Polish Journal of Radiology最新文献

{"title":"Accuracy of artificial intelligence in the detection and segmentation of oral and maxillofacial structures using cone-beam computed tomography images: a systematic review and meta-analysis.","authors":"Farida Abesi,&nbsp;Atena Sadat Jamali,&nbsp;Mohammad Zamani","doi":"10.5114/pjr.2023.127624","DOIUrl":"https://doi.org/10.5114/pjr.2023.127624","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of the present systematic review and meta-analysis was to resolve the conflicts on the diagnostic accuracy of artificial intelligence systems in detecting and segmenting oral and maxillofacial structures using cone-beam computed tomography (CBCT) images.</p><p><strong>Material and methods: </strong>We performed a literature search of the Embase, PubMed, and Scopus databases for reports published from their inception to 31 October 2022. We included studies that explored the accuracy of artificial intelligence in the automatic detection or segmentation of oral and maxillofacial anatomical landmarks or lesions using CBCT images. The extracted data were pooled, and the estimates were presented with 95% confidence intervals (CIs).</p><p><strong>Results: </strong>In total, 19 eligible studies were identified. As per the analysis, the overall pooled diagnostic accuracy of artificial intelligence was 0.93 (95% CI: 0.91-0.94). This rate was 0.93 (95% CI: 0.89-0.96) for anatomical landmarks based on 7 studies and 0.92 (95% CI: 0.90-0.94) for lesions according to 12 reports. Moreover, the pooled accuracy of detection and segmentation tasks for artificial intelligence was 0.93 (95% CI: 0.91-0.94) and 0.92 (95% CI: 0.85-0.95) based on 14 and 5 surveys, respectively.</p><p><strong>Conclusions: </strong>Excellent accuracy was observed for the detection and segmentation objectives of artificial intelligence using oral and maxillofacial CBCT images. These systems have the potential to streamline oral and dental healthcare services.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/37/ec/PJR-88-50709.PMC10280367.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10068970","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":"Computed tomographic abdominal fat volume estimation - a handy tool to predict the risk of metabolic syndrome.","authors":"G C Navaneeth,&nbsp;Rudresh Hiremath,&nbsp;Shweta Raviraj Poojary,&nbsp;Divya Vishwanatha Kini,&nbsp;Kavitha B Chittaragi","doi":"10.5114/pjr.2023.131010","DOIUrl":"https://doi.org/10.5114/pjr.2023.131010","url":null,"abstract":"<p><strong>Purpose: </strong>Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients.</p><p><strong>Material and methods: </strong>This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome.</p><p><strong>Results: </strong>The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (<i>p</i> = 0.001), with visceral fat volume predicting a higher risk in females (<i>p</i> = 0.026).</p><p><strong>Conclusions: </strong>Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/11/eb/PJR-88-51352.PMC10493863.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10295027","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":"Whole-body diffusion-weighted imaging with background body signal suppression and quantitative apparent diffusion coefficient in the detection, staging, and grading of non-Hodgkin lymphoma.","authors":"Ahmed A K A Razek,&nbsp;Ahmed M Tawfik,&nbsp;Mariam Abdel Rahman,&nbsp;Saleh Teima,&nbsp;Nihal M Batouty","doi":"10.5114/pjr.2023.126393","DOIUrl":"https://doi.org/10.5114/pjr.2023.126393","url":null,"abstract":"<p><strong>Purpose: </strong>Assess reproducibility of detection, staging, and grading of non-Hodgkin lymphoma (NHL) using whole-body diffusion-weighted imaging with background body signal suppression (WB-DWIBS).</p><p><strong>Material and methods: </strong>Thirty NHL patients underwent WB-DWIBS, divided into 2 groups according to staging and grading. Image analysis and apparent diffusion coefficient (ADC) measurement of the largest lymph node in each group were performed by 2 observers. Inter-observer agreement was performed.</p><p><strong>Results: </strong>Overall inter-observer agreement for detection of NHL was excellent (k = 0.843; 92.05%) with excellent inter-observer agreement of nodal disease (cervical, thoracic and abdominal) (k = 0.783, 0.769, and 0.856; 96.67%, 90.0%, and 93.3% respectively), extra-nodal disease (k = 1; 100%), and splenic involvement (k = 0.67; 83.3%). The overall inter-observer agreement of DWIBS in staging of NHL was excellent (k = 0.90; 94.9%) with excellent inter-observer agreement for stage I (k = 0.93; 96.4%), stage II (k = 0.90; 94.8%), stage III (k = 0.89; 94.6%), and stage IV (k = 0.88; 94.0%). There was significant difference between ADC in stage I, II (0.77 ± 0.13, 0.85 ± 0.09 × 10^-3 mm²/s), and stage III, IV (0.63 ± 0.08, 0.64 ± 0.11 × 10^-3 mm²/s, <i>p</i> < 0.002, < 0.001). Interclass correlation showed almost perfect agreement for ADC measurement in staging and grading groups (<i>r</i> = 0.96 and <i>r</i> = 0.85, respectively, <i>p</i> < 0.001). There was significant difference between ADC in aggressive lymphoma (0.65 ± 0.1, 0.67 ± 0.13 × 10^-3 mm²/s) and indolent lymphoma (0.76 ± 0.14, 0.84 ± 0.09 × 10^-3 mm²/s, <i>p</i> < 0.028, < 0.001).</p><p><strong>Conclusion: </strong>DWIBS is reproducible for detection and staging of nodal and extra-nodal involvement in patients with NHL. ADC can quantitatively participate in the staging and grading of NHL.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/cd/1a/PJR-88-50494.PMC10086610.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9298832","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":"Opinion on \"The role of radiologist in the changing world of healthcare: a White Paper of the European Society of Radiology (ESR)\".","authors":"Monika Bekiesińska-Figatowska","doi":"10.5114/pjr.2023.124095","DOIUrl":"https://doi.org/10.5114/pjr.2023.124095","url":null,"abstract":"","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/74/35/PJR-88-49899.PMC9907158.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10768002","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":"Fully automated clinical target volume segmentation for glioblastoma radiotherapy using a deep convolutional neural network.","authors":"Sogand Sadeghi,&nbsp;Mostafa Farzin,&nbsp;Somayeh Gholami","doi":"10.5114/pjr.2023.124434","DOIUrl":"https://doi.org/10.5114/pjr.2023.124434","url":null,"abstract":"<p><strong>Purpose: </strong>Target volume delineation is a crucial step prior to radiotherapy planning in radiotherapy for glioblastoma. This step is performed manually, which is time-consuming and prone to intra- and inter-rater variabilities. Therefore, the purpose of this study is to evaluate a deep convolutional neural network (CNN) model for automatic segmentation of clinical target volume (CTV) in glioblastoma patients.</p><p><strong>Material and methods: </strong>In this study, the modified Segmentation-Net (SegNet) model with deep supervision and residual-based skip connection mechanism was trained on 259 glioblastoma patients from the Multimodal Brain Tumour Image Segmentation Benchmark (BraTS) 2019 Challenge dataset for segmentation of gross tumour volume (GTV). Then, the pre-trained CNN model was fine-tuned with an independent clinical dataset (<i>n</i> = 37) to perform the CTV segmentation. In the process of fine-tuning, to generate a CT segmentation mask, both CT and MRI scans were simultaneously used as input data. The performance of the CNN model in terms of segmentation accuracy was evaluated on an independent clinical test dataset (<i>n</i> = 15) using the Dice Similarity Coefficient (DSC) and Hausdorff distance. The impact of auto-segmented CTV definition on dosimetry was also analysed.</p><p><strong>Results: </strong>The proposed model achieved the segmentation results with a DSC of 89.60 ± 3.56% and Hausdorff distance of 1.49 ± 0.65 mm. A statistically significant difference was found for the Dmin and Dmax of the CTV between manually and automatically planned doses.</p><p><strong>Conclusions: </strong>The results of our study suggest that our CNN-based auto-contouring system can be used for segmentation of CTVs to facilitate the brain tumour radiotherapy workflow.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/6a/05/PJR-88-50001.PMC9907163.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10768006","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":"The impact of studying on the hippocampal volume in medical students and its correlation with the results of the Final Medical Examination: a single-centre, prospective observational cohort study.","authors":"Jakub Marek,&nbsp;Edyta Maj,&nbsp;Olga Katarzyna Przybyla,&nbsp;Witold Skrzynski,&nbsp;Katarzyna Pasicz,&nbsp;Ewa Fabiszewska,&nbsp;Andrzej Pruszynski,&nbsp;Olgierd Rowinski","doi":"10.5114/pjr.2023.124433","DOIUrl":"https://doi.org/10.5114/pjr.2023.124433","url":null,"abstract":"<p><strong>Purpose: </strong>The hippocampus forms part of the limbic system and is involved in the learning process; it is responsible for transferring information from short-term to long-term memory. The aim of our study was to assess the effect of intensive studying on hippocampal volume and whether this correlates with exam results.</p><p><strong>Material and methods: </strong>The analysis included volunteer final-year medical students who underwent 2 volumetric 3D T1 magnetic resonance imaging scans with an interval of 20 weeks: 19 weeks before and one week after the Final Medi-cal Examination. FreeSurfer software was used to compare the volumes of the whole hippocampus and its subfields between the 2 measurements. We assessed correlations between changes in hippocampal volume and the time students spent studying, between changes in hippocampal volume and the results of the exam, and between time spent studying and exam results.</p><p><strong>Results: </strong>Forty participants (25 women and 15 men; mean age 25 years) were included in the analysis. The right hippocampus presubiculum area increased significantly over the study period (<i>p</i> = 0.029), whereas the volume of the left hippocampus remained unchanged. An increase in the volume of the right hippocampus correlated with longer study time (<i>r</i> = 0.371 in percentage and <i>r</i> = 0.397 in mm³) and better LEK exam results (<i>r</i> = 0.441 in percentage and <i>r</i> = 0.456 in mm³).</p><p><strong>Conclusions: </strong>Our research confirms the role of the hippocampus, particularly the subicular complex, in the process of learning and remembering, and suggest that the plastic abilities of the hippocampus depend on the intensity of learning and translate into better skills.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/1d/36/PJR-88-50000.PMC9907159.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10768005","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":"Demonstration of chewing-related areas in the brain via functional magnetic resonance imaging.","authors":"Oktay Algin,&nbsp;Orhan Murat Kocak,&nbsp;Yasemin Gokcekuyu,&nbsp;Kemal S Turker","doi":"10.5114/pjr.2023.124756","DOIUrl":"https://doi.org/10.5114/pjr.2023.124756","url":null,"abstract":"<p><strong>Purpose: </strong>To localize and identify chewing-related areas and their connections with other centres in the human brain using functional magnetic resonance imaging (fMRI).</p><p><strong>Material and methods: </strong>The paradigm of the present study was block designed. Spontaneous and controlled chewing with sugar-free gum was used as the main task in a 3-Tesla fMRI unit with a 32-channel birdcage coil. Our study popu-lation comprised 32 healthy volunteers. To determine possible intersections, we also put the rosary pulling (silent tell one's beads) movement in the fMRI protocol. The data analyses were performed with the Statistical Parametric Mapping (SPM) toolbox integrated into the Matlab platform.</p><p><strong>Results: </strong>The superomedial part of the right cerebellum was activated during either pulling rosary beads or spontaneous chewing. This region, however, was not activated during controlled chewing. We did not find statistically significant activation or connection related to the brain stem.</p><p><strong>Conclusion: </strong>We have confirmed that the cerebellum plays an important role in chewing. However, we could not find a definite central pattern generator (CPG) in the brain stem, which has been hypothesized to underlie spontaneous chewing.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/7e/c6/PJR-88-50076.PMC9907160.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10826246","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":"Assessment of sodium (²³Na) brain MRI at 3T - preliminary results.","authors":"Pawel Wawrzyniak,&nbsp;Anna Hebda,&nbsp;Aleksandra Awramienko-Włoczek,&nbsp;Patrycja Mazgaj,&nbsp;Sylwia Heinze,&nbsp;Barbara Bobek-Billewicz","doi":"10.5114/pjr.2023.130252","DOIUrl":"https://doi.org/10.5114/pjr.2023.130252","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this work was to establish a database of tissue sodium concentration (TSC) in the normal brain of healthy volunteers. Tissue sodium concentration can be used as a sensitive marker of tissue viability in stroke or radiation therapy monitoring.</p><p><strong>Material and methods: </strong>Thirty-seven volunteers were scanned with a ²³Na protocol in the span of one year; within this group, 29 studies were of acceptable quality. The study was approved by the Local Bioethics Committee. Data were acquired during a single magnetic resonance (MR) scanner session. The single scanner session consisted of ²³Na 3D radial gradient echo (GRE) acquisition, MPRage, SPACE-FLAIR, and Resolve-DTI. MPRage images were segmented to obtain masks of the grey matter (GM), white matter (WM), and cerebrospinal fluid (CSF), which were registered to the sodium image space for image analysis. Images were transformed into TSC maps - a signal calibration curve obtained from the reference phantom of known sodium concentration and known relaxation time.</p><p><strong>Results: </strong>The collected data were analysed in 2 different ways: volunteers were divided by sex and by age. No significant differences in TSC were found between sexes. In all comparisons there was a significant difference in TSC between younger and older volunteers. In healthy volunteers mean TSC were as follows: GM 33.21 ± 4.76 mmol/l, WM 28.41 ± 4.03 mmol/l and for CSF 41.3 ± 6.69 mmol/l.</p><p><strong>Conclusions: </strong>This preliminary work is a base for further work with sodium imaging in brain lesions. The entirety of the col-lected data will be useful in the future as a baseline brain TSC for comparison to values obtained from pathologies.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9d/9c/PJR-88-51193.PMC10415810.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10001537","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":"⁶⁸Ga-PSMA PET-CT and PSMA score affecting therapeutic decision-making in high-risk prostatic carcinoma.","authors":"Tahira Yasmin,&nbsp;Muhammad Numair Younis,&nbsp;Khalid Ameer,&nbsp;Ahmed Farooq,&nbsp;Abubaker Shahid","doi":"10.5114/pjr.2023.130196","DOIUrl":"https://doi.org/10.5114/pjr.2023.130196","url":null,"abstract":"<p><strong>Purpose: </strong>This research study was conducted to evaluate the impact of (⁶⁸Ga)-tagged prostatic-specific membrane antigen (⁶⁸Ga-PSMA) positron emission tomography and computed tomography (PET-CT), compare its role with conventional radiology in early staging of high-risk prostate cancer, and calculate the PSMA score evaluating its usefulness in ⁶⁸Ga-PSMA PET-CT reporting in our patient population.</p><p><strong>Material and methods: </strong>⁶⁸Ga-PSMA PET-CT of 65 high-risk cases of prostate cancer was performed for staging purpo-ses. Any change in disease stage was noted after ⁶⁸Ga-PSMA PET-CT findings and PSMA score leading to a change in the management plan.</p><p><strong>Results: </strong>Change in disease stage post-PSMA imaging was seen in 39% cases, high PSMA score (03) was noted in > 80% of upstaged cases, while low score (0) and (1) was seen in 65% and 35% down-staged individuals, respectively. Change in therapeutic decision-making was observed in 32% (21) of patients.</p><p><strong>Conclusions: </strong>⁶⁸Ga-PSMA PET-CT scans have a significant influence on the planned clinical management of high-risk prostate cancer patients; hence, they can be utilized as a replacement for radiological imaging tools, particularly in the detection of pelvic nodal and distant metastatic disease. PSMA score can be considered as an effective tool in standardized reporting of ⁶⁸Ga-PSMA imaging.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/8f/bf/PJR-88-51188.PMC10415808.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10001541","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":"Evaluation of peripheral enhancement on contrast-enhanced computed tomography and corresponding pathological findings in colorectal liver metastases after preoperative chemotherapy.","authors":"Akio Tamura,&nbsp;Kazuyuki Ishida,&nbsp;Misato Sone,&nbsp;Kunihiro Yoshioka","doi":"10.5114/pjr.2023.127611","DOIUrl":"https://doi.org/10.5114/pjr.2023.127611","url":null,"abstract":"<p><strong>Purpose: </strong>To correlate peripheral enhancement on contrast-enhanced computed tomography (CE-CT) in patients with post-chemotherapy colorectal liver metastases (CRLM) with the corresponding pathological findings.</p><p><strong>Material and methods: </strong>Forty-four patients with CRLM who underwent hepatic resection after preoperative chemotherapy between 2008 and 2013 were included. Two radiologists blinded to the histopathology findings performed a consensus categorization of the marginal contrast effects of CRLM on CE-CT as follows: Group 1, smooth margin without enhancement; Group 2, smooth margin with an enhanced rim; and Group 3, fuzzy margin with/without an enhanced rim. The Kruskal-Wallis test was used to compare the imaging findings with the histological findings.</p><p><strong>Results: </strong>The percentage of infarct-like necrosis was significantly higher in those with CRLM with smooth margins than in those with CRLM with fuzzy margins (<i>p</i> < 0.001, <i>r</i> = 0.62). The percentage of viable cells was lowest in CRLM with smooth margins without enhancement (<i>p</i> < 0.001, <i>r</i> = 0.60).</p><p><strong>Conclusions: </strong>Our findings suggest that the type of necrosis is related to the nature of the margins, and the presence of residual cells is related to peripheral enhancement.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/87/a7/PJR-88-50707.PMC10280364.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10087921","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}