Radiologia Medica最新文献

{"title":"Spatial-demographic analysis model for brain metastases distribution.","authors":"Lin Zhang, Tongtong Che, Bowen Xin, Shuyu Li, Guanzhong Gong, Xiuying Wang","doi":"10.1007/s11547-025-01965-5","DOIUrl":"10.1007/s11547-025-01965-5","url":null,"abstract":"<p><strong>Purpose: </strong>The distribution analysis of the morphologic characteristics and spatial relations among brain metastases (BMs) to guide screening and early diagnosis.</p><p><strong>Material and methods: </strong>This retrospective study analysed 4314 BMs across 30 brain regions from MRIs of 304 patients. This paper proposed a unified analysis model based on persistent homology (PH) and graph modelling to provide a comprehensive portrait of BMs distribution. Spatial relationships are quantified through dynamic multiple-scale graphs constructed with Rips filtration. The multi-scale centrality importance and clustering coefficients are extracted to decode BMs spatial relations. Morphologic BMs characteristics are further analysed by varying radius and volume values that are considered as clinically influential factors. Finally, two-tailed proportional hypothesis testing is used for BM statistical distribution analysis.</p><p><strong>Results: </strong>For spatial analysis, results have shown a statistical increase in the proportions of high-level centrality BMs at the left cerebellum (p<0.01). BMs rapidly form graphs with high clustering rather than those with high centrality. For demographic analysis, the cerebellum and frontal are the top high-frequency areas of BMs with 0-4 and 5-10 radii. Statistical increases in the proportions of BMs at cerebellum (p<0.01).</p><p><strong>Conclusion: </strong>Results indicate that distributions of both BMs spatial relations and demographics are statistically non-random. This research offers novel insights into the BMs distribution analysis, providing physicians with the BMs demographic to guide screening and early diagnosis.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"397-411"},"PeriodicalIF":9.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11903647/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143524277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of the stability of intracranial aneurysms using a deep learning model based on computed tomography angiography.","authors":"Lu Zeng, Li Wen, Yang Jing, Jing-Xu Xu, Chen-Cui Huang, Dong Zhang, Guang-Xian Wang","doi":"10.1007/s11547-024-01939-z","DOIUrl":"10.1007/s11547-024-01939-z","url":null,"abstract":"<p><strong>Purpose: </strong>Assessment of the stability of intracranial aneurysms is important in the clinic but remains challenging. The aim of this study was to construct a deep learning model (DLM) to identify unstable aneurysms on computed tomography angiography (CTA) images.</p><p><strong>Methods: </strong>The clinical data of 1041 patients with 1227 aneurysms were retrospectively analyzed from August 2011 to May 2021. Patients with aneurysms were divided into unstable (ruptured, evolving and symptomatic aneurysms) and stable (fortuitous, nonevolving and asymptomatic aneurysms) groups and randomly divided into training (833 patients with 991 aneurysms) and internal validation (208 patients with 236 aneurysms) sets. One hundred and ninety-seven patients with 229 aneurysms from another hospital were included in the external validation set. Six models based on a convolutional neural network (CNN) or logistic regression were constructed on the basis of clinical, morphological and deep learning (DL) features. The area under the curve (AUC), accuracy, sensitivity and specificity were calculated to evaluate the discriminating ability of the models.</p><p><strong>Results: </strong>The AUCs of Models A (clinical), B (morphological) and C (DL features from the CTA image) in the external validation set were 0.5706, 0.9665 and 0.8453, respectively. The AUCs of Model D (clinical and DL features), Model E (clinical and morphological features) and Model F (clinical, morphological and DL features) in the external validation set were 0.8395, 0.9597 and 0.9696, respectively.</p><p><strong>Conclusions: </strong>The CNN-based DLM, which integrates clinical, morphological and DL features, outperforms other models in predicting IA stability. The DLM has the potential to assess IA stability and support clinical decision-making.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"248-257"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11870988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142814044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of body fat composition on liver iron overload severity in hemochromatosis: a retrospective MRI analysis.","authors":"Marijan Pušeljić, Vanessa Stadlbauer, Nigar Ahmadova, Maximilian Pohl, Michaela Kopetzky, Ann-Katrin Kaufmann-Bühler, Nikolaus Watzinger, Jasminka Igrec, Michael Fuchsjäger, Emina Talakić","doi":"10.1007/s11547-024-01930-8","DOIUrl":"10.1007/s11547-024-01930-8","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the correlation between ectopic adipose tissue and iron overload severity in patients with hemochromatosis.</p><p><strong>Material and methods: </strong>A retrospective cohort of 52 patients who underwent liver iron concentration quantification from January 2015 to October 2023 using a 3.0T MRI scanner. R2* relaxation times and proton density fat fraction (PDFF) were assessed for the entire liver volume and a specific region of interest (ROI) placed in the right lobe. Total body fat (TF), subcutaneous fat (SCF), intermuscular fat (IMF), and visceral fat (VSF) percentages were calculated from a single axial slice at the level of the third lumbar vertebra. Additionally, ratios of IMF-to-VSF, IMF-to-SCF, and SCF-to-VSF were calculated. Standard iron laboratory parameters were collected at least one month prior to MRI. Pearson correlation coefficient was used for correlation analysis.</p><p><strong>Results: </strong>The mean age of participants was 53.9 ± 19.6 years. IMF positively correlated with R2* values in the ROI (p = 0.005, r_s = 0.382) and entire liver (p = 0.016, r_s = 0.332). Conversely, VSF negatively correlated with R2* values from the ROI (p = < 0.001, r_s = - 0.488) and entire liver (p = < 0.001, r_s = - 0.459). Positive correlations were also found between IMF-to-VSF and R2* of the ROI (p = 0.003, r_s = 0.400) and whole liver (p = 0.008, r_s = 0.364). Ferritin levels positively correlated with R2* values calculated from ROI (p = 0.002, r_s = 0.417) and whole liver volume (p = 0.004, r_s = 0.397). A positive correlation was noted between PDFF of the entire liver and TF (p = 0.024, rs = 0.313).</p><p><strong>Conclusion: </strong>The percentage of Intermuscular and visceral adipose tissues correlates with the severity of liver iron overload in hemochromatosis patients.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"179-189"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11870931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying morphologic variations as an alternate to standard response criteria for unresectable primary liver tumors after checkpoint inhibition therapy.","authors":"Laetitia Saccenti, Nicole Varble, Tabea Borde, Andrew S Mikhail, Michael Kassin, Elliot Levy, Sheng Xu, Lindsey A Hazen, Ifechi Ukeh, Cyndi Vasco, Austin G Duffy, Changqing Xie, Cecilia Monge, Donna Mabry, Tim F Greten, Bradford J Wood","doi":"10.1007/s11547-024-01937-1","DOIUrl":"10.1007/s11547-024-01937-1","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study was to assess the feasibility of quantifying morphologic changes in tumors during immunotherapy, as a reflection of response or survival.</p><p><strong>Methods and materials: </strong>A retrospective single-center analysis was performed in patients with unresectable liver cancer previously enrolled in clinical trials combining immunotherapy (tremelimumab ± durvalumab) and locoregional treatment (either ablation or transarterial chemoembolization). Conventional response (RECIST 1.1) was assessed at 6-month follow-up. For morphologic assessment, the largest target lesion was manually segmented on axial slices in two dimensions using contrast-enhanced CT. Solidity and circularity of tumors were calculated at baseline, 3-month follow-up, and at 6-months follow-up. Survival analysis was performed.</p><p><strong>Results: </strong>From the 68 patients enrolled in clinical trials, 28 did not have target lesions separate from lesions treated by locoregional therapies, and 3 had no follow-up imaging. Thirty-seven patients (9 with biliary cancer and 28 with hepatocellular carcinoma) were included. Shape features and shape variation were not correlated with RECIST 1.1 status at 6-month follow-up. However, patients with low solidity tumors at 6-month follow-up showed poorer prognosis compared with patients with high solidity tumors at 6-month follow-up (p = 0.01). Solidity variation analysis confirmed that a decrease of tumor solidity at 6-month follow-up was associated with poorer prognosis (p = 0.01). No association was found between shape features at baseline or shape features at 3-month follow-up with overall survival.</p><p><strong>Conclusion: </strong>Evolution and variation of tumor morphology during treatment may reflect or correlate with outcomes and contribute toward adapted response criteria.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"226-234"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11870906/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142802142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How different body compositions affect the prognosis of HCC undergoing immunotherapy: the paradoxical phenomenon of BMI.","authors":"Jingzhong Ouyang, Yi Yang, Ying Xu, Zhengzheng Wang, Yanzhao Zhou, Haitao Zhao, Hong Zhao, Jianqiang Cai, Feng Ye, Jinxue Zhou","doi":"10.1007/s11547-024-01933-5","DOIUrl":"10.1007/s11547-024-01933-5","url":null,"abstract":"<p><strong>Purpose: </strong>Body mass index (BMI) is associated with the prognosis of hepatocellular carcinoma (HCC) receiving immunotherapy. Body compositions are considered to account for this association, but this hypothesis has yet to be verified conclusively.</p><p><strong>Material and methods: </strong>Our study included 305 patients received immunotherapy at 3 centers between August 2018 and February 2022. We calculated skeletal muscle index (SMI), mean skeletal muscle density (SMD), subcutaneous adipose tissue index (SATI), visceral adipose tissue index (VATI), and visceral to subcutaneous adipose tissue area ratio (VSR) at lumbar 3 level. The influences of BMI and body compositions on overall survival (OS) were comprehensively described.</p><p><strong>Results: </strong>Sarcopenia (Low SMI, HR = 2.203, 95% CI:1.425-3.405, P < 0.001), myosteatosis (low SMD, HR = 2.013, 95% CI:1.246-3.252, P = 0.004) and visceral adipose deposition (high VATI, HR = 0.658, 95% CI:0.453-0.957, P = 0.028) were independent predictors of OS, while BMI was not. The prognosis of underweight (BMI < 20.0 kg/m², P = 0.009) and obesity (BMI ≥ 25.0 kg/m², P = 0.003) were significantly worse than normal weight (20.0 ≤ BMI ≤ 24.9 kg/m²), which might attribute to the differences in body compositions. High VATI had significantly improved OS than low VATI (P = 0.002), and the difference remained significant after propensity score matching (P = 0.017).</p><p><strong>Conclusion: </strong>In HCC receiving immunotherapy, sarcopenia, myosteatosis, and visceral adipose deposition independently predicted OS, and visceral adipose was protective in OS. The effects of BMI on OS depended on body compositions.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"258-270"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142819098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A CT-based deep learning for segmenting tumors and predicting microsatellite instability in patients with colorectal cancers: a multicenter cohort study.","authors":"Weicui Chen, Kaiyi Zheng, Wenjing Yuan, Ziqi Jia, Yuankui Wu, Xiaohui Duan, Wei Yang, Zhibo Wen, Liming Zhong, Xian Liu","doi":"10.1007/s11547-024-01909-5","DOIUrl":"10.1007/s11547-024-01909-5","url":null,"abstract":"<p><strong>Purpose: </strong>To develop and validate deep learning (DL) models using preoperative contrast-enhanced CT images for tumor auto-segmentation and microsatellite instability (MSI) prediction in colorectal cancer (CRC).</p><p><strong>Materials and methods: </strong>Patients with CRC who underwent surgery or biopsy between January 2018 and April 2023 were retrospectively enrolled. Mismatch repair protein expression was determined via immunohistochemistry or fluorescence multiplex polymerase chain reaction-capillary electrophoresis. Manually delineated tumor contours using arterial and venous phase CT images by three abdominal radiologists are served as ground truth. Tumor auto-segmentation used nnU-Net. MSI prediction employed ViT or convolutional neural networks models, trained and validated with arterial and venous phase images (image model) or combined clinical-pathological factors (combined model). The segmentation model was evaluated using patch coverage ratio, Dice coefficient, recall, precision, and F1-score. The predictive models' efficacy was assessed using areas under the curves and decision curve analysis.</p><p><strong>Results: </strong>Overall, 2180 patients (median age: 61 years ± 17 [SD]; 1285 males) were divided into training (n = 1159), validation (n = 289), and independent external test (n = 732) groups. High-level MSI status was present in 435 patients (20%). In the external test set, the segmentation model performed well in the arterial phase, with patch coverage ratio, Dice coefficient, recall, precision, and F1-score values of 0.87, 0.71, 0.72, 0.74, and 0.71, respectively. For MSI prediction, the combined models outperformed the clinical model (AUC = 0.83 and 0.82 vs 0.67, p < 0.001) and two image models (AUC = 0.75 and 0.77, p < 0.001). Decision curve analysis confirmed the higher net benefit of the combined model compared to the other models across probability thresholds ranging from 0.1 to 0.45.</p><p><strong>Conclusion: </strong>DL enhances tumor segmentation efficiency and, when integrated with contrast-enhanced CT and clinicopathological factors, exhibits good diagnostic performance in predicting MSI in CRC.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"214-225"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142716981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Albi score predicts overall survival (OS) in patients with hepatocellular carcinoma (HCC) treated with selective internal radiation therapy (SIRT).","authors":"Monica Finessi, Martina Cioffi, Serena Grimaldi, Marco Fronda, Guido Rovera, Roberto Passera, Patrizia Carucci, Silvia Gaia, Emanuela Rolle, Giorgia Rizza, Fabio Colli, Giorgio Maria Saracco, Renato Romagnoli, Marco Calandri, Paolo Fonio, Silvia Daniela Morbelli, Andrea Doriguzzi Breatta","doi":"10.1007/s11547-024-01943-3","DOIUrl":"10.1007/s11547-024-01943-3","url":null,"abstract":"<p><strong>Purpose: </strong>We aimed to evaluate the prognostic impact of baseline clinical features and treatment procedure, including liver function measured with albumin-bilirubin (ALBI) formula and dosing methods in HCC patients treated with SIRT.</p><p><strong>Material and methods: </strong>The study includes 82 consecutive patients with liver-dominant HCC treated with SIRT (⁹⁰Y glass microspheres, TheraSphereTM) between October 2014 and September 2023. Twenty-five patients were treated with standard dosimetry, while for remaining patients, multi-compartment dosimetry was performed using Simplicit90YTM software. Impact of baseline patient's characteristics including presence of portal vein thrombosis (PVT), Child-Pugh score (CP), ALBI score, bilirubin levels, tumor size and prior locoregional liver-directed or systemic treatments was assessed through multivariable Cox proportional hazard model.</p><p><strong>Results: </strong>Median follow-up after treatment was 40.0 months (15.2-67.9). At univariable analysis, ALBI score and bilirubin levels were found to be independent prognostic factors for survival after SIRT (p = 0.001, respectively); furthermore, at Cox proportional hazards analysis, HR for death of ALBI 2 versus ALBI 1 was 10.54 (95% CI, 1.42-78.19, p = 0.021), while despite not significant, HR in patients with bilirubin levels over 1.1 mg/dl was 2.67 (0.75-9.44, p = 0.118). Conversely, no significant association was found between OS and cirrhosis, tumor size and PVT.</p><p><strong>Conclusion: </strong>ALBI score demonstrated to impact OS in HCC patients treated with SIRT thus going beyond a simple prediction of treatment-related toxicity. The present results are relevant for the selection of HCC patients for SIRT in a real-world clinical setting.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"271-279"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142839029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Qualitative and quantitative evaluation of the role of CBCT in rectal cancer radiotherapy.","authors":"Geanina-Mirela Catona, Loredana G Marcu","doi":"10.1007/s11547-024-01932-6","DOIUrl":"10.1007/s11547-024-01932-6","url":null,"abstract":"<p><p>Verifying patients' position and internal anatomical changes are important steps in the radiotherapy of rectal cancer. Cone Beam Computed Tomography (CBCT) is an advanced imaging method that allows for the quantification of these modifications, ensuring the delivery of radiation dose to the tumor volume, while protecting surrounding organs at risk. The aim of this review is to discuss and analyze the benefits offered by this method of imaging on board the linear accelerator. In view of this, a systematic search of the scientific literature in the Medline/PubMed database was performed for publications over the last decade, with 20 articles found to be relevant for this study. To highlight the benefits of this imaging technique in rectal cancer, the frequency of CBCT use, identification of tumor volume and organs at risk on CBCT images, quantification of the movement of these organs and tumor volume, analysis of positioning errors as well as evaluation of dosimetric parameters were analyzed.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"150-160"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142688599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The CT collateral map: collateral perfusion estimation and baseline lesion assessment after acute anterior circulation ischemic stroke.","authors":"Hee Jong Ki, Hong Gee Roh, Jin Tae Kwak, In Seong Kim, Jeong Jin Park, Yoo Sung Jeon, Hyun Yang, Sumin Jung, Ji Sung Lee, Hyun Jeong Kim","doi":"10.1007/s11547-024-01941-5","DOIUrl":"10.1007/s11547-024-01941-5","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate the clinical feasibility of a CT collateral map compared with an MRA collateral map, focusing on collateral perfusion (CP) estimation and baseline lesion assessment in acute ischemic stroke (AIS).</p><p><strong>Materials and methods: </strong>This retrospective analysis used selected data from a prospectively collected database. We generated CT collateral maps derived from CT perfusion, encompassing images of arterial, capillary, early venous (CMEV), late venous, and delay phases. Three raters assessed CP scores from MRA and CT collateral maps and CMEV lesion volumes. Lesion volumes of baseline diffusion-weighted imaging (bDWI) and cerebral blood flow rate (CBF) < 30% were automatically measured by the software. The agreement between MRA and CT collateral maps in CP estimation and the correlation between lesion volumes with a CBF < 30% and the CMEV for bDWI lesion volumes were analyzed.</p><p><strong>Results: </strong>One-hundred ten patients (mean age ± standard deviation, 71 ± 14; 60 women) with AIS due to steno-occlusion of the internal carotid and/or middle cerebral arteries were included. The agreement between the MRA and CT collateral maps in CP grading was excellent (weighted κ = 0.93; 95% CI, 0.90-0.97). The concordance correlation coefficients (CCCs) of the CBF < 30% and CMEV for bDWI lesion volumes were 0.76 (95% CI, 0.60-0.91) and 0.97 (0.95-0.98), respectively.</p><p><strong>Conclusion: </strong>The clinical feasibility of the CT collateral map is demonstrated by its significant correlation with the MRA collateral map in CP estimation and baseline lesion assessment.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"235-247"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11870971/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142807898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nodal assessment and extranodal extension in head and neck squamous cell cancer: insights from computed tomography and magnetic resonance imaging.","authors":"Nicola Maggialetti, Ilaria Villanova, Sara Greco, Angela Sardaro, Maria Teresa Lagrasta, Claudia Dipalma, Fabio Maglitto, Eleonora Bicci, Nicola Maria Lucarelli, Chiara Copelli, Amato Antonio Stabile Ianora","doi":"10.1007/s11547-024-01929-1","DOIUrl":"10.1007/s11547-024-01929-1","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of the study was to evaluate the concordance between computed tomography (CT)/magnetic resonance imaging (MRI) and histological examination in the evaluation of lymph nodal involvement (N+) and extranodal extension (ENE+) in patients with squamous cell cancer of the head-neck district (HNSCC). The second end point was to evaluate which of the imaging features was more sensitive and specific in establishing N+ and ENE+, and comparing the diagnostic accuracy between CT and MRI.</p><p><strong>Material and methods: </strong>58 patients with HNSCC undergoing surgical treatment with lymph node dissection at the Policlinico of Bari were enrolled in this retrospective study. The criteria used for identifying radiological N+ (rN+) included six characteristics; the presence of any two or more criteria out of these six was considered rN+. For each rN+, the radiological extranodal extension (rENE+) was evaluated analyzing three characteristics; rENE was considered positive if any one criterion was present.</p><p><strong>Results: </strong>Of 167 lymph nodes, 45/167 (27%) had rN+, out of which 20/45 (44%) were rENE+. On pathological examination, 38/45 (84%) nodes were N+ and 11/20 (55%) were ENE+. The agreement between imaging and histology in the evaluation of N was (149/167) 89% with a good concordance (k = 0.7). The agreement between imaging and histology in the evaluation of ENE was (35/45) 78% with a moderate concordance (k = 0.5). Loss of fatty hilum was found to be the most sensitive (84%) imaging finding in N+ evaluation. Capsular irregularity with fat stranding had the highest sensitivity (82%) for the determination of ENE+. Comparing CT and MRI imaging in the evaluation of N+ and ENE+, we found no statistically significant differences (p-value of 0.3 for N+ and p-value of 0.3 for ENE +).</p><p><strong>Conclusions: </strong>Imaging has good confidence in detecting rN+ but modest in assessing rENE+. Further research could improve the imaging specificity for the determination of rENE.</p>","PeriodicalId":20817,"journal":{"name":"Radiologia Medica","volume":" ","pages":"202-213"},"PeriodicalIF":9.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142710941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}