Comparing Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) Fat suppression techniques in Magnetic Resonance Imaging of knee joint

Comparing Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) Fat suppression techniques in Magnetic Resonance Imaging of knee joint | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparing Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) Fat suppression techniques in Magnetic Resonance Imaging of knee joint Govindaraj S, Dr. Lavanya Dharmalingam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8749005/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Magnetic Resonance Imaging (MRI) is regarded as the gold standard for musculoskeletal imaging due to its excellent soft-tissue contrast and multiplanar capabilities. Nevertheless, the high signal intensity of fat often obscures important anatomical and pathological details, underscoring the need for robust fat suppression techniques. Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) are widely applied frequency-selective inversion recovery methods. Objective: This study aims to compare SPIR and SPAIR fat suppression techniques in MRI of the knee joint to determine which provides superior overall image quality for clinical application. Materials and methods: This cross-sectional study was conducted in the Department of Radiodiagnosis, Aarupadai Veedu Medical College and Hospital, Puducherry. A total of 72 patients referred for knee MRI were included using purposive sampling. Imaging was performed on a 1.5T MRI system with a dedicated knee coil, and both PDW-SPIR and PDW-SPAIR fat suppression sequences were obtained under identical parameters. Images were anonymized and independently reviewed by two experienced radiologists. Descriptive and inferential Statistical analysis was performed using the SPSS software. Results: SPAIR sequences consistently outperformed SPIR in terms of fat suppression homogeneity, reduction of artifacts, and visualization of key anatomical structures. Structures such as the cruciate ligaments, menisci, articular cartilage, and periarticular soft tissues were more distinctly delineated on PDW - SPAIR images. The differences in image quality were statistically significant (p < 0.05). Inter-observer reliability was excellent (κ = 0.88–1.00), confirming consistent evaluations across readers. Conclusion: SPAIR provides superior fat suppression and overall image quality compared to SPIR in knee MRI. SPAIR enhances diagnostic confidence in musculoskeletal imaging. Its routine incorporation into knee MRI protocols is recommended to improve the detection and assessment of subtle joint pathologies. Knee joint SPIR MRI SPAIR MRI Fat suppression Musculoskeletal imaging Figures Figure 1 1. Introduction Magnetic Resonance Imaging (MRI) is a revolutionary advancement in diagnostic Radiology [ 1 ]. Magnetic resonance imaging (MRI) is an imaging technique without ionizing radiation. MRI utilizes strong magnetic fields and radiofrequency (RF) pulses to produce detailed anatomical images [ 2 ]. In 1983, MRI first began to be used for the diagnostic assessment of the knee joint. The introduction of MRI has transformed the practice of musculoskeletal imaging, particularly that of internal derangements of the knee (e.g., meniscal and ligament injuries). The ability of MRI to create thin-section images with high-contrast resolution makes this modality the imaging modality of choice to evaluate many knee pathologies [ 3 ]. The knee is a mechanically complex joint that behaves as a modified hinge with great motion potential throughout its available planes of movement. The knee is mainly responsible for flexion and extension in the sagittal plane and supports varus and valgus movements in the frontal plane [ 4 ]. The patellar ligament, anterior and posterior cruciate ligaments (ACL & PCL), and the medial and lateral collateral ligaments (MCL & LCL) are the main ligaments that provide stability at the knee joint [ 5 ]. The infrapatellar fat pad or Hoffa's fat pad was first documented in 1904; it is located below the patella and is intracapsular but not intracapsular. It is a filler of interstitial spaces during movement, stabilizer of the patella, and limits mechanical compression on the knee joint [ 6 ]. Synovial fluid, particularly its hyaluronic acid, is important in reducing joint friction and smooth articulation [ 7 ]. MRI adds significant value to early diagnosis of knee pain by identifying early soft tissue and joint abnormalities that are not identifiable on plain x ray. Although the detection of early arthritis may not provide better sensitivity compared to clinical or radiographic methods, MRI is invaluable at identifying associated findings, including cartilage damage and bone marrow edema, which can assist with treatment planning [ 8 ]. Spectral Pre-saturation with Inversion Recovery (SPIR) is utilized to suppress fat signals in MR imaging and combines the key components of both spectral fat saturation and inversion recovery. SPIR is a chemical shift selective (CHESS) method which utilizes an inversion pulse selectively to suppress the fat signal while enabling the rest of the anatomy of interest to be preserved. Originally designed by Oh et al. for spine imaging [ 9 ]. SPIR works by employing a frequency-specific 180° radiofrequency (RF) inversion pulse targeting solely fat protons where these protons utilize the frequency (chemical shift) difference as fat and water differ. In this manner the longitudinal magnetization of the fat protons are inverted. After a designated time (the inversion time or TI) during which the longitudinal magnetization of the fat has ultimately decayed to zero, a 90° RF excitation pulse is transmitted specifically targeting fat, and at that moment, the fat magnetization is null and hence there is zero contribution of fat to the transverse signal used to generate fat in the final image indicating fat suppression was successful [ 10 ]. However, SPIR also has certain limitations, The technique is sensitive to variations in both the main magnetic field (B₀) and the radiofrequency field (B₁). Its effectiveness depends on accurate separation between fat and water resonance frequencies, which may be difficult to achieve in low-field scanners or poorly shimmed systems [ 11 ]. As MRI technology has advanced, fat suppression techniques have significantly improved images and lesion detection. Among these Spectral Adiabatic Inversion Recovery (SPAIR). SPAIR is recognized as a reliable and effective fat signal suppression technique. Overall, SPAIR is a hybrid of CHESS's spectral selectivity and STIR's inversion recovery that utilizes adiabatic radiofrequency (RF) pulses to produce more uniform fat signal suppression across various regions [ 12 ]. One of the good aspects of SPAIR is the application's use of adiabatic RF pulses. An adiabatic RF pulse applies frequency and percentage changes to keep the magnetization stable even with B1 field in-homogeneity. Thus, SPAIR is more consistent and provides a more homogeneous fat suppression when compared to traditional frequency selective methods such as FatSat, especially in areas that are anatomically complicated or exhibit magnetic non-uniformity, such as the spine or pelvis [ 13 ]. SPAIR has been clinically applied with great benefit in musculoskeletal imaging. It has allowed for better demonstrations of soft tissue structures including ligaments, cartilage, and joint capsules especially around joints like the knee [ 14 ]. While SPAIR has prolonged scan times and higher specific absorption rates (SAR) with larger flip angles, the diagnostic advantages of this technique often outweigh its limitations [ 15 ]. 2. Methods and Materials This study was a hospital-based cross-sectional study conducted in the Department of Radiodiagnosis, Aarupadai Veedu Medical College and Hospital, Puducherry, over a period of six months. A total of 72 patients referred for MRI of the knee joint were selected using purposive sampling. Ethical clearance was obtained, and written informed consent was taken from all participants. Patients with metal implants, first-trimester pregnancy, claustrophobia, or those unwilling to participate were excluded from the study. All MRI scans were performed on a Philips Achieva 1.5 Tesla MRI scanner using a dedicated knee coil to ensure high-quality images. Patients were positioned supine, head-first, with the mid-knee joint as the landmark. Routine knee MRI sequences such as proton density (PDW) images were obtained in axial, sagittal, and coronal planes. Along with these, SPIR (Spectral Presaturation with Inversion Recovery) and SPAIR (Spectral Adiabatic Inversion Recovery) sagittal proton density-weighted (PDW) images were also acquired under identical imaging parameters to allow direct comparison between the two fat suppression techniques. All images were anonymized and independently reviewed by two experienced radiologists in a double-blind manner. The evaluation focused on anatomical clarity, uniformity of fat suppression, and presence of artifacts in key structures such as the femoral condyles, tendons, ligaments, menisci, cartilage, patella, and Hoffa’s fat pad. Each structure was scored using a three-point Likert scale, where higher scores represented superior clarity and fat suppression. The data were compiled in Microsoft Excel and analyzed using IBM SPSS software. Descriptive statistics were used to summarize the findings, while Wilcoxon signed-rank tests were applied to compare SPIR and SPAIR image quality. Inter-observer agreement was assessed using the kappa (κ) coefficient. A p-value < 0.05 was considered statistically significant. 3. Results The research was carried out on 72 participants who underwent MRI examination of the knee joint, with an age range from 10 to 69 years. Among them, 47 were male (65.3%) and 25 were female (34.7%). The majority of participants were within the 20–39 years age group (Tables 1 & 2). Table-1 Demographic Profile of study participants Parameters No. of Participants (n = 72) Percentage (%) Male 47 65.3 Female 25 34.7 Total 72 100 Table-2 Age group distribution of the participants Age Group Count Percentage 10–19 8 11.1% 20–29 20 27.8% 30–39 20 27.8% 40–49 9 12.5% 50–59 10 13.9% 60–69 5 6.9% All anatomical structures showed statistically significant improvement in image clarity with the SPAIR sequence compared to SPIR, as confirmed by the Wilcoxon signed-rank test (p < 0.001) (Table 3 ). The mean clarity scores for SPIR and SPAIR sequences across major knee joint anatomical structures. SPAIR demonstrated consistently higher mean scores than SPIR, indicating more uniform fat suppression and clearer visualization of soft-tissue details. These findings highlight SPAIR’s superior diagnostic image quality in knee MRI (Table 4 ). And the inter-observer agreement between the two radiologists for SPIR and SPAIR sequences were evaluated by using Cohen’s κ statistic. Image interpretation was based on the clarity of anatomical structures. All κ values indicate excellent reliability, confirming consistent image-quality assessments across readers. SPAIR sequences demonstrated marginally higher agreement, reflecting superior inter-reader consistency. κ values were interpreted according to Landis and Koch (1977), where κ ≥ 0.81 denotes excellent agreement (Table 5 ). Table 3 Comparison of SPIR and SPAIR sequences Structure p-value Femoral condyle < 0.001 Tendons < 0.001 Ligaments < 0.001 Meniscus < 0.001 Cartilage < 0.001 Hoffa’s fat pad < 0.001 Table 4 Comparison of mean clarity scores between SPIR and SPAIR sequences Anatomical Structure SPIR (Mean) SPAIR (Mean) Femoral condyle 2.67 2.92 Tendons 2.55 2.93 Patella 2.53 2.88 Ligaments 2.54 2.91 Meniscus 2.57 2.92 Cartilage 2.56 2.89 Hoffa’s fat pad 2.64 2.95 Table 5 Inter-observer reliability for SPIR and SPAIR sequences in evaluation of knee MRI structures Anatomical Structure SPIR (κ Value) SPAIR (κ Value) Femoral condyle 0.88 0.92 Tendons 0.89 0.93 Patella 0.87 0.91 Ligaments 0.90 0.94 Meniscus 0.91 0.96 Cartilage 0.89 0.93 Hoffa’s fat pad 0.90 1.00 4. Discussion This study comprehensively compared Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) fat suppression techniques in knee joint MRI, with a focus on their effectiveness in visualizing key anatomical structures, including the femoral condyles, tendons, patella, ligaments, menisci, articular cartilage, and Hoffa’s fat pad. The findings of the present study are in strong agreement with previously published literature. Indrati et al. (2017) in a comparative study of SPIR and SPAIR in wrist MRI, reported that SPAIR yielded superior anatomical detail due to its adiabatic inversion pulse, which provides uniform fat suppression while minimizing artifacts [ 16 ]. Similarly, Dalto et al. (2020) in their evaluation of sacroiliac joint imaging, demonstrated that T2-weighted SPAIR sequences achieved higher signal-to-noise ratios (SNR) and improved image contrast compared to STIR, consistent with the enhanced diagnostic confidence observed in the current study [ 17 ]. Kishida et al. (2018) also demonstrated at 3T that SPAIR achieved higher fat-to-noise ratios and more reliable suppression than SPIR, while maintaining reproducibility an outcome that parallels the high inter-reader agreement (κ = 0.88–1.00) was documented [ 18 ]. Similarly, Brandão et al. (2015) in their evaluation of breast diffusion-weighted MRI, reported that SPAIR produced higher lesion visibility in specific cases compared with STIR, underscoring SPAIR’s broader utility across different anatomical regions and modalities [ 19 ]. Evidence from non-musculoskeletal applications also corroborates these findings. Le Bihan et al. (2025) demonstrated SPAIR’s superior performance in breast MRI, achieving more uniform fat suppression in regions affected by field inhomogeneities [ 20 ]. The consistency and reproducibility observed in this study reinforce the growing consensus in the literature that SPAIR should be considered the preferred fat suppression technique in clinical musculoskeletal MRI protocols, particularly for high-resolution imaging of complex anatomical structures such as the knee joint. 5. Strengths and Limitations This study’s structured comparative design directly evaluated SPIR and SPAIR fat-suppression techniques under standardized 1.5 T MRI parameters, ensuring objective assessment. A sample of 72 subjects provided adequate statistical power, and analysis of key knee structures enabled a comprehensive comparison of image clarity. Robust statistical methods and excellent inter-observer agreement (κ = 0.88–1.00) reinforced the reliability of findings, confirming SPAIR’s superior diagnostic performance. Limitations include its single-centre design using only a 1.5 T scanner, reliance on a subjective 3-point scale without quantitative metrics (SNR, CNR), and restriction to the knee joint without clinical or surgical correlation. SPAIR also required a slightly longer scan time (≈ 2 min more than SPIR), which may affect workflow in high-volume settings. 6. Conclusion This study demonstrated that the SPAIR fat-suppression technique provides superior image quality compared to SPIR in knee MRI. Using standardized 1.5 T imaging parameters, SPAIR produced more homogeneous fat suppression, fewer artifacts, and clearer visualization of critical anatomical structures, including the menisci, cruciate ligaments, cartilage, and periarticular soft tissues. These findings highlight SPAIR’s potential to enhance diagnostic confidence and accuracy in musculoskeletal imaging, particularly for subtle ligamentous and cartilage pathologies. Overall, SPAIR can be recommended as a preferred fat-suppression technique for routine knee MRI examinations, balancing diagnostic quality and clinical practicality. Abbrevations ACL – Anterior Cruciate Ligament B₀ – Main Magnetic Field B₁ – Radiofrequency Magnetic Field CHESS – Chemical Shift Selective CNR – Contrast-to-Noise Ratio LCL – Lateral Collateral Ligament MCL – Medial Collateral Ligament MRI – Magnetic Resonance Imaging PD – Proton Density PDW – Proton Density Weighted PCL – Posterior Cruciate Ligament RF – Radiofrequency SAR – Specific Absorption Rate SNR – Signal-to-Noise Ratio SPAIR – Spectral Adiabatic Inversion Recovery SPIR – Spectral Pre-saturation with Inversion Recovery STIR – Short Tau Inversion Recovery T – Tesla TI – Inversion Time UTE – Ultra-short Echo Time Declarations Acknowledgements Not applicable. Author contribution All authors contributed to the study conception and design. Funding No funds were received. Data availability Not applicable Ethics approval Ethical approval was obtained. Consent to participate Informed consent was from the participants Consent for publication Not applicable. In this study no identifiable patient data’s were included. Conflict of interests The authors declare no competing interests. References Jahng GH, Park S, Ryu CW, Cho ZH. Magnetic Resonance Imaging: Historical Overview, Technical Developments, and Clinical Applications. Prog Med Phys. 2020 Sept 30;31(3):35–53. Nasir AI. The Role of Magnetic Resonance Imaging in the Knee Joint Injuries. 1. Sharma D, Sharma A, Talwar N, Abhimanyu A, Mittal P, Garg S, et al. Role of MRI Evaluation in Knee Injuries. jemds. 2020 Apr 27;9(17):1435–41. Abulhasan J, Grey M. Anatomy and Physiology of Knee Stability. JFMK. 2017 Sept 24;2(4):34. Li J, Liu H, Song M, Lin F, Zhao Z, Wang Z, et al. Biomechanical characteristics of ligament injuries in the knee joint during impact in the upright position: a finite element analysis. Journal of Orthopaedic Surgery and Research. 2024 Oct 7;19(1):630. Zeng N, Yan ZP, Chen XY, Ni GX. Infrapatellar Fat Pad and Knee Osteoarthritis. Aging and disease. 2020;11(5):1317. Gerena LA, Mabrouk A, DeCastro A. Knee Effusion. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 [cited 2025 July 25]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK532279/ Ahmed I, Moiz H, Carlos W, Edwin C, Staniszewska S, Parsons N, et al. The use of magnetic resonance imaging (MRI) of the knee in current clinical practice: A retrospective evaluation of the MRI reports within a large NHS trust. The Knee. 2021 Mar 1;29:557–63. Zee CS, Segall HD, Terk MR, Destian S, Ahmadi J, Gober JR, et al. SPIR MRI in spinal diseases. J Comput Assist Tomogr. 1992;16(3):356–60. Jung DB, Lee HK, Heo YC. Comparison of mDixon, T2 TSE, and T2 SPIR Images in Magnetic Resonance Imaging of Lumbar Sagittal Plane. Journal of the Korean Society of Radiology. 2021;15(6):927–33. Cameron I. Techniques of Fat Suppression. Lauenstein TC, Sharma P, Hughes T, Heberlein K, Tudorascu D, Martin DR. Evaluation of optimized inversion-recovery fat-suppression techniques for T2-weighted abdominal MR imaging. Journal of Magnetic Resonance Imaging. 2008;27(6):1448–54. Iyama Y, Nakaura T, Kidoh M, Katahira K, Namimoto T, Morishita S, et al. Fat Suppressed Contrast-Enhanced T1-Weighted Dynamic Magnetic Resonance Imaging at 3T: Comparison of Image Quality Between Spectrally Adiabatic Iversion Recovery and the Multiecho Dixon Technique in Imaging of the Prostate. Journal of Computer Assisted Tomography. 2017 June;41(3):382. Wu J, Lu LQ, Gu JP, Yin XD. The Application of Fat-Suppression MR Pulse Sequence in the Diagnosis of Bone-Joint Disease. IJMPCERO. 2012;01(03):88–94. Larson PEZ, Conolly SM, Pauly JM, Nishimura DG. Using Adiabatic Inversion Pulses for Long-T2 Suppression in Ultra-short Echo Time (UTE) Imaging. Magn Reson Med. 2007 Nov;58(5):952–61. Politeknik Kesehatan Kemenkes Semarang, Indonesia, Indrati R. Comparing SPIR and SPAIR Fat Suppression Techniques in Magnetic Resonance Imaging (MRI) of Wrist Joint. jmscr. 2017 June 12;05(06):23180–5. Dalto VF, Assad RL, Lorenzato MM, Crema MD, Louzada-Junior P, Nogueira-Barbosa MH. Comparison between STIR and T2-weighted SPAIR sequences in the evaluation of inflammatory sacroiliitis: diagnostic performance and signal-to-noise ratio. Radiol Bras. 2020;53(4):223–8. Kishida Y, Koyama H, Seki S, Yoshikawa T, Kyotani K, Okuaki T, et al. Comparison of fat suppression capability for chest MR imaging with Dixon, SPAIR and STIR techniques at 3 Tesla MR system. Magn Reson Imaging. 2018 Apr;47:89–96. Brandão S, Nogueira L, Matos E, Nunes RG, Ferreira HA, Loureiro J, et al. Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience. Radiol med. 2015 Aug;120(8):705–13. Le Bihan D, Iima M, Partridge SC. Fat-signal suppression in breast diffusion-weighted imaging: the Good, the Bad, and the Ugly. Eur Radiol. 2025;35(2):733–41. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8749005","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":586547174,"identity":"a9a6b43a-9348-4dbf-adff-fb4523292122","order_by":0,"name":"Govindaraj S","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYJCCAwxsEOoAg8F/OTDzAdFaDlQwG4OZCQTtYYNpPsOc2ABi4NMi795jeLigzC6fv/Hsw8Mf29jS54cdfgi0xU5OtwG7FsMzZwwOzziXbDnjwHGDAwfbeHI33k4zAGpJNjY7gEPLjLSEw7xtzAYMB44xALVI5G6cnQDSciBxG34t9QbyEC0G6Yaz0z/g1SIvkXwAqOWwgQFIy4EzCQny0jn4bTHgOXzgMM+54waGIC1nKg4YbpDOKTiQYIDbL/Ltjc2fecqqDeRuHGP+UGFwQF5+dvrmDx8q7ORwaTGAi0scQBYxwK4cbEsDjMXfgC4yCkbBKBgFowACAJCTb24t/VijAAAAAElFTkSuQmCC","orcid":"","institution":"Vinayaka Missions University","correspondingAuthor":true,"prefix":"","firstName":"Govindaraj","middleName":"","lastName":"S","suffix":""},{"id":586547175,"identity":"662edefe-82db-442c-8818-2d17d424b2fc","order_by":1,"name":"Dr. Lavanya Dharmalingam","email":"","orcid":"","institution":"Aarupadai Veedu Medical College \u0026 Hospital","correspondingAuthor":false,"prefix":"Dr.","firstName":"Lavanya","middleName":"","lastName":"Dharmalingam","suffix":""}],"badges":[],"createdAt":"2026-01-31 10:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8749005/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8749005/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102207902,"identity":"c40a63b3-97db-45cb-a540-ed5ef5cf34e8","added_by":"auto","created_at":"2026-02-09 12:06:51","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":404984,"visible":true,"origin":"","legend":"\u003cp\u003eThe left image represents the PD-SPIR sagittal sequence and the right image the PD-SPAIR sagittal sequence of the same patient’s knee joint with identical parameters. SPAIR provides superior fat-signal suppression and sharper delineation of anatomical structures compared with SPIR, resulting in improved visualization of intra-articular components and overall image uniformity.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8749005/v1/aa495d5d9acda3f6112587a7.jpeg"},{"id":102296918,"identity":"7b83a4e3-8502-407d-bfc6-cde47fc48a84","added_by":"auto","created_at":"2026-02-10 10:22:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1016120,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8749005/v1/9ffaf765-cd42-4cbc-bd18-dace01d84832.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparing Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) Fat suppression techniques in Magnetic Resonance Imaging of knee joint","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMagnetic Resonance Imaging (MRI) is a revolutionary advancement in diagnostic Radiology [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Magnetic resonance imaging (MRI) is an imaging technique without ionizing radiation. MRI utilizes strong magnetic fields and radiofrequency (RF) pulses to produce detailed anatomical images [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In 1983, MRI first began to be used for the diagnostic assessment of the knee joint. The introduction of MRI has transformed the practice of musculoskeletal imaging, particularly that of internal derangements of the knee (e.g., meniscal and ligament injuries). The ability of MRI to create thin-section images with high-contrast resolution makes this modality the imaging modality of choice to evaluate many knee pathologies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe knee is a mechanically complex joint that behaves as a modified hinge with great motion potential throughout its available planes of movement. The knee is mainly responsible for flexion and extension in the sagittal plane and supports varus and valgus movements in the frontal plane [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The patellar ligament, anterior and posterior cruciate ligaments (ACL \u0026amp; PCL), and the medial and lateral collateral ligaments (MCL \u0026amp; LCL) are the main ligaments that provide stability at the knee joint [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The infrapatellar fat pad or Hoffa's fat pad was first documented in 1904; it is located below the patella and is intracapsular but not intracapsular. It is a filler of interstitial spaces during movement, stabilizer of the patella, and limits mechanical compression on the knee joint [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Synovial fluid, particularly its hyaluronic acid, is important in reducing joint friction and smooth articulation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMRI adds significant value to early diagnosis of knee pain by identifying early soft tissue and joint abnormalities that are not identifiable on plain x ray. Although the detection of early arthritis may not provide better sensitivity compared to clinical or radiographic methods, MRI is invaluable at identifying associated findings, including cartilage damage and bone marrow edema, which can assist with treatment planning [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpectral Pre-saturation with Inversion Recovery (SPIR) is utilized to suppress fat signals in MR imaging and combines the key components of both spectral fat saturation and inversion recovery. SPIR is a chemical shift selective (CHESS) method which utilizes an inversion pulse selectively to suppress the fat signal while enabling the rest of the anatomy of interest to be preserved. Originally designed by Oh et al. for spine imaging [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. SPIR works by employing a frequency-specific 180\u0026deg; radiofrequency (RF) inversion pulse targeting solely fat protons where these protons utilize the frequency (chemical shift) difference as fat and water differ. In this manner the longitudinal magnetization of the fat protons are inverted. After a designated time (the inversion time or TI) during which the longitudinal magnetization of the fat has ultimately decayed to zero, a 90\u0026deg; RF excitation pulse is transmitted specifically targeting fat, and at that moment, the fat magnetization is null and hence there is zero contribution of fat to the transverse signal used to generate fat in the final image indicating fat suppression was successful [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, SPIR also has certain limitations, The technique is sensitive to variations in both the main magnetic field (B₀) and the radiofrequency field (B₁). Its effectiveness depends on accurate separation between fat and water resonance frequencies, which may be difficult to achieve in low-field scanners or poorly shimmed systems [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As MRI technology has advanced, fat suppression techniques have significantly improved images and lesion detection. Among these Spectral Adiabatic Inversion Recovery (SPAIR). SPAIR is recognized as a reliable and effective fat signal suppression technique. Overall, SPAIR is a hybrid of CHESS's spectral selectivity and STIR's inversion recovery that utilizes adiabatic radiofrequency (RF) pulses to produce more uniform fat signal suppression across various regions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. One of the good aspects of SPAIR is the application's use of adiabatic RF pulses. An adiabatic RF pulse applies frequency and percentage changes to keep the magnetization stable even with B1 field in-homogeneity. Thus, SPAIR is more consistent and provides a more homogeneous fat suppression when compared to traditional frequency selective methods such as FatSat, especially in areas that are anatomically complicated or exhibit magnetic non-uniformity, such as the spine or pelvis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSPAIR has been clinically applied with great benefit in musculoskeletal imaging. It has allowed for better demonstrations of soft tissue structures including ligaments, cartilage, and joint capsules especially around joints like the knee [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. While SPAIR has prolonged scan times and higher specific absorption rates (SAR) with larger flip angles, the diagnostic advantages of this technique often outweigh its limitations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e"},{"header":"2. Methods and Materials","content":"\u003cp\u003eThis study was a hospital-based cross-sectional study conducted in the Department of Radiodiagnosis, Aarupadai Veedu Medical College and Hospital, Puducherry, over a period of six months. A total of 72 patients referred for MRI of the knee joint were selected using purposive sampling. Ethical clearance was obtained, and written informed consent was taken from all participants. Patients with metal implants, first-trimester pregnancy, claustrophobia, or those unwilling to participate were excluded from the study.\u003c/p\u003e \u003cp\u003eAll MRI scans were performed on a Philips Achieva 1.5 Tesla MRI scanner using a dedicated knee coil to ensure high-quality images. Patients were positioned supine, head-first, with the mid-knee joint as the landmark. Routine knee MRI sequences such as proton density (PDW) images were obtained in axial, sagittal, and coronal planes. Along with these, SPIR (Spectral Presaturation with Inversion Recovery) and SPAIR (Spectral Adiabatic Inversion Recovery) sagittal proton density-weighted (PDW) images were also acquired under identical imaging parameters to allow direct comparison between the two fat suppression techniques.\u003c/p\u003e \u003cp\u003eAll images were anonymized and independently reviewed by two experienced radiologists in a double-blind manner. The evaluation focused on anatomical clarity, uniformity of fat suppression, and presence of artifacts in key structures such as the femoral condyles, tendons, ligaments, menisci, cartilage, patella, and Hoffa\u0026rsquo;s fat pad. Each structure was scored using a three-point Likert scale, where higher scores represented superior clarity and fat suppression.\u003c/p\u003e \u003cp\u003eThe data were compiled in Microsoft Excel and analyzed using IBM SPSS software. Descriptive statistics were used to summarize the findings, while Wilcoxon signed-rank tests were applied to compare SPIR and SPAIR image quality. Inter-observer agreement was assessed using the kappa (κ) coefficient. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe research was carried out on 72 participants who underwent MRI examination of the knee joint, with an age range from 10 to 69 years. Among them, 47 were male (65.3%) and 25 were female (34.7%). The majority of participants were within the 20\u0026ndash;39 years age group (Tables\u0026nbsp;1 \u0026amp; 2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable-1 Demographic Profile of study participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of Participants (n\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTable-2 Age group distribution of the participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll anatomical structures showed statistically significant improvement in image clarity with the SPAIR sequence compared to SPIR, as confirmed by the Wilcoxon signed-rank test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The mean clarity scores for SPIR and SPAIR sequences across major knee joint anatomical structures. SPAIR demonstrated consistently higher mean scores than SPIR, indicating more uniform fat suppression and clearer visualization of soft-tissue details. These findings highlight SPAIR\u0026rsquo;s superior diagnostic image quality in knee MRI (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). And the inter-observer agreement between the two radiologists for SPIR and SPAIR sequences were evaluated by using Cohen\u0026rsquo;s κ statistic. Image interpretation was based on the clarity of anatomical structures. All κ values indicate excellent reliability, confirming consistent image-quality assessments across readers. SPAIR sequences demonstrated marginally higher agreement, reflecting superior inter-reader consistency. κ values were interpreted according to Landis and Koch (1977), where κ\u0026thinsp;\u0026ge;\u0026thinsp;0.81 denotes excellent agreement (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of SPIR and SPAIR sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemoral condyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTendons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLigaments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeniscus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCartilage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoffa\u0026rsquo;s fat pad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of mean clarity scores between SPIR and SPAIR sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnatomical Structure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSPIR (Mean)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSPAIR (Mean)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemoral condyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTendons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLigaments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeniscus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCartilage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoffa\u0026rsquo;s fat pad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInter-observer reliability for SPIR and SPAIR sequences in evaluation of knee MRI structures\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnatomical Structure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSPIR (κ Value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSPAIR (κ Value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemoral condyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTendons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLigaments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeniscus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCartilage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoffa\u0026rsquo;s fat pad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study comprehensively compared Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) fat suppression techniques in knee joint MRI, with a focus on their effectiveness in visualizing key anatomical structures, including the femoral condyles, tendons, patella, ligaments, menisci, articular cartilage, and Hoffa\u0026rsquo;s fat pad. The findings of the present study are in strong agreement with previously published literature. Indrati et al. (2017) in a comparative study of SPIR and SPAIR in wrist MRI, reported that SPAIR yielded superior anatomical detail due to its adiabatic inversion pulse, which provides uniform fat suppression while minimizing artifacts [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Similarly, Dalto et al. (2020) in their evaluation of sacroiliac joint imaging, demonstrated that T2-weighted SPAIR sequences achieved higher signal-to-noise ratios (SNR) and improved image contrast compared to STIR, consistent with the enhanced diagnostic confidence observed in the current study [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Kishida et al. (2018) also demonstrated at 3T that SPAIR achieved higher fat-to-noise ratios and more reliable suppression than SPIR, while maintaining reproducibility an outcome that parallels the high inter-reader agreement (κ\u0026thinsp;=\u0026thinsp;0.88\u0026ndash;1.00) was documented [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similarly, Brand\u0026atilde;o et al. (2015) in their evaluation of breast diffusion-weighted MRI, reported that SPAIR produced higher lesion visibility in specific cases compared with STIR, underscoring SPAIR\u0026rsquo;s broader utility across different anatomical regions and modalities [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Evidence from non-musculoskeletal applications also corroborates these findings. Le Bihan et al. (2025) demonstrated SPAIR\u0026rsquo;s superior performance in breast MRI, achieving more uniform fat suppression in regions affected by field inhomogeneities [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe consistency and reproducibility observed in this study reinforce the growing consensus in the literature that SPAIR should be considered the preferred fat suppression technique in clinical musculoskeletal MRI protocols, particularly for high-resolution imaging of complex anatomical structures such as the knee joint.\u003c/p\u003e"},{"header":"5. Strengths and Limitations","content":"\u003cp\u003eThis study\u0026rsquo;s structured comparative design directly evaluated SPIR and SPAIR fat-suppression techniques under standardized 1.5 T MRI parameters, ensuring objective assessment. A sample of 72 subjects provided adequate statistical power, and analysis of key knee structures enabled a comprehensive comparison of image clarity. Robust statistical methods and excellent inter-observer agreement (κ\u0026thinsp;=\u0026thinsp;0.88\u0026ndash;1.00) reinforced the reliability of findings, confirming SPAIR\u0026rsquo;s superior diagnostic performance. Limitations include its single-centre design using only a 1.5 T scanner, reliance on a subjective 3-point scale without quantitative metrics (SNR, CNR), and restriction to the knee joint without clinical or surgical correlation. SPAIR also required a slightly longer scan time (\u0026asymp;\u0026thinsp;2 min more than SPIR), which may affect workflow in high-volume settings.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study demonstrated that the SPAIR fat-suppression technique provides superior image quality compared to SPIR in knee MRI. Using standardized 1.5 T imaging parameters, SPAIR produced more homogeneous fat suppression, fewer artifacts, and clearer visualization of critical anatomical structures, including the menisci, cruciate ligaments, cartilage, and periarticular soft tissues. These findings highlight SPAIR\u0026rsquo;s potential to enhance diagnostic confidence and accuracy in musculoskeletal imaging, particularly for subtle ligamentous and cartilage pathologies. Overall, SPAIR can be recommended as a preferred fat-suppression technique for routine knee MRI examinations, balancing diagnostic quality and clinical practicality.\u003c/p\u003e"},{"header":"Abbrevations","content":"\u003cul\u003e\n \u003cli\u003eACL – Anterior Cruciate Ligament\u003c/li\u003e\n \u003cli\u003eB₀ – Main Magnetic Field\u003c/li\u003e\n \u003cli\u003eB₁ – Radiofrequency Magnetic Field\u003c/li\u003e\n \u003cli\u003eCHESS – Chemical Shift Selective\u003c/li\u003e\n \u003cli\u003eCNR – Contrast-to-Noise Ratio\u003c/li\u003e\n \u003cli\u003eLCL – Lateral Collateral Ligament\u003c/li\u003e\n \u003cli\u003eMCL – Medial Collateral Ligament\u003c/li\u003e\n \u003cli\u003eMRI – Magnetic Resonance Imaging\u003c/li\u003e\n \u003cli\u003ePD – Proton Density\u003c/li\u003e\n \u003cli\u003ePDW – Proton Density Weighted\u003c/li\u003e\n \u003cli\u003ePCL – Posterior Cruciate Ligament\u003c/li\u003e\n \u003cli\u003eRF – Radiofrequency\u003c/li\u003e\n \u003cli\u003eSAR – Specific Absorption Rate\u003c/li\u003e\n \u003cli\u003eSNR – Signal-to-Noise Ratio\u003c/li\u003e\n \u003cli\u003eSPAIR – Spectral Adiabatic Inversion Recovery\u003c/li\u003e\n \u003cli\u003eSPIR – Spectral Pre-saturation with Inversion Recovery\u003c/li\u003e\n \u003cli\u003eSTIR – Short Tau Inversion Recovery\u003c/li\u003e\n \u003cli\u003eT – Tesla\u003c/li\u003e\n \u003cli\u003eTI – Inversion Time\u003c/li\u003e\n \u003cli\u003eUTE – Ultra-short Echo Time\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funds were received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was from the participants\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. In this study no identifiable patient data\u0026rsquo;s were included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eJahng GH, Park S, Ryu CW, Cho ZH. Magnetic Resonance Imaging: Historical Overview, Technical Developments, and Clinical Applications. Prog Med Phys. 2020 Sept 30;31(3):35\u0026ndash;53.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNasir AI. The Role of Magnetic Resonance Imaging in the Knee Joint Injuries. 1.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSharma D, Sharma A, Talwar N, Abhimanyu A, Mittal P, Garg S, et al. Role of MRI Evaluation in Knee Injuries. jemds. 2020 Apr 27;9(17):1435\u0026ndash;41.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAbulhasan J, Grey M. Anatomy and Physiology of Knee Stability. JFMK. 2017 Sept 24;2(4):34.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLi J, Liu H, Song M, Lin F, Zhao Z, Wang Z, et al. Biomechanical characteristics of ligament injuries in the knee joint during impact in the upright position: a finite element analysis. Journal of Orthopaedic Surgery and Research. 2024 Oct 7;19(1):630.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZeng N, Yan ZP, Chen XY, Ni GX. Infrapatellar Fat Pad and Knee Osteoarthritis. Aging and disease. 2020;11(5):1317.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eGerena LA, Mabrouk A, DeCastro A. Knee Effusion. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 [cited 2025 July 25]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK532279/\u003c/li\u003e\n \u003cli\u003eAhmed I, Moiz H, Carlos W, Edwin C, Staniszewska S, Parsons N, et al. The use of magnetic resonance imaging (MRI) of the knee in current clinical practice: A retrospective evaluation of the MRI reports within a large NHS trust. The Knee. 2021 Mar 1;29:557\u0026ndash;63.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eZee CS, Segall HD, Terk MR, Destian S, Ahmadi J, Gober JR, et al. SPIR MRI in spinal diseases. J Comput Assist Tomogr. 1992;16(3):356\u0026ndash;60.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJung DB, Lee HK, Heo YC. Comparison of mDixon, T2 TSE, and T2 SPIR Images in Magnetic Resonance Imaging of Lumbar Sagittal Plane. Journal of the Korean Society of Radiology. 2021;15(6):927\u0026ndash;33.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCameron I. Techniques of Fat Suppression.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLauenstein TC, Sharma P, Hughes T, Heberlein K, Tudorascu D, Martin DR. Evaluation of optimized inversion-recovery fat-suppression techniques for T2-weighted abdominal MR imaging. Journal of Magnetic Resonance Imaging. 2008;27(6):1448\u0026ndash;54.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIyama Y, Nakaura T, Kidoh M, Katahira K, Namimoto T, Morishita S, et al. Fat Suppressed Contrast-Enhanced T1-Weighted Dynamic Magnetic Resonance Imaging at 3T: Comparison of Image Quality Between Spectrally Adiabatic Iversion Recovery and the Multiecho Dixon Technique in Imaging of the Prostate. Journal of Computer Assisted Tomography. 2017 June;41(3):382.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWu J, Lu LQ, Gu JP, Yin XD. The Application of Fat-Suppression MR Pulse Sequence in the Diagnosis of Bone-Joint Disease. IJMPCERO. 2012;01(03):88\u0026ndash;94.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLarson PEZ, Conolly SM, Pauly JM, Nishimura DG. Using Adiabatic Inversion Pulses for Long-T2 Suppression in Ultra-short Echo Time (UTE) Imaging. Magn Reson Med. 2007 Nov;58(5):952\u0026ndash;61.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePoliteknik Kesehatan Kemenkes Semarang, Indonesia, Indrati R. Comparing SPIR and SPAIR Fat Suppression Techniques in Magnetic Resonance Imaging (MRI) of Wrist Joint. jmscr. 2017 June 12;05(06):23180\u0026ndash;5.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDalto VF, Assad RL, Lorenzato MM, Crema MD, Louzada-Junior P, Nogueira-Barbosa MH.\u0026nbsp;Comparison between STIR and T2-weighted SPAIR sequences in the evaluation of inflammatory sacroiliitis: diagnostic performance and signal-to-noise ratio. Radiol Bras. 2020;53(4):223\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eKishida Y, Koyama H, Seki S, Yoshikawa T, Kyotani K, Okuaki T, et al. Comparison of fat suppression capability for chest MR imaging with Dixon, SPAIR and STIR techniques at 3 Tesla MR system. Magn Reson Imaging. 2018 Apr;47:89\u0026ndash;96.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBrand\u0026atilde;o S, Nogueira L, Matos E, Nunes RG, Ferreira HA, Loureiro J, et al.\u0026nbsp;Fat suppression techniques (STIR vs. SPAIR) on diffusion-weighted imaging of breast lesions at 3.0 T: preliminary experience. Radiol med. 2015 Aug;120(8):705\u0026ndash;13.\u003c/li\u003e\n \u003cli\u003eLe Bihan D, Iima M, Partridge SC. Fat-signal suppression in breast diffusion-weighted imaging: the Good, the Bad, and the Ugly. Eur Radiol. 2025;35(2):733\u0026ndash;41. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Knee joint, SPIR MRI, SPAIR MRI, Fat suppression, Musculoskeletal imaging","lastPublishedDoi":"10.21203/rs.3.rs-8749005/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8749005/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eMagnetic Resonance Imaging (MRI) is regarded as the gold standard for musculoskeletal imaging due to its excellent soft-tissue contrast and multiplanar capabilities. Nevertheless, the high signal intensity of fat often obscures important anatomical and pathological details, underscoring the need for robust fat suppression techniques. Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) are widely applied frequency-selective inversion recovery methods.\u003c/p\u003e\u003ch2\u003eObjective:\u003c/h2\u003e \u003cp\u003eThis study aims to compare SPIR and SPAIR fat suppression techniques in MRI of the knee joint to determine which provides superior overall image quality for clinical application.\u003c/p\u003e\u003ch2\u003eMaterials and methods:\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted in the Department of Radiodiagnosis, Aarupadai Veedu Medical College and Hospital, Puducherry. A total of 72 patients referred for knee MRI were included using purposive sampling. Imaging was performed on a 1.5T MRI system with a dedicated knee coil, and both PDW-SPIR and PDW-SPAIR fat suppression sequences were obtained under identical parameters. Images were anonymized and independently reviewed by two experienced radiologists. Descriptive and inferential Statistical analysis was performed using the SPSS software.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eSPAIR sequences consistently outperformed SPIR in terms of fat suppression homogeneity, reduction of artifacts, and visualization of key anatomical structures. Structures such as the cruciate ligaments, menisci, articular cartilage, and periarticular soft tissues were more distinctly delineated on PDW - SPAIR images. The differences in image quality were statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Inter-observer reliability was excellent (κ\u0026thinsp;=\u0026thinsp;0.88\u0026ndash;1.00), confirming consistent evaluations across readers.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eSPAIR provides superior fat suppression and overall image quality compared to SPIR in knee MRI. SPAIR enhances diagnostic confidence in musculoskeletal imaging. Its routine incorporation into knee MRI protocols is recommended to improve the detection and assessment of subtle joint pathologies.\u003c/p\u003e","manuscriptTitle":"Comparing Spectral Pre-saturation with Inversion Recovery (SPIR) and Spectral Adiabatic Inversion Recovery (SPAIR) Fat suppression techniques in Magnetic Resonance Imaging of knee joint","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 12:06:46","doi":"10.21203/rs.3.rs-8749005/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e2d4b4c4-52d9-4843-94fe-a26b165c83bf","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T20:08:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 12:06:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8749005","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8749005","identity":"rs-8749005","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}