Research in diagnostic and interventional imaging最新文献

{"title":"Imaging patterns of the arterial supply of the prostate gland in adult Ghanaian men","authors":"Bashiru Babatunde Jimah ,&nbsp;Benjamin Dabo Sarkodie ,&nbsp;Dorothea Anim ,&nbsp;Edmund Brakohiapa ,&nbsp;Asare Kweku Offei ,&nbsp;Ewurama Andam Idun ,&nbsp;Benard Botwe ,&nbsp;Klenam Dzefi-Tettey ,&nbsp;Kofi Amedi","doi":"10.1016/j.redii.2022.100020","DOIUrl":"10.1016/j.redii.2022.100020","url":null,"abstract":"<div><h3>Background</h3><p>Prostatic arterial embolization (PAE) is a novel procedure in West Africa and Ghana. A thorough understanding of the prostate artery's (PA) anatomy and pattern is required for successful prostatic arterial embolization and to guarantee targeted intervention. This study focuses on prostate arterial supply in adult males, including prevalence, variability, and imaging pattern.</p></div><div><h3>Methodology</h3><p>A prospective cross-sectional study was conducted, at Euracare Advanced Diagnostics and Heart Centre. Patients who presented for Computed Tomography Angiography of the pelvis were included in the study. A total of 52 males were included and 104 pelvic CT angiography (one for each side) were analyzed, including: prostatic artery diameter, prostatic gland volume and prostate artery branching pattern. The PA branching pattern was classified using de Assis et al. classification.</p></div><div><h3>Result</h3><p>Thirty-seven (71.15%) men had enlarged prostate volume (&gt;30ml). On each side there was only one prostatic artery and no accessory one was found. Only three types of arterial branching were identified: type I, II,III. The type I artery was the most common origin 58.7% (61/104). PA originating from the anterior division of the internal iliac artery (type II) and the type III is from the internal pudendal artery, accounted for 16.3% (17/104) and 25% (26/104) respectively.</p></div><div><h3>Conclusion</h3><p>The most frequent type of PA origin was type I followed by type III then II. Knowing the different and most frequent types of anatomy of PA may help standardization and effectiveness of the PAE in developing countries.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"5 ","pages":"Article 100020"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45169699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis on diagnostic failure of US-guided core needle biopsy for soft tissue tumors","authors":"Ying-Lun Zhang MS ,&nbsp;Qian Ma MS ,&nbsp;Yu Hu MD ,&nbsp;Meng-Jie Wu MS ,&nbsp;Zong-Kai Wei MS ,&nbsp;Qi-Yu Yao MS ,&nbsp;Ju-Ming Li MD ,&nbsp;Ao Li MD, PhD","doi":"10.1016/j.redii.2023.100023","DOIUrl":"10.1016/j.redii.2023.100023","url":null,"abstract":"<div><h3>Purpose</h3><p>To evaluate the diagnostic yield of ultrasonography (US)-guided core needle biopsy (CNB) in the diagnosis of soft tissue tumors (STTs) and to analyze the failure factors.</p></div><div><h3>Methods</h3><p>139 patients with STTs that underwent both US-guided CNB and surgical resection were collected retrospectively. Compared with the histopathological results of surgical resection, the biopsy failure was defined as the following conditions: indefinitive diagnosis, including insufficient samples and unknown subtypes with correct biological potential classification; wrong diagnosis, including wrong biological potential classification and wrong subtypes with correct biological potential classification. Univariate and multivariate analyses from the perspectives of histopathological, demographic and US features together with biopsy procedures were performed to determine risk factors for diagnostic failure.</p></div><div><h3>Results</h3><p>The diagnostic yield of US-guided CNB for STTs in our study was 78.4%, but when only considering the correct biological potential classification of STTs, the diagnostic yield was 80.6%. The multivariate analysis showed that adipocytic tumors (odds ratio (OR) = 10.195, 95% confidence interval (CI): 1.062 - 97.861, <em>p</em> = 0.044), vascular tumors (OR = 41.710, 95% CI: 3.126 - 556.581, <em>p</em> = 0.005) and indeterminate US diagnosis (OR = 8.641, 95% CI: 1.852 - 40.303, <em>p</em> = 0.006) were correlated with the diagnostic failure. The grade III vascular density (OR = 0.019, 95% CI: 0.001 - 0.273, <em>p</em> = 0.007) enabled a higher diagnostic accuracy.</p></div><div><h3>Conclusion</h3><p>US-guided CNB can be an effective modality for the diagnosis of STTs. The diagnostic yield can be increased when the tumor vascular density was grade III in Color Doppler US, but can be decreased in adipocytic tumors, vascular tumors and masses with indeterminate US diagnosis.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"5 ","pages":"Article 100023"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48004210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement of renal cortical fibrosis by CT scan","authors":"John D Olson ,&nbsp;Janet A Tooze ,&nbsp;Daniel J Bourland ,&nbsp;J Mark Cline ,&nbsp;Eduardo B Faria ,&nbsp;Eric P Cohen","doi":"10.1016/j.redii.2023.100024","DOIUrl":"10.1016/j.redii.2023.100024","url":null,"abstract":"<div><h3>Rationale and objectives</h3><p>The accurate, non-invasive, and rapid measurement of renal cortical fibrosis is needed for well-defined benchmarks of permanent injury and for use of anti-fibrotic agents. It is also needed for non-invasive and rapid assessment of the chronicity of human renal diseases.</p></div><div><h3>Materials and methods</h3><p>We have used a non-human primate model of radiation nephropathy to develop a novel method of size-corrected CT imaging to quantify renal cortical fibrosis.</p></div><div><h3>Results</h3><p>Our method has an area under the receiver operating curve of 0.96, which is superior to any other non-invasive method of measuring renal fibrosis.</p></div><div><h3>Conclusion</h3><p>Our method is suitable for immediate translation to human clinical renal diseases.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"5 ","pages":"Article 100024"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10124964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9438374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction model for patient prognosis in idiopathic pulmonary fibrosis using hybrid radiomics analysis","authors":"Daisuke Kawahara ,&nbsp;Takeshi Masuda ,&nbsp;Riku Nishioka ,&nbsp;Masashi Namba ,&nbsp;Nobuki Imano ,&nbsp;Kakuhiro Yamaguchi ,&nbsp;Shinjiro Sakamoto ,&nbsp;Yasushi Horimasu ,&nbsp;Shintaro Miyamoto ,&nbsp;Taku Nakashima ,&nbsp;Hiroshi Iwamoto ,&nbsp;Shinichiro Ohshimo ,&nbsp;Kazunori Fujitaka ,&nbsp;Hironobu Hamada ,&nbsp;Noboru Hattori ,&nbsp;Yasushi Nagata","doi":"10.1016/j.redii.2022.100017","DOIUrl":"10.1016/j.redii.2022.100017","url":null,"abstract":"<div><h3>Objectives</h3><p>To develop an imaging prognostic model for idiopathic pulmonary fibrosis (IPF) patients using hybrid auto-segmentation radiomics analysis, and compare the predictive ability between the radiomics analysis and conventional visual score methods.</p></div><div><h3>Methods</h3><p>Data from 72 IPF patients who had undergone CT were analyzed. In the radiomics analysis, quantitative CT analysis was performed using the semi-auto-segmentation method. In the visual method, the extent of radiologic abnormalities was evaluated and the overall percentage of lung involvement was calculated by averaging values for six lung zones. Using a training cohort of 50 cases, we generated a radiomics model and a visual score model. Subsequently, we investigated the predictive ability of these models in a testing cohort of 22 cases.</p></div><div><h3>Results</h3><p>Three significant prognostic factors such as contrast, Idn, and cluster shade were selected by LASSO Cox regression analysis. In the visual method, multivariate Cox regression analysis revealed that honeycombing and reticulation were significant prognostic factors. Subsequently, a predictive nomogram for prognosis in IPF patients was established using these factors. In the testing cohort, the c-index of the visual and radiomics nomograms were 0.68 and 0.74, respectively. When dividing the cohort into high-risk and low-risk groups using the median nomogram score, significant differences in overall survival (OS) in the visual and radiomics models were observed (P=0.000 and P=0.0003, respectively).</p></div><div><h3>Conclusions</h3><p>The prediction model with hybrid radiomics analysis had a better ability to predict OS in IPF patients than that of the visual method.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"4 ","pages":"Article 100017"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772652522000175/pdfft?md5=d46aea44f6d5f4c39c56f34c5d71c7eb&pid=1-s2.0-S2772652522000175-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47231367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Additional value of chest CT AI-based quantification of lung involvement in predicting death and ICU admission for COVID-19 patients","authors":"Eloise Galzin ,&nbsp;Laurent Roche ,&nbsp;Anna Vlachomitrou ,&nbsp;Olivier Nempont ,&nbsp;Heike Carolus ,&nbsp;Alexander Schmidt-Richberg ,&nbsp;Peng Jin ,&nbsp;Pedro Rodrigues ,&nbsp;Tobias Klinder ,&nbsp;Jean-Christophe Richard ,&nbsp;Karim Tazarourte ,&nbsp;Marion Douplat ,&nbsp;Alain Sigal ,&nbsp;Maude Bouscambert-Duchamp ,&nbsp;Salim Aymeric Si-Mohamed ,&nbsp;Sylvain Gouttard ,&nbsp;Adeline Mansuy ,&nbsp;François Talbot ,&nbsp;Jean-Baptiste Pialat ,&nbsp;Olivier Rouvière ,&nbsp;Loic Boussel","doi":"10.1016/j.redii.2022.100018","DOIUrl":"10.1016/j.redii.2022.100018","url":null,"abstract":"<div><h3>Objectives</h3><p>We evaluated the contribution of lung lesion quantification on chest CT using a clinical Artificial Intelligence (AI) software in predicting death and intensive care units (ICU) admission for COVID-19 patients.</p></div><div><h3>Methods</h3><p>For 349 patients with positive COVID-19-PCR test that underwent a chest CT scan at admittance or during hospitalization, we applied the AI for lung and lung lesion segmentation to obtain lesion volume (LV), and LV/Total Lung Volume (TLV) ratio. ROC analysis was used to extract the best CT criterion in predicting death and ICU admission. Two prognostic models using multivariate logistic regressions were constructed to predict each outcome and were compared using AUC values. The first model (“Clinical”) was based on patients’ characteristics and clinical symptoms only. The second model (“Clinical+LV/TLV”) included also the best CT criterion.</p></div><div><h3>Results</h3><p>LV/TLV ratio demonstrated best performance for both outcomes; AUC of 67.8% (95% CI: 59.5 - 76.1) and 81.1% (95% CI: 75.7 - 86.5) respectively. Regarding death prediction, AUC values were 76.2% (95% CI: 69.9 - 82.6) and 79.9% (95%IC: 74.4 - 85.5) for the “Clinical” and the “Clinical+LV/TLV” models respectively, showing significant performance increase (+ 3.7%; p-value&lt;0.001) when adding LV/TLV ratio. Similarly, for ICU admission prediction, AUC values were 74.9% (IC 95%: 69.2 - 80.6) and 84.8% (IC 95%: 80.4 - 89.2) respectively corresponding to significant performance increase (+ 10%: p-value&lt;0.001).</p></div><div><h3>Conclusions</h3><p>Using a clinical AI software to quantify the COVID-19 lung involvement on chest CT, combined with clinical variables, allows better prediction of death and ICU admission.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"4 ","pages":"Article 100018"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716289/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9583093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of ultrasound guidance for vacuum-assisted biopsy of breast microcalcifications without associated mass","authors":"S. Le Cam ,&nbsp;Y. Badachi ,&nbsp;S. Ayadi ,&nbsp;O. Lucidarme","doi":"10.1016/j.redii.2022.100012","DOIUrl":"10.1016/j.redii.2022.100012","url":null,"abstract":"","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"3 ","pages":"Article 100012"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772652522000126/pdfft?md5=a2a89cdadd9b98514d6da6175e622e41&pid=1-s2.0-S2772652522000126-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47031241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation between native CT density of thyroid parenchyma and thyroid function tests","authors":"Dr. Padma Vikram Badhe M.D. (Radiodiagnosis (Professor)) ,&nbsp;Dr. Moinuddin Sultan M.D. (Radiodiagnosis Senior Resident) ,&nbsp;Dr. Sanika Patil DMRD (Former Senior Resident) ,&nbsp;Dr. Ajith Varrior (Junior Resident) ,&nbsp;Dr. Tejas Ghodasara (Junior Resident) ,&nbsp;Dr. Gautham Shankar (Junior Resident) ,&nbsp;Dr. Satyam Barchha (Junior Resident)","doi":"10.1016/j.redii.2022.100016","DOIUrl":"10.1016/j.redii.2022.100016","url":null,"abstract":"","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"3 ","pages":"Article 100016"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772652522000163/pdfft?md5=4fcd65118e56d0a742a37b7884b371c3&pid=1-s2.0-S2772652522000163-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47915302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT in non-traumatic acute abdominal emergencies: Comparison of unenhanced acquisitions and single-energy iodine mapping for the characterization of bowel wall enhancement","authors":"Sophie Boyer,&nbsp;Charles Lombard,&nbsp;Ayla Urbaneja,&nbsp;Céline Vogrig,&nbsp;Denis Regent,&nbsp;Alain Blum,&nbsp;Pedro Augusto Gondim Teixeira","doi":"10.1016/j.redii.2022.100010","DOIUrl":"10.1016/j.redii.2022.100010","url":null,"abstract":"<div><h3>Objectives</h3><p>To evaluate the benefit of unenhanced CT and single energy iodine mapping (SIM) to conventional contrast-enhanced CT for bowel wall enhancement characterization in an acute abdomen setting.</p></div><div><h3>Methods</h3><p>CT images from 45 patients with a suspected acute abdomen who underwent abdominopelvic CT from April 2018 to June 2018 were analyzed retrospectively by two independent radiologists. These patients had been referred by emergency department physicians in a context of acute abdominal pain and had a confirmed etiological diagnosis. Three image sets were evaluated separately (portal phase images alone; portal phase images and unenhanced images, portal phase images, and single energy iodine maps). Diagnostic accuracy and confidence were assessed. Quantitative analysis of bowel wall enhancement was also performed.</p></div><div><h3>Results</h3><p>The number of correct diagnoses increased by 8% and 12% with unenhanced images and 6% and 13% with SIM for readers 1 and 2, respectively, compared to the portal phase only. There was an improvement in the confidence of the etiological diagnosis with the number of certain diagnoses increasing from 23% to 100%, which was statistically significant for reader 2 and of borderline significance for reader 1 (<em>P</em> = 0.002 and 0.052, respectively) when unenhanced phase and SIM were added. The inter-rater agreement improved when unenhanced and portal phase images were associated, compared to portal phase images alone (kappa = 0.652 [ICC=0.482–0.822] and 0.42 [ICC=0.241–0.607] respectively).</p></div><div><h3>Conclusion</h3><p>SIM and unenhanced images improve the reproducibility and the diagnostic confidence to diagnose ischemic and inflammatory/infectious bowel wall thickening compared to portal phase images alone</p></div><div><h3>Summary sentence</h3><p>The analysis of unenhanced and SIM images in association with portal phase images improves the reproducibility and the radiologist's confidence in the etiological diagnosis of acute non-traumatic bowel wall thickening in adults.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"2 ","pages":"Article 100010"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772652522000102/pdfft?md5=3a976b9a4af0f72983e1a9c5962f7058&pid=1-s2.0-S2772652522000102-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42605168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MADplots: A methodology for visualizing and characterizing energy-dependent attenuation of tissues in spectral computed tomography","authors":"Matthew A. Lewis PhD ,&nbsp;Todd C. Soesbe PhD ,&nbsp;Xinhui Duan PhD ,&nbsp;Liran Goshen PhD ,&nbsp;Yoad Yagil PhD ,&nbsp;Shlomo Gotman MSc ,&nbsp;Robert E. Lenkinski PhD","doi":"10.1016/j.redii.2022.100011","DOIUrl":"10.1016/j.redii.2022.100011","url":null,"abstract":"<div><h3>Rationale and objectives</h3><p>A method for visualizing and analyzing the complete information contained in spectral CT scans using two-dimensional histograms (i.e. Material Attenuation Decomposition plots – MADplots) of the water-photoelectric attenuation versus water-scatter attenuation at the cohort (combination of multiple studies across patients), examination, series, slice, and organ/ROI levels is described.</p></div><div><h3>Materials and methods</h3><p>The appearance of a MADplot with several standard biological materials was predicted using ideal material properties available from NIST and the ICRU to generate a map for this non-spatial data space. Software tools were developed to generate MADplots as new DICOM series that facilitate spectral analysis. Illustrative examples were selected from an IRB-approved, retrospective cohort of Spectral Basis Images (SBIs) scanned using a pre-release, dual-layer detector spectral CT.</p></div><div><h3>Results</h3><p>By combining all of the voxels for contrast and non-contrast studies, the predicted appearance of the MADplot was confirmed. Locations of several kinds of tissue, the shape of the tissue distributions in normal lung, and the variations in the manner in which organ-specific MADplots change with pathology are demonstrated for the presence of fat in both the liver and pancreas highlighting the potential use for identifying pathologies on spectral CT images.</p></div><div><h3>Conclusions</h3><p>The examples of MADplots shown at cohort (combined studies), examination, series, slice, organ, and ROI levels illustrate their potential utility in analyzing and displaying spectral CT data. Future studies are directed at developing MADplot based organ segmentation and the automated detection and display of organ based pathologies.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"2 ","pages":"Article 100011"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772652522000114/pdfft?md5=5f8611115bbe7efa1565b4432f1281c8&pid=1-s2.0-S2772652522000114-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47057273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating bone biopsy quality by technique in an animal model","authors":"Corey K Ho MD ,&nbsp;David Gimarc MD ,&nbsp;Hsieng-Feng Carroll PhD ,&nbsp;Michael Clay MD ,&nbsp;Jeffrey Schowinsky MD ,&nbsp;MK Jesse MD ,&nbsp;Amanda M Crawford MD ,&nbsp;Carrie B Marshall MD","doi":"10.1016/j.redii.2022.100008","DOIUrl":"10.1016/j.redii.2022.100008","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><p>Powered bone biopsy technique is popular due to its ease of use. However, there is conflicting evidence regarding the diagnostic quality of the samples. The purpose of this study is to evaluate the diagnostic adequacy of different bone biopsy devices and techniques as it relates to the frequency of sample artifacts.</p></div><div><h3>Materials and Methods</h3><p>Bone biopsy was performed on same-day processed lamb femora using the following techniques: manual, pulsed powered and full powered. Ten samples were collected using each method by a single musculoskeletal-trained radiologist and were reviewed by 3 blinded pathologists. Samples were compared across multiple categories: length, bone dust, thermal/crush artifact, cellular morphology, fragmentation, and diagnostic acceptability. Bayesian Multilevel Nonlinear Regression models were performed assessing the association between the techniques across the categories.</p></div><div><h3>Results</h3><p>Statistical analysis revealed that the manual technique outperformed any powered technique across all categories: decreased thermal/crush artifact (<em>P</em> = 0.014), decreased bone dust (p&lt;0.001), better cellular morphology (<em>P</em> = 0.005), less fragmentation (<em>P</em> &lt; 0.0001) and better diagnostic acceptability (<em>P</em> &lt; 0.0001).</p></div><div><h3>Conclusion</h3><p>Manually obtained bone biopsy samples generally produce a more diagnostic sample as compared to powered techniques in an animal model. Given these results, manual bone biopsy methods should be encouraged after consideration for lesion composition, difficulty of access and the patient's overall condition.</p></div>","PeriodicalId":74676,"journal":{"name":"Research in diagnostic and interventional imaging","volume":"2 ","pages":"Article 100008"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772652522000084/pdfft?md5=c0b43c642a873d8d251dc9ffdb132cfb&pid=1-s2.0-S2772652522000084-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44016643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}