a reasonable scanning time.…”

Section: Methodsmentioning

confidence: 99%

“…In this paper, we propose an automatic segmentation for trabecular and cortical bone of the femur and tibia in a clinically relevant MR sequence, proton density weighted contrast [ 21 ]. We use a local energy-based level set method to obtain a 3D rough segmentation of trabecular bone and correct the image data from the inhomogeneity problem.…”

Section: Introductionmentioning

confidence: 99%

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Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee

Chen

Sprengers

Kang

2018

Med Biol Eng Comput

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Patient-specific implant design and pre- and intra-operative planning is becoming increasingly important in the orthopaedic field. For clinical feasibility of these techniques, fast and accurate segmentation of bone structures from MRI is essential. However, manual segmentation is time intensive and subject to inter- and intra-observer variation. The challenge in developing automatic segmentation algorithms for MRI data mainly exists in the inhomogeneity problem and the low contrast among cortical bone and adjacent tissues. In this paper, we proposed a method for automatic segmentation of knee bone structures for MRI data with a 3D local intensity clustering-based level set and a novel approach to determine the cortical boundary utilizing the normal vector of the trabecular surface. Application to clinical imaging data shows that our method is robust to MRI inhomogeneity. In comparing our method to manual segmentation in 18 femurs and tibiae, we found a dice similarity coefficient (DSC) of 0.9611 ± 0.0052 for the femurs and 0.9591 ± 0.0173 for tibiae. The average surface distance error was 0.4649 ± 0.1430 mm for the femurs and 0.4712 ± 0.2113 mm for the tibiae. The results of the automatic technique thus strongly corresponded to the manual segmentation using less than 3% of the time and with virtually no workload. Graphical abstract ᅟ

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee

Chen

Sprengers

Kang

2018

Med Biol Eng Comput

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“…In the TMJ MRI protocol, PD- or T1-WI is mainly used to diagnose disc malposition. 1 2 3 In a normal joint, the disc is sometimes difficult to identify, as it is located between the cortex of the mandibular condyle and articular eminence in PD image. When the disc is displaced, it is completely surrounded by soft tissues only and is rather clearly visible.…”

Section: Discussionmentioning

confidence: 99%

“…PD-WI is generally used as a sequence for disc and ligament evaluation in joints throughout the body. 3 T2-WI, as a fluid-sensitive sequence, best depicts joint effusion as areas of hyperintensity. 1 2 …”

Section: Introductionmentioning

confidence: 99%

Synthesis of T2-weighted images from proton density images using a generative adversarial network in a temporomandibular joint magnetic resonance imaging protocol

Lee

Choi

et al. 2022

Imaging Sci Dent

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Purpose This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint (TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen’s ĸ coefficient. Results The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement (ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement (ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

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“…This signal intensity pattern was similar to that described in the limbs of horse (Smith & Wright, 2012), cattle (Raji et al, 2009) and camel (Hagag & Tawfiek, 2018).In this protocol, using the density of hydrogen atoms in each tissue, the desired contrast is created and that is why the bone, which has a lower density of hydrogen atoms compared to joint fluid, is seen hypodense. For this reason, the PD FATSAT protocol is the first choice for examining the limb joints (Tokuda et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Gross anatomy, computed tomography, magnetic resonance imaging and bone mineral densitometry of the ovine metacarpo/metatarsophalangeal joint

Ghaderi

Goodarzi

2022

Anat Histol Embryol

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This study was aimed to provide anatomical atlas of the ovine metacarpo/metatarsophalangeal joints using computed tomography (CT) scan and magnetic resonance imaging (MRI), as well as to investigate bone mineral density (BMD) and morphometric features of this joint. The limbs of twenty adult Sanjabi sheep were examined. Imaging was performed using a 16‐slice multi‐detector CT scanner and a 1.5 Tesla MRI scanner. The obtained images were correlated with corresponding anatomical sections. BMD was measured by Dual Energy X‐ray Absorptiometry (DEXA) method. Also morphometric features included distance between metacarpal and metatarsal heads, width of metacarpal and metatarsal head, length, width and the height of the proximal sesamoid bones were measured. In MRI images, compact bones, ligaments and tendons showed less signal intensity (hypointense). The fatty tissue and bone marrow had more signal intensity (hyperintense), but articular cartilage and synovial fluid showed moderate signal intensity. BMD in the left hind limb was significantly higher than other three limbs (p ≤ 0.05). The length of proximal sesamoid bones in left forelimb was higher than right forelimb (p ≤ 0.05). The thickness of proximal sesamoid bones in left limbs was higher than those in their counterparts (p ≤ 0.05). The width of the medial head in the forelimbs was significantly greater than the hind limbs (p ≤ 0.05). The present results might be useful in managing the clinical techniques on this joint. Larger volume of the proximal sesamoid bones and wider medial head in the forelimbs compared to the hindlimbs impel this speculation that the centre of gravity is closer to the forelimbs.

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MRI of the anatomical structures of the knee: the proton density-weighted fast spin-echo sequencevsthe proton density-weighted fast-recovery fast spin-echo sequence

Cited by 6 publications

References 19 publications

Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee

Automated segmentation of trabecular and cortical bone from proton density weighted MRI of the knee

Synthesis of T2-weighted images from proton density images using a generative adversarial network in a temporomandibular joint magnetic resonance imaging protocol

Gross anatomy, computed tomography, magnetic resonance imaging and bone mineral densitometry of the ovine metacarpo/metatarsophalangeal joint

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