Diagnostic and interventional radiology最新文献

{"title":"Predictability of the radiological response to Yttrium-90 transarterial radioembolization by dynamic magnetic resonance imaging-based radiomics analysis in patients with intrahepatic cholangiocarcinoma","authors":"Hüseyin Tuğsan Ballı, Ferhat Can Pişkin, Sevinç Püren Yücel, Sinan Sözütok, Duygu Özgül, Kairgeldy Aikimbaev","doi":"10.4274/dir.2023.222025","DOIUrl":"10.4274/dir.2023.222025","url":null,"abstract":"<p><strong>Purpose: </strong>The study aims to investigate the predictability of the radiological response in intrahepatic cholangiocarcinoma (iCC) patients undergoing Yttrium-90 transarterial radioembolization (TARE) with a combined model built on dynamic magnetic resonance imaging (MRI)-based radiomics and clinical features.</p><p><strong>Methods: </strong>Thirty-six naive iCC patients who underwent TARE were included in this study. The tumor segmentation was performed on the axial T2-weighted (T2W) without fat suppression, axial T2W with fat suppression, and axial T1-weighted (T1W) contrast-enhanced (CE) sequence in equilibrium phase (Eq). At the sixth month MRI follow-up, all patients were divided into responders and non-responders according to the modified Response Evaluation Criteria in Solid Tumors. Subsequently, a radiomics score (rad-score) and a combined model of the rad-score and clinical features for each sequence were generated and compared between the groups.</p><p><strong>Results: </strong>Thirteen (36.1%) patients were considered responders, and the remaining 23 (63.9%) were non-responders. Responders exhibited significantly lower rad-scores than non-responders (<i>P</i> < 0.050 for all sequences). The radiomics models showed good discriminatory ability with an area under the curve (AUC) of 0.696 [95% confidence interval (CI), 0.522–0.870] for the axial T1W-CE-Eq, AUC of 0.839 (95% CI, 0.709–0.970) for the axial T2W with fat suppression, and AUC of 0.836 (95% CI, 0.678–0.995) for the axial T2W without fat suppression.</p><p><strong>Conclusion: </strong>Radiomics models created by pre-treatment MRIs can predict the radiological response to Yttrium- 90 TARE in iCC patients with high accuracy. Combining radiomics with clinical features could increase the power of the test. Large-scale studies of multi-parametric MRIs with internal and external validations are needed to determine the clinical value of radiomics in iCC patients.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"193-199"},"PeriodicalIF":1.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9240342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishment of local diagnostic reference levels for computed tomography with cloud-based automated dose-tracking software in Türkiye","authors":"Gökhan Kahraman, Kemal Murat Haberal, Ahmet Muhteşem Ağıldere","doi":"10.4274/dir.2023.232265","DOIUrl":"10.4274/dir.2023.232265","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study is to establish local diagnostic reference levels (LDRLs) for computed tomography (CT) procedures using cloud-based automated dose-tracking software.</p><p><strong>Methods: </strong>The study includes the dose data obtained from a total of 104,272 examinations performed on adult patients (>18 years) using 8 CT scanners over 12 months. The protocols included in our study were as follows: head CT without contrast, cervical spine CT without contrast, neck CT with contrast, chest CT without contrast, abdomen-pelvis CT without contrast, lumbar spine CT without contrast, high-resolution computed tomography (HRCT) of the chest, and coronary CT angiography (CTA). Dose data were collected using cloud-based automatic dose-tracking software. The 75^th percentiles of the distributions of the median volume CT dose index (CTDIvol) and dose length product (DLP) values were used to determine the LDRLs for each protocol. The LDRLs were compared with national DRLs (NDRLs) and DRLs set in other countries. Inter-CT scanner variability, which is a measure of how well clinical practices are standardized, was determined for each protocol. Median values for each protocol were compared with the LDRLs for dose optimization in each CT scanner.</p><p><strong>Results: </strong>The LDRLs (for DLP and CTDIvol, respectively) were 839 mGy.cm and 41.2 mGy for head CT without contrast, 530.6 mGy.cm and 19.8 mGy for cervical spine CT without contrast, 431.9 mGy.cm and 15.5 mGy for neck CT with contrast, 364.8 mGy.cm and 9.3 mGy for chest CT without contrast, 588.9 mGy. cm and 11.2 mGy for abdomen-pelvis CT without contrast, 713 mGy.cm and 24.3 mGy for lumbar spine CT without contrast, 326 mGy.cm and 9.5 mGy for HRCT, and 642.3 mGy.cm and 33.4 mGy for coronary CTA. The LDRLs were comparable to or lower than NDRLs and DRLs set in other countries for most protocols. The comparisons revealed the need for immediate initiation of an optimization process for CT protocols with higher dose distributions. Furthermore, protocols with high inter-CT scanner variability revealed the need for standardization.</p><p><strong>Conclusion: </strong>There is a need to update the NDRLs for CT protocols in Turkey. Until new NDRLs are established, local institutions in Turkey can initiate the optimization process by comparing their dose distributions to the LDRLs established in our study. Automated dose-tracking software can play an important role in establishing DRLs by facilitating the collection and analysis of large datasets.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"205-211"},"PeriodicalIF":2.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10125053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort study","authors":"Ömer Önder, Müjdat Ayva, Yasin Yaraşır, Volkan Gürler, Mustafa Sertaç Yazıcı, Bülent Akdoğan, Ali Devrim Karaosmanoğlu, Muşturay Karçaaltıncaba, Mustafa Nasuh Özmen, Deniz Akata","doi":"10.4274/dir.2023.232414","DOIUrl":"10.4274/dir.2023.232414","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;We aim to examine the long-term outcomes of patients who underwent multiparametric prostate magnetic resonance imaging (mp-MRI) for suspected prostate cancer (PCa), specifically based on their initial Prostate Imaging Reporting and Data System (PI-RADS) categories and various clinical factors. Our secondary aim is to evaluate the prognostic value of the PI-RADS through the National Comprehensive Cancer Network (NCCN) risk group distribution.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This research was conducted as a single-center retrospective cohort study in a tertiary care hospital. A total of 1,359 cases having at least one histopathological examination after the initial mp-MRI and/or adequate clinical/radiological follow-up data were included in the clinically significant PCa (cs-PCa) diagnosis-free survival analysis. Initial mp-MRI dates were accepted as the start of follow-up for the time-to-event analysis. The event was defined as cs-PCa diagnosis (International Society of Urological Pathology ≥2). Patients who were not diagnosed with cs-PCa during follow-up were censored according to predefined literature-based criteria at the end of the maximum follow-up duration with no reasonable suspicion of PCa and no biopsy indication. The impact of various factors on survival was assessed using a log-rank test and multivariable Cox regression. Subsequently, 394 cases diagnosed with PCa during follow-up were evaluated, based on initial PI-RADS categories and NCCN risk groups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Three main risk factors for cs-PCa diagnosis during follow-up were an initial PI-RADS 5 category, initial PI-RADS 4 category, and high MRI-defined PSA density (mPSAD), with average hazard ratios of 29.52, 14.46, and 3.12, respectively. The PI-RADS 3 category, advanced age group, and biopsy-naïve status were identified as additional risk factors (hazard ratios: 2.03, 1.54-1.98, and 1.79, respectively). In the PI-RADS 1-2 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 99.1%, 96.5%, and 93.8%, respectively. For the PI-RADS 3 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 94.9%, 90.9%, and 89.1%, respectively. For the PI-RADS 4 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 56.6%, 55.1%, and 55.1%, respectively. These rates were found to all be 24.2% in the PI-RADS 5 cohort. Considering the 394 cases diagnosed with PCa during follow-up, PI-RADS ≥4 cases were more likely to harbor unfavorable PCa compared to PI-RADS ≤3 cases (&lt;i&gt;P&lt;/i&gt; &lt; 0.001). In the PI-RADS 3 subgroup analysis, a low mPSAD (&lt;0.15 ng/mL&lt;sup&gt;2&lt;/sup&gt;) was found to be a protective prognostic factor against unfavorable PCa (&lt;i&gt;P&lt;/i&gt; = 0.005).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The PI-RADS category has a significant impact on patient management and provides important diagnostic and prognostic information. Higher initial PI-RADS categories are associated with decreased follow-up losses, a shorter time to PCa diag","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"139-151"},"PeriodicalIF":2.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41106174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term results of liver thermal ablation in patients with hepatocellular carcinoma and colorectal cancer liver metastasis regarding spatial features and tumor-specific variables","authors":"Okan Akhan, Ahmet Gürkan Erdemir, Sevilay Karahan, Emre Ünal, Türkmen Turan Çiftçi, Devrim Akıncı, Şuayib Yalçın","doi":"10.4274/dir.2023.221986","DOIUrl":"10.4274/dir.2023.221986","url":null,"abstract":"<p><strong>Purpose: </strong>Colorectal cancer liver metastasis (CRLM) and hepatocellular carcinoma (HCC) are widely treated using microwave and radiofrequency ablation. Local tumor progression (LTP) may develop depending on the shortest vascular distance and large lesion diameter. This study aims to explore the effect of these spatial features and to investigate the correlation between tumor-specific variables and LTP.</p><p><strong>Methods: </strong>This is a retrospective study covering the period between January 2007 and January 2019. One hundred twenty-five patients (CRLM: HCC: 64:61) with 262 lesions (CRLM: HCC: 142:120) were enrolled. The correlation between LTP and the variables was analyzed using the chi-square test, Fischer's exact test, or the Fisher-Freeman-Halton test where applicable. The local progression-free survival (Loc-PFS) was analyzed using the Kaplan-Meier method. Univariable and multivariable Cox regression analyses were performed to identify prognostic factors.</p><p><strong>Results: </strong>Significant correlations were observed for LTP in both CRLM and HCC at a lesion diameter of 30-50 mm (<i>P</i> = 0.019 and <i>P</i> < 0.001, respectively) and SVD of ≤3 mm (<i>P</i> < 0.001 for both). No correlation was found between the ablation type and LTP (CRLM: <i>P</i> = 0.141; HCC: <i>P</i> = 0.771). There was no relationship between residue and the ablation type, but a strong correlation with tumor size was observed (<i>P</i> = 0.127 and <i>P</i> < 0.001, respectively). In CRLM, LTP was associated with mutant K-ras and concomitant lung metastasis (<i>P</i> < 0.001 and <i>P</i> = 0.003, respectively). In HCC, a similar correlation was found for Child-Pugh B, serum alpha-fetoprotein (AFP) level of >10 ng/mL, predisposing factors, and moderate histopathological differentiation (<i>P</i> < 0.001, <i>P</i> = 0.008, <i>P</i> = 0.027, and <i>P</i> < 0.001, respectively). In CRLM, SVD of ≤3 mm proved to be the variable with the greatest negative effect on Loc-PFS (<i>P</i> = 0.007), followed by concomitant lung metastasis (<i>P</i> = 0.027). In HCC, a serum AFP level of >10 ng/mL proved to be the variable with the greatest negative effect on Loc-PFS (<i>P</i> = 0.045).</p><p><strong>Conclusion: </strong>In addition to the lesions' spatial features, tumor-specific variables may also have an impact on LTP.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"183-192"},"PeriodicalIF":2.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9240341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources","authors":"İsmail Meşe, Ceylan Altıntaş Taşlıçay, Beyza Nur Kuzan, Taha Yusuf Kuzan, Ali Kemal Sivrioğlu","doi":"10.4274/dir.2023.232496","DOIUrl":"10.4274/dir.2023.232496","url":null,"abstract":"<p><p>Rapid technological advances have transformed medical education, particularly in radiology, which depends on advanced imaging and visual data. Traditional electronic learning (e-learning) platforms have long served as a cornerstone in radiology education, offering rich visual content, interactive sessions, and peer-reviewed materials. They excel in teaching intricate concepts and techniques that necessitate visual aids, such as image interpretation and procedural demonstrations. However, Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI)-powered language model, has made its mark in radiology education. It can generate learning assessments, create lesson plans, act as a round-the-clock virtual tutor, enhance critical thinking, translate materials for broader accessibility, summarize vast amounts of information, and provide real-time feedback for any subject, including radiology. Concerns have arisen regarding ChatGPT's data accuracy, currency, and potential biases, especially in specialized fields such as radiology. However, the quality, accessibility, and currency of e-learning content can also be imperfect. To enhance the educational journey for radiology residents, the integration of ChatGPT with expert-curated e-learning resources is imperative for ensuring accuracy and reliability and addressing ethical concerns. While AI is unlikely to entirely supplant traditional radiology study methods, the synergistic combination of AI with traditional e-learning can create a holistic educational experience.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"163-174"},"PeriodicalIF":2.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139032129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sonographic cortical bone thickness measurement: can it predict bone mineral density in the pediatric population?","authors":"Uğur Ufuk Işın, Emin Çakmakçı, Ayşe Derya Buluş, Yüksel Yaşartekin, Öznur Ünal, Onur Dirican, Abbas Ali Husseini","doi":"10.4274/dir.2023.232392","DOIUrl":"10.4274/dir.2023.232392","url":null,"abstract":"<p><strong>Purpose: </strong>To explore sonographic cortical bone thickness (CoT) as a potential indicator of bone mineral density (BMD) measured by dual-energy X-ray absorptiometry for screening and diagnosing pediatric osteoporosis.</p><p><strong>Methods: </strong>A prospective study included 41 osteopenic or osteoporotic patients and 52 healthy children. Radius cortical thickness (R-CoT), tibial cortical thickness (T-CoT), and second metatarsal cortical thickness (M-CoT) were measured by B-mode ultrasound; CoT values were compared between groups and the correlation between BMD and CoT was examined.</p><p><strong>Results: </strong>There were no significant differences in R-CoT (<i>P</i> = 0.433), T-CoT (<i>P</i> = 0.057), and M-CoT (<i>P</i> = 0.978) values between the patient and control groups. No significant correlations were found between BMD T-scores and R-CoT (r = -0.073, <i>P</i> = 0.490), T-CoT (r = -0.154, <i>P</i> = 0.141), and M-CoT (r = 0.047, <i>P</i> = 0.657) values.</p><p><strong>Conclusion: </strong>Sonographic CoT values in children do not correlate with BMD values. Unlike in adults, sonographic CoT measurements do not appear to have a role in assessing BMD in the pediatric population.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"200-204"},"PeriodicalIF":2.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095066/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138476938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of image preprocessing on the segmentation-based reproducibility of radiomic features: <i>in vivo</i> experiments on discretization and resampling parameters","authors":"Burak Koçak, Sabahattin Yüzkan, Samet Mutlu, Mehmet Karagülle, Ahmet Kala, Mehmet Kadıoğlu, Sıla Solak, Şeyma Sunman, Zişan Hayriye Temiz, Ali Kürşad Ganiyusufoğlu","doi":"10.4274/dir.2023.232543","DOIUrl":"10.4274/dir.2023.232543","url":null,"abstract":"<p><strong>Purpose: </strong>To systematically investigate the impact of image preprocessing parameters on the segmentation-based reproducibility of magnetic resonance imaging (MRI) radiomic features.</p><p><strong>Methods: </strong>The MRI scans of 50 patients were included from the multi-institutional Brain Tumor Segmentation 2021 public glioma dataset. Whole tumor volumes were manually segmented by two independent readers, with the participation of eight readers. Radiomic features were extracted from two sequences: T2-weighted (T2) and contrast-enhanced T1-weighted (T1ce). Two methods were considered for discretization: bin count (i.e., relative discretization) and bin width (i.e., absolute discretization). Ten discretization (five for each method) and five resampling parameters were varied while other parameters were fixed. The intraclass correlation coefficient (ICC) was used for reliability analysis based on two commonly used cut-off values (0.75 and 0.90).</p><p><strong>Results: </strong>Image preprocessing parameters had a significant impact on the segmentation-based reproducibility of radiomic features. The bin width method yielded more reproducible features than the bin count method. In discretization experiments using the bin width on both sequences, according to the ICC cut-off values of 0.75 and 0.90, the rate of reproducible features ranged from 70% to 84% and from 35% to 57%, respectively, with an increasing percentage trend as parameter values decreased (from 84 to 5 for T2; 100 to 6 for T1ce). In the resampling experiments, these ranged from 53% to 74% and from 10% to 20%, respectively, with an increasing percentage trend from lower to higher parameter values (physical voxel size; from 1 x 1 x 1 to 2 x 2 x 2 mm³).</p><p><strong>Conclusion: </strong>The segmentation-based reproducibility of radiomic features appears to be substantially influenced by discretization and resampling parameters. Our findings indicate that the bin width method should be used for discretization and lower bin width and higher resampling values should be used to allow more reproducible features.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"152-162"},"PeriodicalIF":1.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138801173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Follow-up results of BI-RADS 3 lesions on magnetic resonance imaging: a retrospective study","authors":"Özge Aslan, Ayşenur Oktay, Fatih Eroğlu","doi":"10.4274/dir.2023.232393","DOIUrl":"10.4274/dir.2023.232393","url":null,"abstract":"<p><strong>Purpose: </strong>The categorization of Breast Imaging Reporting and Data System (BI-RADS) 3 lesions is not as clear in magnetic resonance imaging (MRI) as it is in mammography (MG). With the increasing number of MRI scans currently being conducted globally, incidentally detected lesions falling into the probably benign category are frequently being observed. In this study, our aim was to investigate the imaging characteristics and follow-up results of BI-RADS 3 lesions detected by MRI and to determine their malignancy rates.</p><p><strong>Methods: </strong>Breast MRI scans performed between January 2010 and January 2020 and classified as BI-RADS 3 lesions were retrospectively analyzed. The study included 216 lesions with known biopsy or surgical excision results or with at least one year of radiological follow-up. We assessed the patients' age, the presence of breast cancer, the follow-up interval, and the imaging findings at the beginning and during the follow-up. Lesions that remained stable, disappeared, or decreased in size and had a benign histopathological diagnosis were classified as benign. Lesions with the histopathological diagnosis of malignancy, identified by either biopsy or surgical excision, were classified as malignant. We determined the malignancy rate based on the histopathology and follow-up results.</p><p><strong>Results: </strong>Considering the follow-up results of all cases, 8% of lesions were excised, 0.5% decreased in size, 1.4% became enlarged, 17.1% disappeared, and 73% remained stable. The malignancy rate was 2.8%. A significant relationship was found between lesion shape and malignancy, as progression to malignancy was more likely in round lesions than in other types. An irregular margin, heterogeneous enhancement, and kinetic curve (type 2) features were significant for lesion upgrade to malignancy.</p><p><strong>Conclusion: </strong>The malignancy rate in BI-RADS 3 lesions detected by MRI is low and falls within the accepted cancer rate for MG and sonography. Changes in size, morphology, and enhancement pattern should be considered in terms of malignancy development during follow-up. The follow-up intervals should be determined on a case-by-case basis.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"175-182"},"PeriodicalIF":2.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11095069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139641833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic value of synthetic diffusion-weighted imaging on breast magnetic resonance imaging assessment: comparison with conventional diffusion-weighted imaging.","authors":"Ebru Yılmaz, Nilgün Güldoğan, Sıla Ulus, Ebru Banu Türk, Mustafa Enes Mısır, Aydan Arslan, Mustafa Erkin Arıbal","doi":"10.4274/dir.2023.232466","DOIUrl":"10.4274/dir.2023.232466","url":null,"abstract":"<p><strong>Purpose: </strong>To compare images generated by synthetic diffusion-weighted imaging (sDWI) with those from conventional DWI in terms of their diagnostic performance in detecting breast lesions when performing breast magnetic resonance imaging (MRI).</p><p><strong>Methods: </strong>A total of 128 consecutive patients with 135 enhanced lesions who underwent dynamic MRI between 2018 and 2021 were included. The sDWI and DWI signals were compared by three radiologists with at least 10 years of experience in breast radiology.</p><p><strong>Results: </strong>Of the 82 malignant lesions, 91.5% were hyperintense on sDWI and 73.2% were hyperintense on DWI. Of the 53 benign lesions, 71.7% were isointense on sDWI and 37.7% were isointense on DWI. sDWI provides accurate signal intensity data with statistical significance compared with DWI (<i>P</i> < 0.05). The diagnostic performance of DWI and sDWI to differentiate malignant breast masses from benign masses was as follows: sensitivity 73.1% [95% confidence interval (CI): 62-82], specificity 37.7% (95% CI: 24-52); sensitivity 91.5% (95% CI: 83-96), specificity 71.7% (95% CI: 57-83), respectively. The diagnostic accuracy of DWI and sDWI was 59.2% and 83.7%, respectively. However, when the DWI images were evaluated with apparent diffusion coefficient mapping and compared with the sDWI images, the sensitivity was 92.68% (95% CI: 84-97) and the specificity was 79.25% (95% CI: 65-89) with no statistically significant difference. The inter-reader agreement was almost perfect (<i>P</i> < 0.001).</p><p><strong>Conclusion: </strong>Synthetic DWI is superior to DWI for lesion visibility with no additional acquisition time and should be taken into consideration when conducting breast MRI scans. The evaluation of sDWI in routine MRI reporting will increase diagnostic accuracy.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"91-98"},"PeriodicalIF":2.1,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10916533/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54228229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions.","authors":"Tugba Akinci D'Antonoli, Arnaldo Stanzione, Christian Bluethgen, Federica Vernuccio, Lorenzo Ugga, Michail E Klontzas, Renato Cuocolo, Roberto Cannella, Burak Koçak","doi":"10.4274/dir.2023.232417","DOIUrl":"10.4274/dir.2023.232417","url":null,"abstract":"<p><p>With the advent of large language models (LLMs), the artificial intelligence revolution in medicine and radiology is now more tangible than ever. Every day, an increasingly large number of articles are published that utilize LLMs in radiology. To adopt and safely implement this new technology in the field, radiologists should be familiar with its key concepts, understand at least the technical basics, and be aware of the potential risks and ethical considerations that come with it. In this review article, the authors provide an overview of the LLMs that might be relevant to the radiology community and include a brief discussion of their short history, technical basics, ChatGPT, prompt engineering, potential applications in medicine and radiology, advantages, disadvantages and risks, ethical and regulatory considerations, and future directions.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":" ","pages":"80-90"},"PeriodicalIF":2.1,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10916534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41102193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}