AIM: To discuss the advantages of ultra-high field (7T) for 1H and 13C magnetic resonance spectroscopy (MRS) studies of metabolism.made at both 3 and 7T using 1H MRS. Measurements of glycogen and lipids in muscle were...AIM: To discuss the advantages of ultra-high field (7T) for 1H and 13C magnetic resonance spectroscopy (MRS) studies of metabolism.made at both 3 and 7T using 1H MRS. Measurements of glycogen and lipids in muscle were measured using 13C and 1H MRS respectively. RESULTS: In the brain, increased signal-to-noise ratio (SNR) and dispersion allows spectral separation of the amino-acids glutamate, glutamine and γ-aminobutyric acid (GABA), without the need for sophisticated editing sequences. Improved quantification of these me-tabolites is demonstrated at 7T relative to 3T. SNR was 36% higher, and measurement repeatability (% coefficients of variation) was 4%, 10% and 10% at 7T, vs 8%, 29% and 21% at 3T for glutamate, glutamine and GABA respectively. Measurements at 7T were used to compare metabolite levels in the anterior cingulate cortex (ACC) and insula. Creatine and glutamate levels were found to be significantly higher in the insula compared to the ACC (P 【 0.05). In muscle, the increased SNR and spectral resolution at 7T enables interleaved studies of glycogen (13C) and intra-myocellular lipid (IMCL) and extra-myocellular lipid (EMCL) (1H) following exercise and refeeding. Glycogen levels were sig-nificantly decreased following exercise (-28% at 50% VO2 max; -58% at 75% VO2 max). Interestingly, levels of glycogen in the hamstrings followed those in the quadriceps, despite reduce exercise loading. No changes in IMCL and EMCL were found in the study. CONCLUSION: The demonstrated improvements in brain and muscle MRS measurements at 7T will increase the potential for use in investigating human metabolism and changes due to pathologies.展开更多
BACKGROUND Artificial intelligence in radiology has the potential to assist with the diagnosis,prognostication and therapeutic response prediction of various cancers.A few studies have reported that texture analysis c...BACKGROUND Artificial intelligence in radiology has the potential to assist with the diagnosis,prognostication and therapeutic response prediction of various cancers.A few studies have reported that texture analysis can be helpful in predicting the response to chemotherapy for colorectal liver metastases,however,the results have varied.Necrotic metastases were not clearly excluded in these studies and in most studies the full range of texture analysis features were not evaluated.This study was designed to determine if the computed tomography(CT)texture analysis results of non-necrotic colorectal liver metastases differ from previous reports.A larger range of texture features were also evaluated to identify potential new biomarkers.AIM To identify potential new imaging biomarkers with CT texture analysis which can predict the response to first-line cytotoxic chemotherapy in non-necrotic colorectal liver metastases(CRLMs).METHODS Patients who presented with CRLMs from 2012 to 2020 were retrospectively selected on the institutional radiology information system of our private radiology practice.The inclusion criteria were non-necrotic CRLMs with a minimum size of 10 mm(diagnosed on archived 1.25 mm portal venous phase CT(FOLFOX,FOLFIRI,FOLFOXIRI,CAPE-OX,CAPE-IRI or capecitabine).The final study cohort consisted of 29 patients.The treatment response of the CRLMs was classified according to the RECIST 1.1 criteria.By means of CT texture analysis,various first and second order texture features were extracted from a single nonnecrotic target CRLM in each responding and non-responding patient.Associations between features and response to chemotherapy were assessed by logistic regression models.The prognostic accuracy of selected features was evaluated by using the area under the curve.RESULTS There were 15 responders(partial response)and 14 non-responders(7 stable and 7 with progressive disease).The responders presented with a higher number of CRLMs(P=0.05).In univariable analysis,eight texture features of the responding CRLMs were associated with treatment response,but due to strong correlations among some of the features,only two features,namely minimum histogram gradient intensity and long run low grey level emphasis,were included in the multiple analysis.The area under the receiver operating characteristic curve of the multiple model was 0.80(95%CI:0.64 to 0.96),with a sensitivity of 0.73(95%CI:0.48 to 0.89)and a specificity of 0.79(95%CI:0.52 to 0.92).CONCLUSION Eight first and second order texture features,but particularly minimum histogram gradient intensity and long run low grey level emphasis are significantly correlated with treatment response in non-necrotic CRLMs.展开更多
基金Supported by The Haldane-Spearman Consortium for PhD funding for Dr. Gunner F, Swecarb AB for provision of the carbo-hydrate drink，and Pfizer for funding the 1H Repeatability work Dr.Stephenson M was supported by the University of Notting-ham’s Mansfield Fellowship scheme+2 种基金7T work was supported by grant G9900259 from the Medical Research CouncilPfizer and grant G0901321 from the Medical Research CouncilThe 7 T MR Scanner in Nottingham, was funded by a Joint Infrastructure Fund Grant from the Wellcome Trust UK
文摘AIM: To discuss the advantages of ultra-high field (7T) for 1H and 13C magnetic resonance spectroscopy (MRS) studies of metabolism.made at both 3 and 7T using 1H MRS. Measurements of glycogen and lipids in muscle were measured using 13C and 1H MRS respectively. RESULTS: In the brain, increased signal-to-noise ratio (SNR) and dispersion allows spectral separation of the amino-acids glutamate, glutamine and γ-aminobutyric acid (GABA), without the need for sophisticated editing sequences. Improved quantification of these me-tabolites is demonstrated at 7T relative to 3T. SNR was 36% higher, and measurement repeatability (% coefficients of variation) was 4%, 10% and 10% at 7T, vs 8%, 29% and 21% at 3T for glutamate, glutamine and GABA respectively. Measurements at 7T were used to compare metabolite levels in the anterior cingulate cortex (ACC) and insula. Creatine and glutamate levels were found to be significantly higher in the insula compared to the ACC (P 【 0.05). In muscle, the increased SNR and spectral resolution at 7T enables interleaved studies of glycogen (13C) and intra-myocellular lipid (IMCL) and extra-myocellular lipid (EMCL) (1H) following exercise and refeeding. Glycogen levels were sig-nificantly decreased following exercise (-28% at 50% VO2 max; -58% at 75% VO2 max). Interestingly, levels of glycogen in the hamstrings followed those in the quadriceps, despite reduce exercise loading. No changes in IMCL and EMCL were found in the study. CONCLUSION: The demonstrated improvements in brain and muscle MRS measurements at 7T will increase the potential for use in investigating human metabolism and changes due to pathologies.
文摘BACKGROUND Artificial intelligence in radiology has the potential to assist with the diagnosis,prognostication and therapeutic response prediction of various cancers.A few studies have reported that texture analysis can be helpful in predicting the response to chemotherapy for colorectal liver metastases,however,the results have varied.Necrotic metastases were not clearly excluded in these studies and in most studies the full range of texture analysis features were not evaluated.This study was designed to determine if the computed tomography(CT)texture analysis results of non-necrotic colorectal liver metastases differ from previous reports.A larger range of texture features were also evaluated to identify potential new biomarkers.AIM To identify potential new imaging biomarkers with CT texture analysis which can predict the response to first-line cytotoxic chemotherapy in non-necrotic colorectal liver metastases(CRLMs).METHODS Patients who presented with CRLMs from 2012 to 2020 were retrospectively selected on the institutional radiology information system of our private radiology practice.The inclusion criteria were non-necrotic CRLMs with a minimum size of 10 mm(diagnosed on archived 1.25 mm portal venous phase CT(FOLFOX,FOLFIRI,FOLFOXIRI,CAPE-OX,CAPE-IRI or capecitabine).The final study cohort consisted of 29 patients.The treatment response of the CRLMs was classified according to the RECIST 1.1 criteria.By means of CT texture analysis,various first and second order texture features were extracted from a single nonnecrotic target CRLM in each responding and non-responding patient.Associations between features and response to chemotherapy were assessed by logistic regression models.The prognostic accuracy of selected features was evaluated by using the area under the curve.RESULTS There were 15 responders(partial response)and 14 non-responders(7 stable and 7 with progressive disease).The responders presented with a higher number of CRLMs(P=0.05).In univariable analysis,eight texture features of the responding CRLMs were associated with treatment response,but due to strong correlations among some of the features,only two features,namely minimum histogram gradient intensity and long run low grey level emphasis,were included in the multiple analysis.The area under the receiver operating characteristic curve of the multiple model was 0.80(95%CI:0.64 to 0.96),with a sensitivity of 0.73(95%CI:0.48 to 0.89)and a specificity of 0.79(95%CI:0.52 to 0.92).CONCLUSION Eight first and second order texture features,but particularly minimum histogram gradient intensity and long run low grey level emphasis are significantly correlated with treatment response in non-necrotic CRLMs.
