BACKGROUND The peritumoral region possesses attributes that promote cancer growth and progression.However,the potential prognostic biomarkers in this region remain relatively underexplored in radiomics.AIM To investig...BACKGROUND The peritumoral region possesses attributes that promote cancer growth and progression.However,the potential prognostic biomarkers in this region remain relatively underexplored in radiomics.AIM To investigate the prognostic value and importance of peritumoral radiomics in locally advanced rectal cancer(LARC).METHODS This retrospective study included 409 patients with biopsy-confirmed LARC treated with neoadjuvant chemoradiotherapy and surgically.Patients were divided into training(n=273)and validation(n=136)sets.Based on intratumoral and peritumoral radiomic features extracted from pretreatment axial high-resolution small-field-of-view T2-weighted images,multivariate Cox models for progression-free survival(PFS)prediction were developed with or without clinicoradiological features and evaluated with Harrell’s concordance index(C-index),calibration curve,and decision curve analyses.Risk stratification,Kaplan-Meier analysis,and permutation feature importance analysis were performed.RESULTS The comprehensive integrated clinical-radiological-omics model(ModelICRO)integrating seven peritumoral,three intratumoral,and four clinicoradiological features achieved the highest C-indices(0.836 and 0.801 in the training and validation sets,respectively).This model showed robust calibration and better clinical net benefits,effectively distinguished high-risk from low-risk patients(PFS:97.2%vs 67.6%and 95.4%vs 64.8%in the training and validation sets,respectively;both P<0.001).Three most influential predictors in the comprehensive ModelICRO were,in order,a peritumoral,an intratumoral,and a clinicoradiological feature.Notably,the peritumoral model outperformed the intratumoral model(C-index:0.754 vs 0.670;P=0.015);peritumoral features significantly enhanced the performance of models based on clinicoradiological or intratumoral features or their combinations.CONCLUSION Peritumoral radiomics holds greater prognostic value than intratumoral radiomics for predicting PFS in LARC.The comprehensive model may serve as a reliable tool for better stratification and management postoperatively.展开更多
Introduction: Meningiomas are the most common type of extra-axial neoplasm. Peritumoral brain edema (PTBE) can be seen around meningiomas while it may be absent in others. Despite that Ki67 proliferative index has bee...Introduction: Meningiomas are the most common type of extra-axial neoplasm. Peritumoral brain edema (PTBE) can be seen around meningiomas while it may be absent in others. Despite that Ki67 proliferative index has been previously correlated with meningioma grades, no definite relationship has been established in relation to PTBE in meningioma patients. Objective: Correlate the peritumoral brain edema with the Ki67 proliferative index of meningiomas. Patients & Methods: Aclinical prospective study was conducted on 56 patients (47 women, 9 men;mean age 50.89 ± 12.55 years) diagnosed with meningiomas. All patients were evaluated regarding the presence of brain edema surrounding the lesion in pre-operative neuroimaging using T2W and FLAIR MR images. Immunohistochemical staining of Ki67 index (representing proliferative activity) was done. Correlation between presence of PTBE and Ki67 index values was evaluated. Results: PTBE was found in nearly half of the patients (48.2%), while the remaining (51.8%) of patients did not exhibit PTBE in their pre-operative neuroimaging. The mean value of Ki67 index in meningioma patients with PTBE was 4.83% compared to a value of 1.83% in patients without PTBE, P value = 0.014. Conclusion: High Ki67 indices are evident in meningiomas with surrounding peritumoral brain edema (PTBE).展开更多
Objective: To determine whether VEGF plays a role in the development of peritumoral brain edema. Methods 50 meningioma patients and their VEGF expression were studied. We took a monoclonal antibody from mouse to VEGF ...Objective: To determine whether VEGF plays a role in the development of peritumoral brain edema. Methods 50 meningioma patients and their VEGF expression were studied. We took a monoclonal antibody from mouse to VEGF to stain the tumor cells, the vascular endothelial cells and the interstitial cells. The severity of brain edema was evaluated according to CT or MR scans by the following equation: edema index= V tumor +edema /Vtumor. The relationship between VEGF expression and edema index was analyzed statistically. Results VEGF was expressed in meningioma tumor cells, which is usually concentrated at the peripheral sites of the tumor. There was a positive linear correlation between the expression and the brain edema index. Conclusion VEGF may play a role in the development of peritumoral brain edema in meningioma patient.展开更多
Meningiomas are among the most common primary tumors of the central nervous system. In the past several decades, many researchers have emphasized the importance of radiographic findings and their possible role in pred...Meningiomas are among the most common primary tumors of the central nervous system. In the past several decades, many researchers have emphasized the importance of radiographic findings and their possible role in predicting the various aspects of the meningioma biology. One of the factors most commonly analyzed with respect to the lesions’ clinical behavior is peritumoral brain edema (PTBE), not only one of the most common signs associated with meningiomas, but also a significant clinical problem. Radiographic predictors of PTBE are usually noted as being the size of the tumor, its location, irregular margins, heterogeneity, and the peritumoral arachnoid plane with its pial vascular recruitment. Here, we review the available literature on the topic of these radiographic predictors of PTBE formation, we analyze the methodology of the research conducted, and we highlight the many controversies still present. Indeed, the evidence about PTBE pathogenesis, predictive factors, and clinical significance still seems to be mostly inconclusive, despite intense research in the area. We believe that by highlighting the many inconsistencies in the methodology used, we can showcase how little is actually known about the pathogenesis of PTBE, which in turn has important clinical implications. Additionally, we provide several MR images of intracranial meningiomas from our own practice which, we believe, showcase the unpredictable nature of PTBE, and demonstrate vividly the topics we discuss.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making pr...BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making precise treatment plans and improving patient prognosis.AIM To establish an intratumoral and peritumoral model for predicting ER in HCC patients following curative ablation.METHODS This study included a total of 288 patients from three Centers.The patients were divided into a primary cohort(n=222)and an external cohort(n=66).Radiomics and deep learning methods were combined for feature extraction,and models were constructed following a three-step feature selection process.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),while calibration curves and decision curve analysis(DCA)were used to assess calibration and clinical utility.Finally,Kaplan-Meier(K-M)analysis was used to stratify patients according to progression-free survival(PFS)and overall survival(OS).RESULTS The combined model,which utilizes the light gradient boosting machine learning algorithm and incorporates both intratumoral and peritumoral regions(5 mm and 10 mm),demonstrated the best predictive performance for ER following HCC ablation,achieving AUCs of 0.924 in the training set,0.899 in the internal validation set,and 0.839 in the external validation set.Calibration and DCA curves confirmed strong calibration and clinical utility,whereas K-M curves provided risk stratification for PFS and OS in HCC patients.CONCLUSION The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions.This model provides a noninvasive,effective,and reliable method for predicting ER after curative ablation of HCC.展开更多
BACKGROUND Accurate preoperative T staging is essential for determining optimal treatment strategies in colorectal cancer(CRC).Low-keV virtual monoenergetic images(VMIs)have been shown to enhance lesion conspicuity.Th...BACKGROUND Accurate preoperative T staging is essential for determining optimal treatment strategies in colorectal cancer(CRC).Low-keV virtual monoenergetic images(VMIs)have been shown to enhance lesion conspicuity.This study aimed to assess the diagnostic value of dual-layer spectral computed tomography(CT)-derived VMIs,in combination with multiplanar reformation(MPR)and evaluation of peritumoral fat stranding(PFS),for improving the accuracy of T staging in CRC.AIM To assess the diagnostic performance of dual-layer spectral CT(DLSCT)VMIs,particularly at low energy levels,and their integration with personalized MPR for preoperative T staging of CRC.METHODS In this retrospective study,157 patients with pathologically confirmed CRC(mean age:63.5±12.1 years)underwent DLSCT within 1 week before surgery.VMIs ranging from 40 keV to 70 keV(at 10 keV intervals)and conventional polyenergetic images(PEIs)were reconstructed.Objective image quality parameters,including image noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR),were quantified,alongside subjective image quality scores using a 5-point Likert scale.Interobserver agreement was evaluated usingκstatistics.Taking histopathology as the reference standard,the diagnostic accuracy of T staging(T1-2 vs T3-4)was compared across PEIs and VMIs,both with and without MPR and PFS.RESULTS Low-keV VMIs(40-70 keV)demonstrated significantly higher SNR and CNR than PEIs(all P<0.001).Notably,40-keV VMIs achieved noise levels comparable to PEIs(8.17±3.63 vs 8.53±2.90;P=0.673).Subjective image quality peaked at 40-50 keV VMIs(Likert scores 4.85-4.88 vs 3.97 for PEIs;P<0.001),supported by excellent interobserver agreement(κ=0.812-0.913).The combination of 40-50 keV VMIs with MPR yielded the highest T staging accuracy(94.27%)compared to axial PEIs(70.7%),with a sensitivity and specificity of 83.87%and 96.83%,respectively(Youden index=0.81;P<0.05).While PFS enhanced staging accuracy on PEIs(up to 77.07%with MPR),it provided no significant additional benefit for VMIs.CONCLUSION DLSCT VMIs at 40-50 keV significantly enhanced image quality and improved preoperative T staging accuracy of CRC when combined with MPR.These findings underscored the clinical value of low-keV spectral imaging in tailoring individualized treatment strategies.展开更多
BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in a...BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.展开更多
Metabolic reprogramming is a key feature driving oncogenesis in cancers. Recent studies have revealed that protein metabolism is largely altered in gliomas facilitating its malignant growth. Urea is the end product of...Metabolic reprogramming is a key feature driving oncogenesis in cancers. Recent studies have revealed that protein metabolism is largely altered in gliomas facilitating its malignant growth. Urea is the end product of nitrogen metabolism which is mainly produced by arginase. The interdependence of arginase and other biochemical mechanisms triggered scientific research interest. This research aimed to investigate the relationships between the urea as the main parameter of protein metabolism and glioma progression. It was also the most pronounced relationship between urea and the level of the nuclear protein Ki-67 as a marker of proliferative activity and O-6-methylguanine-DNA methyltransferase (MGMT), which performs DNA repair. Postoperative material from 20 patients with gliomas of different grades of anaplasia was analyzed.展开更多
Background and purpose:There exist two major consensus guidelines for target delineation in glioblastoma(GBM).Namely the established radiation therapy oncology group(RTOG)and the recently redefined European society fo...Background and purpose:There exist two major consensus guidelines for target delineation in glioblastoma(GBM).Namely the established radiation therapy oncology group(RTOG)and the recently redefined European society for radiation oncology(EORTC)-advisory committee on radiation oncology practice(ACROP),clinical studies evaluating the pattern of recurrence with relation to the CTV margins have as of date not evidenced statistically significant difference in relation to the two guidelines.However,considering the standardization of concurrent chemo-radiation with Temozolomide nearly 20%off patients can be expected to survive 2years or beyond.Quality of life issues will play a higher role in defining the better protocol.In the current study,we have dosimetrically compared these guidelines in both perspectives.Material and methods:Thirty patients of GBM who had been planned for conformal radiotherapy during Jan 2017 to Feb 2019 were considered.Each patient dataset contoured with ESTRO-ACROP guidelines to create PLAN A and RTOG guidelines to create PLAN B.Both plans were compared to evaluate the volumetric difference in terms of PTV and the relative proximity to critical normal structures.Results:The median volume of brain irradiated to high doses(60Gy)was significantly greater in PLAN B,566cc vs 398 cc(P<0.0002).The organs at risk were better spared with PLAN A in terms of encroachment of high dose PTV volume.This achieved significance for Brainstem(P<0.01),Chiasma(P<0.04)and hippocampus(P<0.016).We were able to identify patients with PTV volume>400cc and with tumor in Parietal or Temporal regions wouldn’t benefit from PLAN A.Conclusion:The use of target delineation based on a single step plan,excluding expanded edema(ESTRO-ACROP)could potentially reduce high dose target volumes and significantly spare brainstem,optic-chiasma,and hippocampus.Patients with tumor volume<400 cc and frontal lesions are most likely to benefit.展开更多
文摘BACKGROUND The peritumoral region possesses attributes that promote cancer growth and progression.However,the potential prognostic biomarkers in this region remain relatively underexplored in radiomics.AIM To investigate the prognostic value and importance of peritumoral radiomics in locally advanced rectal cancer(LARC).METHODS This retrospective study included 409 patients with biopsy-confirmed LARC treated with neoadjuvant chemoradiotherapy and surgically.Patients were divided into training(n=273)and validation(n=136)sets.Based on intratumoral and peritumoral radiomic features extracted from pretreatment axial high-resolution small-field-of-view T2-weighted images,multivariate Cox models for progression-free survival(PFS)prediction were developed with or without clinicoradiological features and evaluated with Harrell’s concordance index(C-index),calibration curve,and decision curve analyses.Risk stratification,Kaplan-Meier analysis,and permutation feature importance analysis were performed.RESULTS The comprehensive integrated clinical-radiological-omics model(ModelICRO)integrating seven peritumoral,three intratumoral,and four clinicoradiological features achieved the highest C-indices(0.836 and 0.801 in the training and validation sets,respectively).This model showed robust calibration and better clinical net benefits,effectively distinguished high-risk from low-risk patients(PFS:97.2%vs 67.6%and 95.4%vs 64.8%in the training and validation sets,respectively;both P<0.001).Three most influential predictors in the comprehensive ModelICRO were,in order,a peritumoral,an intratumoral,and a clinicoradiological feature.Notably,the peritumoral model outperformed the intratumoral model(C-index:0.754 vs 0.670;P=0.015);peritumoral features significantly enhanced the performance of models based on clinicoradiological or intratumoral features or their combinations.CONCLUSION Peritumoral radiomics holds greater prognostic value than intratumoral radiomics for predicting PFS in LARC.The comprehensive model may serve as a reliable tool for better stratification and management postoperatively.
文摘Introduction: Meningiomas are the most common type of extra-axial neoplasm. Peritumoral brain edema (PTBE) can be seen around meningiomas while it may be absent in others. Despite that Ki67 proliferative index has been previously correlated with meningioma grades, no definite relationship has been established in relation to PTBE in meningioma patients. Objective: Correlate the peritumoral brain edema with the Ki67 proliferative index of meningiomas. Patients & Methods: Aclinical prospective study was conducted on 56 patients (47 women, 9 men;mean age 50.89 ± 12.55 years) diagnosed with meningiomas. All patients were evaluated regarding the presence of brain edema surrounding the lesion in pre-operative neuroimaging using T2W and FLAIR MR images. Immunohistochemical staining of Ki67 index (representing proliferative activity) was done. Correlation between presence of PTBE and Ki67 index values was evaluated. Results: PTBE was found in nearly half of the patients (48.2%), while the remaining (51.8%) of patients did not exhibit PTBE in their pre-operative neuroimaging. The mean value of Ki67 index in meningioma patients with PTBE was 4.83% compared to a value of 1.83% in patients without PTBE, P value = 0.014. Conclusion: High Ki67 indices are evident in meningiomas with surrounding peritumoral brain edema (PTBE).
文摘Objective: To determine whether VEGF plays a role in the development of peritumoral brain edema. Methods 50 meningioma patients and their VEGF expression were studied. We took a monoclonal antibody from mouse to VEGF to stain the tumor cells, the vascular endothelial cells and the interstitial cells. The severity of brain edema was evaluated according to CT or MR scans by the following equation: edema index= V tumor +edema /Vtumor. The relationship between VEGF expression and edema index was analyzed statistically. Results VEGF was expressed in meningioma tumor cells, which is usually concentrated at the peripheral sites of the tumor. There was a positive linear correlation between the expression and the brain edema index. Conclusion VEGF may play a role in the development of peritumoral brain edema in meningioma patient.
文摘Meningiomas are among the most common primary tumors of the central nervous system. In the past several decades, many researchers have emphasized the importance of radiographic findings and their possible role in predicting the various aspects of the meningioma biology. One of the factors most commonly analyzed with respect to the lesions’ clinical behavior is peritumoral brain edema (PTBE), not only one of the most common signs associated with meningiomas, but also a significant clinical problem. Radiographic predictors of PTBE are usually noted as being the size of the tumor, its location, irregular margins, heterogeneity, and the peritumoral arachnoid plane with its pial vascular recruitment. Here, we review the available literature on the topic of these radiographic predictors of PTBE formation, we analyze the methodology of the research conducted, and we highlight the many controversies still present. Indeed, the evidence about PTBE pathogenesis, predictive factors, and clinical significance still seems to be mostly inconclusive, despite intense research in the area. We believe that by highlighting the many inconsistencies in the methodology used, we can showcase how little is actually known about the pathogenesis of PTBE, which in turn has important clinical implications. Additionally, we provide several MR images of intracranial meningiomas from our own practice which, we believe, showcase the unpredictable nature of PTBE, and demonstrate vividly the topics we discuss.
基金Supported by Anhui Provincial Key Research and Development Plan,No.202104j07020048.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy.Ablation therapy is one of the first-line treatments for early HCC.Accurately predicting early recurrence(ER)is crucial for making precise treatment plans and improving patient prognosis.AIM To establish an intratumoral and peritumoral model for predicting ER in HCC patients following curative ablation.METHODS This study included a total of 288 patients from three Centers.The patients were divided into a primary cohort(n=222)and an external cohort(n=66).Radiomics and deep learning methods were combined for feature extraction,and models were constructed following a three-step feature selection process.Model performance was evaluated using the area under the receiver operating characteristic curve(AUC),while calibration curves and decision curve analysis(DCA)were used to assess calibration and clinical utility.Finally,Kaplan-Meier(K-M)analysis was used to stratify patients according to progression-free survival(PFS)and overall survival(OS).RESULTS The combined model,which utilizes the light gradient boosting machine learning algorithm and incorporates both intratumoral and peritumoral regions(5 mm and 10 mm),demonstrated the best predictive performance for ER following HCC ablation,achieving AUCs of 0.924 in the training set,0.899 in the internal validation set,and 0.839 in the external validation set.Calibration and DCA curves confirmed strong calibration and clinical utility,whereas K-M curves provided risk stratification for PFS and OS in HCC patients.CONCLUSION The most efficient model integrated the tumor region with the peritumoral 5 mm and 10 mm regions.This model provides a noninvasive,effective,and reliable method for predicting ER after curative ablation of HCC.
基金Supported by Jiangsu Province 333 Talent Key Industry Field Talent Project,No.[2022]21Key Scientific Research Program of Jiangsu Provincial Health Committee,No.ZD2021059+2 种基金Nantong Key Laboratory Project,No.[2020]163The Project of Nantong City Health Committee,No.MS2023027Young Medical Talents Fund of Health and Family Planning Commission of Nantong,No.QA2019006 and No.QNZ2023027.
文摘BACKGROUND Accurate preoperative T staging is essential for determining optimal treatment strategies in colorectal cancer(CRC).Low-keV virtual monoenergetic images(VMIs)have been shown to enhance lesion conspicuity.This study aimed to assess the diagnostic value of dual-layer spectral computed tomography(CT)-derived VMIs,in combination with multiplanar reformation(MPR)and evaluation of peritumoral fat stranding(PFS),for improving the accuracy of T staging in CRC.AIM To assess the diagnostic performance of dual-layer spectral CT(DLSCT)VMIs,particularly at low energy levels,and their integration with personalized MPR for preoperative T staging of CRC.METHODS In this retrospective study,157 patients with pathologically confirmed CRC(mean age:63.5±12.1 years)underwent DLSCT within 1 week before surgery.VMIs ranging from 40 keV to 70 keV(at 10 keV intervals)and conventional polyenergetic images(PEIs)were reconstructed.Objective image quality parameters,including image noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR),were quantified,alongside subjective image quality scores using a 5-point Likert scale.Interobserver agreement was evaluated usingκstatistics.Taking histopathology as the reference standard,the diagnostic accuracy of T staging(T1-2 vs T3-4)was compared across PEIs and VMIs,both with and without MPR and PFS.RESULTS Low-keV VMIs(40-70 keV)demonstrated significantly higher SNR and CNR than PEIs(all P<0.001).Notably,40-keV VMIs achieved noise levels comparable to PEIs(8.17±3.63 vs 8.53±2.90;P=0.673).Subjective image quality peaked at 40-50 keV VMIs(Likert scores 4.85-4.88 vs 3.97 for PEIs;P<0.001),supported by excellent interobserver agreement(κ=0.812-0.913).The combination of 40-50 keV VMIs with MPR yielded the highest T staging accuracy(94.27%)compared to axial PEIs(70.7%),with a sensitivity and specificity of 83.87%and 96.83%,respectively(Youden index=0.81;P<0.05).While PFS enhanced staging accuracy on PEIs(up to 77.07%with MPR),it provided no significant additional benefit for VMIs.CONCLUSION DLSCT VMIs at 40-50 keV significantly enhanced image quality and improved preoperative T staging accuracy of CRC when combined with MPR.These findings underscored the clinical value of low-keV spectral imaging in tailoring individualized treatment strategies.
基金The study was reviewed and approved by the Second Hospital of Shandong University Institutional Review Board,IRB No.KYLL-2023LW044.
文摘BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.
文摘Metabolic reprogramming is a key feature driving oncogenesis in cancers. Recent studies have revealed that protein metabolism is largely altered in gliomas facilitating its malignant growth. Urea is the end product of nitrogen metabolism which is mainly produced by arginase. The interdependence of arginase and other biochemical mechanisms triggered scientific research interest. This research aimed to investigate the relationships between the urea as the main parameter of protein metabolism and glioma progression. It was also the most pronounced relationship between urea and the level of the nuclear protein Ki-67 as a marker of proliferative activity and O-6-methylguanine-DNA methyltransferase (MGMT), which performs DNA repair. Postoperative material from 20 patients with gliomas of different grades of anaplasia was analyzed.
文摘Background and purpose:There exist two major consensus guidelines for target delineation in glioblastoma(GBM).Namely the established radiation therapy oncology group(RTOG)and the recently redefined European society for radiation oncology(EORTC)-advisory committee on radiation oncology practice(ACROP),clinical studies evaluating the pattern of recurrence with relation to the CTV margins have as of date not evidenced statistically significant difference in relation to the two guidelines.However,considering the standardization of concurrent chemo-radiation with Temozolomide nearly 20%off patients can be expected to survive 2years or beyond.Quality of life issues will play a higher role in defining the better protocol.In the current study,we have dosimetrically compared these guidelines in both perspectives.Material and methods:Thirty patients of GBM who had been planned for conformal radiotherapy during Jan 2017 to Feb 2019 were considered.Each patient dataset contoured with ESTRO-ACROP guidelines to create PLAN A and RTOG guidelines to create PLAN B.Both plans were compared to evaluate the volumetric difference in terms of PTV and the relative proximity to critical normal structures.Results:The median volume of brain irradiated to high doses(60Gy)was significantly greater in PLAN B,566cc vs 398 cc(P<0.0002).The organs at risk were better spared with PLAN A in terms of encroachment of high dose PTV volume.This achieved significance for Brainstem(P<0.01),Chiasma(P<0.04)and hippocampus(P<0.016).We were able to identify patients with PTV volume>400cc and with tumor in Parietal or Temporal regions wouldn’t benefit from PLAN A.Conclusion:The use of target delineation based on a single step plan,excluding expanded edema(ESTRO-ACROP)could potentially reduce high dose target volumes and significantly spare brainstem,optic-chiasma,and hippocampus.Patients with tumor volume<400 cc and frontal lesions are most likely to benefit.
