Nan Jiang , Yu Xia , Mingcong Luo , Jianhua Chen , Zongjian Qiu , Jianfang Liu
{"title":"利用双能 CT 诊断在常规计算机断层扫描(CT)中未发现骨病的新发多发性骨髓瘤","authors":"Nan Jiang , Yu Xia , Mingcong Luo , Jianhua Chen , Zongjian Qiu , Jianfang Liu","doi":"10.1016/j.jbo.2024.100636","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To evaluate the diagnostic utility of fat (hydroxyapatite) density [D<sub>Fat (HAP)</sub>] on dual-energy computed tomography (DECT) for identifying clinical diagnosed multiple myeloma without bone disease (MNBD) that is not visible on conventional CT scans.</div></div><div><h3>Material and Methods</h3><div>In this age-gender-examination sites matched case control prospective study, Chest and/or abdominal images on Revolution CT of MNBDs and control subjects were consecutive enrolled in a 1:2 ratio from October 2022 to November 2023. Multiple myeloma was clinical diagnosed according to criteria of the International Myeloma Working Group. Regions of interest (ROIs) were drawn separately for all thoracolumbar vertebrae in the scanning range by two radiologists. Additionally, a radiologist specializing in musculoskeletal imaging supervised the process. D<sub>Fat (HAP)</sub> was extracted from each ROI. The spine was divided into upper thoracic (UPT), middle and lower thoracic (MLT), thoracolumbar (TL), and middle and lower lumbar (MLL) vertebrae. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of D<sub>Fat (HAP)</sub> in diagnosing multiple myeloma, and the sensitivity, specificity, and accuracy under the optimal cut-off were determined by Youden index (sensitivity + specificity −1).</div></div><div><h3>Results</h3><div>A total of 32 and MNBD patients and 64 control patients were included. The total number of ROIs outlined included MNBD group (n = 493) and control group (n = 986). For all vertebrae, D<sub>Fat(HAP)</sub> got average performance in the diagnosis of MNBD (AUC = 0.733, <em>p</em> < 0.001) with a cut-off value of 958 (mg/cm<sup>3</sup>); the sensitivity, specificity, and accuracy were 58.8 %, 77.8 %, and 71.7 %, respectively. Regarding segment analysis, the diagnostic performance was good for all (AUC, 0.803–0.837; <em>p</em> < 0.001) but the UPT segment (AUC = 0.692, <em>p</em> = 0.002). The optimal diagnostic cut-off values for the MLT, TL, and MLL vertebrae were 955 mg/cm<sup>3</sup>, 947 mg/cm<sup>3</sup>, and 947 mg/cm<sup>3</sup>, respectively; the sensitivity, specificity, and accuracy were 80.0 %-87.5 %, 71.9 %-82.6 %, and 77.1 %-81.6 %, respectively.</div></div><div><h3>Conclusion</h3><div>DECT was effective for detecting MNBD, and better diagnostic results can be obtained by grouping different spine segments.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnosis of newly developed multiple myeloma without bone disease detectable on conventional computed tomography (CT) scan by using dual-energy CT\",\"authors\":\"Nan Jiang , Yu Xia , Mingcong Luo , Jianhua Chen , Zongjian Qiu , Jianfang Liu\",\"doi\":\"10.1016/j.jbo.2024.100636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>To evaluate the diagnostic utility of fat (hydroxyapatite) density [D<sub>Fat (HAP)</sub>] on dual-energy computed tomography (DECT) for identifying clinical diagnosed multiple myeloma without bone disease (MNBD) that is not visible on conventional CT scans.</div></div><div><h3>Material and Methods</h3><div>In this age-gender-examination sites matched case control prospective study, Chest and/or abdominal images on Revolution CT of MNBDs and control subjects were consecutive enrolled in a 1:2 ratio from October 2022 to November 2023. Multiple myeloma was clinical diagnosed according to criteria of the International Myeloma Working Group. Regions of interest (ROIs) were drawn separately for all thoracolumbar vertebrae in the scanning range by two radiologists. Additionally, a radiologist specializing in musculoskeletal imaging supervised the process. D<sub>Fat (HAP)</sub> was extracted from each ROI. The spine was divided into upper thoracic (UPT), middle and lower thoracic (MLT), thoracolumbar (TL), and middle and lower lumbar (MLL) vertebrae. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of D<sub>Fat (HAP)</sub> in diagnosing multiple myeloma, and the sensitivity, specificity, and accuracy under the optimal cut-off were determined by Youden index (sensitivity + specificity −1).</div></div><div><h3>Results</h3><div>A total of 32 and MNBD patients and 64 control patients were included. The total number of ROIs outlined included MNBD group (n = 493) and control group (n = 986). For all vertebrae, D<sub>Fat(HAP)</sub> got average performance in the diagnosis of MNBD (AUC = 0.733, <em>p</em> < 0.001) with a cut-off value of 958 (mg/cm<sup>3</sup>); the sensitivity, specificity, and accuracy were 58.8 %, 77.8 %, and 71.7 %, respectively. Regarding segment analysis, the diagnostic performance was good for all (AUC, 0.803–0.837; <em>p</em> < 0.001) but the UPT segment (AUC = 0.692, <em>p</em> = 0.002). The optimal diagnostic cut-off values for the MLT, TL, and MLL vertebrae were 955 mg/cm<sup>3</sup>, 947 mg/cm<sup>3</sup>, and 947 mg/cm<sup>3</sup>, respectively; the sensitivity, specificity, and accuracy were 80.0 %-87.5 %, 71.9 %-82.6 %, and 77.1 %-81.6 %, respectively.</div></div><div><h3>Conclusion</h3><div>DECT was effective for detecting MNBD, and better diagnostic results can be obtained by grouping different spine segments.</div></div>\",\"PeriodicalId\":48806,\"journal\":{\"name\":\"Journal of Bone Oncology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Bone Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212137424001167\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bone Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212137424001167","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Diagnosis of newly developed multiple myeloma without bone disease detectable on conventional computed tomography (CT) scan by using dual-energy CT
Objective
To evaluate the diagnostic utility of fat (hydroxyapatite) density [DFat (HAP)] on dual-energy computed tomography (DECT) for identifying clinical diagnosed multiple myeloma without bone disease (MNBD) that is not visible on conventional CT scans.
Material and Methods
In this age-gender-examination sites matched case control prospective study, Chest and/or abdominal images on Revolution CT of MNBDs and control subjects were consecutive enrolled in a 1:2 ratio from October 2022 to November 2023. Multiple myeloma was clinical diagnosed according to criteria of the International Myeloma Working Group. Regions of interest (ROIs) were drawn separately for all thoracolumbar vertebrae in the scanning range by two radiologists. Additionally, a radiologist specializing in musculoskeletal imaging supervised the process. DFat (HAP) was extracted from each ROI. The spine was divided into upper thoracic (UPT), middle and lower thoracic (MLT), thoracolumbar (TL), and middle and lower lumbar (MLL) vertebrae. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of DFat (HAP) in diagnosing multiple myeloma, and the sensitivity, specificity, and accuracy under the optimal cut-off were determined by Youden index (sensitivity + specificity −1).
Results
A total of 32 and MNBD patients and 64 control patients were included. The total number of ROIs outlined included MNBD group (n = 493) and control group (n = 986). For all vertebrae, DFat(HAP) got average performance in the diagnosis of MNBD (AUC = 0.733, p < 0.001) with a cut-off value of 958 (mg/cm3); the sensitivity, specificity, and accuracy were 58.8 %, 77.8 %, and 71.7 %, respectively. Regarding segment analysis, the diagnostic performance was good for all (AUC, 0.803–0.837; p < 0.001) but the UPT segment (AUC = 0.692, p = 0.002). The optimal diagnostic cut-off values for the MLT, TL, and MLL vertebrae were 955 mg/cm3, 947 mg/cm3, and 947 mg/cm3, respectively; the sensitivity, specificity, and accuracy were 80.0 %-87.5 %, 71.9 %-82.6 %, and 77.1 %-81.6 %, respectively.
Conclusion
DECT was effective for detecting MNBD, and better diagnostic results can be obtained by grouping different spine segments.
期刊介绍:
The Journal of Bone Oncology is a peer-reviewed international journal aimed at presenting basic, translational and clinical high-quality research related to bone and cancer.
As the first journal dedicated to cancer induced bone diseases, JBO welcomes original research articles, review articles, editorials and opinion pieces. Case reports will only be considered in exceptional circumstances and only when accompanied by a comprehensive review of the subject.
The areas covered by the journal include:
Bone metastases (pathophysiology, epidemiology, diagnostics, clinical features, prevention, treatment)
Preclinical models of metastasis
Bone microenvironment in cancer (stem cell, bone cell and cancer interactions)
Bone targeted therapy (pharmacology, therapeutic targets, drug development, clinical trials, side-effects, outcome research, health economics)
Cancer treatment induced bone loss (epidemiology, pathophysiology, prevention and management)
Bone imaging (clinical and animal, skeletal interventional radiology)
Bone biomarkers (clinical and translational applications)
Radiotherapy and radio-isotopes
Skeletal complications
Bone pain (mechanisms and management)
Orthopaedic cancer surgery
Primary bone tumours
Clinical guidelines
Multidisciplinary care
Keywords: bisphosphonate, bone, breast cancer, cancer, CTIBL, denosumab, metastasis, myeloma, osteoblast, osteoclast, osteooncology, osteo-oncology, prostate cancer, skeleton, tumour.