Five years have passed since the Japan Narrow Band Imaging Expert Team (JNET) classification was proposed in 2014. However, the diagnostic performance of this classification has not yet been established. We conducted ...Five years have passed since the Japan Narrow Band Imaging Expert Team (JNET) classification was proposed in 2014. However, the diagnostic performance of this classification has not yet been established. We conducted a retrospective study and a systematic search of Medical Literature Analysis and Retrieval System On-Line. There were three retrospective single center studies about the diagnostic performance of this classification. In order to clarify this issue, we reviewed our study and three previous studies. This review revealed the diagnostic performance in regards to three important differentiations.(1) Neoplasia from non-neoplasia;(2) malignant neoplasia from benign neoplasia;and (3) deep submucosal invasive cancer (D-SMC) from other neoplasia. The sensitivity in differentiating neoplasia from non-neoplasia was 98.1%-99.8%. The specificity in differentiating malignant neoplasia from benign neoplasia was 84.7%-98.2% and the specificity in the differentiation D-SMC from other neoplasia was 99.8%-100.0%. This classification would enable endoscopists to identify almost all neoplasia, to appropriately determine whether to perform en bloc resection or not, and to avoid unnecessary surgery. This article is the first review about the diagnostic performance of the JNET classification. Previous reports about the diagnostic performance have all been retrospective single center studies. A large-scale prospective multicenter evaluation study is awaited for the validation.展开更多
AIM:To retrospectively evaluate the imaging features of pancreatic intraductal papillary mucinous neoplasms (IPMNs) in multi-detector row computed tomography (MDCT).METHODS: A total of 20 patients with pathologically-...AIM:To retrospectively evaluate the imaging features of pancreatic intraductal papillary mucinous neoplasms (IPMNs) in multi-detector row computed tomography (MDCT).METHODS: A total of 20 patients with pathologically-confirmed intraductal papillary mucinous neoplasms (IPMNs) were included in this study. Axial MDCT images combined with CT angiography (CTA) and multiplanar volume reformations (MPVR) or curved reformations (CR) were preoperatively acquired. Two radiologists (Tan L and Wang DB) reviewed all the images in consensus using an interactive picture archiving and communication system. The disputes in readings were resolved through consultation with a third experienced radiologist (Chen KM). Finally, the findings and diagnoses were compared with the pathologic results.RESULTS: The pathological study revealed 12 malignant IPMNs and eight benign IPMNs. The diameters of the cystic lesions and main pancreatic ducts (MPDs) were significantly larger in malignant IPMNs compared with those of the benign IPMNs (P<0.05). The combined-type IPMNs had a higher rate of malignancy than the other two types of IPMNs (P<0.05). Tumors with mural nodules and thick septa had a significantly higher incidence of malignancy than tumors without these features (P<0.05). Communication of side-branch IPMNs with the MPD was present in nine cases at pathologic examination. Seven of them were identified from CTA and MPVR or CR images. From comparison with the pathological diagnosis, the sensitivity, specificity, and accuracy of MDCT in characterizing the malignancy of IPMN of the pancreas were determined to be 100%, 87.5% and 95%, respectively.CONCLUSION: MDCT with CTA and MPVR or CR techniques can elucidate the imaging features of IPMNs and help predict the malignancy of these tumors.展开更多
AIM To establish the ability of magnetic resonance(MR) and computer tomography(CT) to predict pathologic dimensions of pancreatic neuroendocrine tumors(Pan NET) in a caseload of a tertiary referral center.METHODS Pati...AIM To establish the ability of magnetic resonance(MR) and computer tomography(CT) to predict pathologic dimensions of pancreatic neuroendocrine tumors(Pan NET) in a caseload of a tertiary referral center.METHODS Patients submitted to surgery for Pan NET at the Surgical Unit of the Pancreas Institute with at least 1 preoperative imaging examination(MR or CT scan) from January 2005 to December 2015 were included and data retrospectively collected. Exclusion criteria were: multifocal lesions, genetic syndromes, microadenomas or mixed tumors, metastatic disease and neoadjuvant therapy. Bland-Altman(BA) and Mountain-Plot(MP) statistics were used to compare size measured by each modality with the pathology size. Passing-Bablok(PB) regression analysis was used to check the agreement between MR and CT.RESULTS Our study population consisted of 292 patients. Seventy-nine(27.1%) were functioning Pan NET. The mean biases were 0.17 ± 7.99 mm, 1 ± 8.51 mm and 0.23 ± 9 mm, 1.2 ± 9.8 mm for MR and CT, considering the overall population and the subgroup of non-functioning-Pan NET, respectively. Limits of agreement(LOA) included the vast majority of observations, indicating a good agreement between imaging and pathology. The MP further confirmed this finding and showed that the two methods are unbiased with respect to each other. Considering ≤ 2 cm non-functioning-Pan NET, no statistical significance was found in the size estimation rate of MR and CT(P = 0.433). PBR analysis did not reveal significant differences between MR, CT and pathology.CONCLUSION MR and CT scan are accurate and interchangeable imaging techniques in predicting pathologic dimensions of Pan NET.展开更多
BACKGROUND It is unclear whether the Japan Narrow-Band Imaging Expert Team(JNET)classification and pit pattern classification are applicable for diagnosing neoplastic lesions in patients with ulcerative colitis(UC).AI...BACKGROUND It is unclear whether the Japan Narrow-Band Imaging Expert Team(JNET)classification and pit pattern classification are applicable for diagnosing neoplastic lesions in patients with ulcerative colitis(UC).AIM To clarify the diagnostic performance of these classifications for neoplastic lesions in patients with UC.METHODS This study was conducted as a single-center,retrospective case-control study.Twenty-one lesions in 19 patients with UC-associated neoplasms(UCAN)and 23 lesions in 22 UC patients with sporadic neoplasms(SN),evaluated by magnifying image-enhanced endoscopy,were retrospectively and separately assessed by six endoscopists(three experts,three non-experts),using the JNET and pit pattern classifications.The results were compared with the pathological diagnoses to evaluate the diagnostic performance.Inter-and intra-observer agreements were calculated.RESULTS In this study,JNET type 2 A and pit pattern typeⅢ/Ⅳwere used as indicators of low-grade dysplasia,JNET type 2 B and pit pattern typeⅥlow irregularity were used as indicators of highgrade dysplasia to shallow submucosal invasive carcinoma,JNET type 3 and pit pattern typeⅥhigh irregularity/VN were used as indicators of deep submucosal invasive carcinoma.In the UCAN group,JNET type 2 A and pit pattern typeⅢ/Ⅳhad a low positive predictive value(PPV;50.0%and 40.0%,respectively);however,they had a high negative predictive value(NPV;94.7%and 100%,respectively).Conversely,in the SN group,JNET type 2 A and pit pattern typeⅢ/Ⅳhad a high PPV(100%for both)but a low NPV(63.6%and 77.8%,respectively).In both groups,JNET type 3 and pit pattern typeⅥ-high irregularity/VN showed high specificity.The interobserver agreement of JNET classification and pit pattern classification for UCAN among experts were 0.401 and 0.364,in the same manner for SN,0.666 and 0.597,respectively.The intra-observer agreements of JNET classification and pit pattern classification for UCAN among experts were 0.387,0.454,for SN,0.803 and 0.567,respectively.CONCLUSION The accuracy of endoscopic diagnosis using both classifications was lower for UCAN than for SN.Endoscopic diagnosis of UCAN tended to be underestimated compared with the pathological results.展开更多
BACKGROUND Challenging lesions,difficult to diagnose through non-invasive methods,constitute an important emotional burden for each patient regarding a still uncertain diagnosis(malignant x benign).In addition,from a ...BACKGROUND Challenging lesions,difficult to diagnose through non-invasive methods,constitute an important emotional burden for each patient regarding a still uncertain diagnosis(malignant x benign).In addition,from a therapeutic and prognostic point of view,delay in a definitive diagnosis can lead to worse outcomes.One of the main innovative trends currently is the use of molecular and functional methods to diagnosis.Numerous liver-specific contrast agents havebeen developed and studied in recent years to improve the performance of liver magnetic resonance imaging(MRI).More recently,one of the contrast agents introduced in clinical practice is gadoxetic acid(gadoxetate disodium).AIM To demonstrate the value of the hepatobiliary phases using gadoxetic acid in MRI for the characterization of focal liver lesions(FLL)in clinical practice.METHODS Overall,302 Lesions were studied in 136 patients who underwent MRI exams using gadoxetic acid for the assessment of FLL.Two radiologists independently reviewed the MRI exams using four stages,and categorized them on a 6-point scale,from 0(lesion not detected)to 5(definitely malignant).The stages were:stage 1-images without contrast,stage 2-addition of dynamic phases after contrast(analogous to usual extracellular contrasts),stage 3-addition of hepatobiliary phase after 10 min(HBP 10’),stage 4-hepatobiliary phase after 20 min(HBP 20’)in addition to stage 2.RESULTS The interobserver agreement was high(weighted Kappa coefficient:0.81-1)at all stages in the characterization of benign and malignant FLL.The diagnostic weighted accuracy(Az)was 0.80 in stage 1 and was increased to 0.90 in stage 2.Addition of the hepatobiliary phase increased Az to 0.98 in stage 3,which was also 0.98 in stage 4.CONCLUSION The hepatobiliary sequences improve diagnostic accuracy.With growing potential in the era of precision medicine,the improvement and dissemination of the method among medical specialties can bring benefits in the management of patients with FLL that are difficult to diagnose.展开更多
BACKGROUND Appendiceal tumors are rare lesions that may not be easily differentiated from primary ovarian lesions preoperatively,despite the use of advanced diagnostic methods by experienced clinicians.CASE SUMMARY A ...BACKGROUND Appendiceal tumors are rare lesions that may not be easily differentiated from primary ovarian lesions preoperatively,despite the use of advanced diagnostic methods by experienced clinicians.CASE SUMMARY A 59-year-old G2P2 woman,with chronic pelvic pain,underwent a pelvic ultrasound that revealed an adnexal mass measuring 58 mm×34 mm×36 mm,with irregular borders,heterogeneous echogenicity,no color Doppler vascularization and without acoustic shadowing.Normal ovarian tissue was visualized in contact with the lesion,and it was impossible to separate the lesion from the ovary by applying pressure with the ultrasound probe.Ascites,peritoneal metastases or other alterations were not observed.With the international ovarian tumor analysis ADNEX model,the lesion was classified as a malignant tumor(the risk of malignancy was 27.1%,corresponding to Ovarian-Adnexal Reporting Data System category 4).Magnetic resonance imaging confirmed the presence of a right adnexal mass,apparently an ovarian tumor measuring 65 mm×35 mm,without signs of invasive or metastatic disease.During explorative laparotomy,normal morphology of the internal reproductive organs was noted.A solid mobile lesion involved the entire appendix.Appendectomy was performed.Inspection of the abdominal cavity revealed no signs of malignant dissemination.Histopathologically,the appendiceal lesion corresponded to a completely resected low-grade mucinous appendiceal neoplasm(LAMN).CONCLUSION The appropriate treatment and team of specialists who should provide health care to patients with seemingly adnexal lesions depend on the nature(benign vs malignant)and origin(gynecological vs nongynecological)of the lesion.Radiologists,gynecologists and other pelvic surgeons should be familiar with the imaging signs of LAMN whose clinical presentation is silent or nonspecific.The assistance of a consultant specializing in intestinal tumors is important support that gynecological surgeons can receive during the operation to offer the patient with intestinal pathology an optimal intervention.展开更多
BACKGROUND This study investigated the construction and clinical validation of a predictive model for neuroaggression in patients with gastric cancer.Gastric cancer is one of the most common malignant tumors in the wo...BACKGROUND This study investigated the construction and clinical validation of a predictive model for neuroaggression in patients with gastric cancer.Gastric cancer is one of the most common malignant tumors in the world,and neuroinvasion is the key factor affecting the prognosis of patients.However,there is a lack of systematic analysis on the construction and clinical application of its prediction model.This study adopted a single-center retrospective study method,collected a large amo-unt of clinical data,and applied statistics and machine learning technology to build and verify an effective prediction model for neuroaggression,with a view to providing scientific basis for clinical treatment decisions and improving the tr-eatment effect and survival rate of patients with gastric cancer.AIM To investigate the value of a model based on clinical data,spectral computed to-mography(CT)parameters and image omics characteristics for the preoperative prediction of nerve invasion in patients with gastric cancer.METHODS A retrospective analysis was performed on 80 gastric cancer patients who under-went preoperative energy spectrum CT at our hospital between January 2022 and August 2023,these patients were divided into a positive group and a negative group according to their pathological results.Clinicopathological data were collected,the energy spectrum parameters of primary gastric cancer lesions were measured,and single factor analysis was performed.A total of 214 image omics features were extracted from two-phase mixed energy images,and the features were screened by single factor analysis and a support vector machine.The variables with statist-ically significant differences were included in logistic regression analysis to construct a prediction model,and the performance of the model was evaluated using the subject working characteristic curve.There were statistically significant differences in sex,carbohydrate antigen 199 expression,tumor thickness,Lauren classification and Borrmann classification between the two groups(all P<0.05).Among the energy spectrum parameters,there were statistically significant differences in the single energy values(CT60-CT110 keV)at the arterial stage between the two groups(all P<0.05)and statistically significant differences in CT values,iodide group values,standardized iodide group values and single energy values except CT80 keV at the portal vein stage between the two groups(all P<0.05).The support vector machine model with the largest area under the curve was selected by image omics analysis,and its area under the curve,sensitivity,specificity,accuracy,P value and pa-rameters were 0.843,0.923,0.714,0.925,<0.001,and c:g 2.64:10.56,respectively.Finally,based on the logistic regression algorithm,a clinical model,an energy spectrum CT model,an imaging model,a clinical+energy spe-ctrum model,a clinical+imaging model,an energy spectrum+imaging model,and a clinical+energy spectrum+imaging model were established,among which the clinical+energy spectrum+imaging model had the best efficacy in diagnosing gastric cancer nerve invasion.The area under the curve,optimal threshold,Youden index,sensitivity and specificity were 0.927(95%CI:0.850-1.000),0.879,0.778,0.778,and 1.000,respectively.CONCLUSION The combined model based on clinical features,spectral CT parameters and imaging data has good value for the preoperative prediction of gastric cancer neuroinvasion.展开更多
文摘Five years have passed since the Japan Narrow Band Imaging Expert Team (JNET) classification was proposed in 2014. However, the diagnostic performance of this classification has not yet been established. We conducted a retrospective study and a systematic search of Medical Literature Analysis and Retrieval System On-Line. There were three retrospective single center studies about the diagnostic performance of this classification. In order to clarify this issue, we reviewed our study and three previous studies. This review revealed the diagnostic performance in regards to three important differentiations.(1) Neoplasia from non-neoplasia;(2) malignant neoplasia from benign neoplasia;and (3) deep submucosal invasive cancer (D-SMC) from other neoplasia. The sensitivity in differentiating neoplasia from non-neoplasia was 98.1%-99.8%. The specificity in differentiating malignant neoplasia from benign neoplasia was 84.7%-98.2% and the specificity in the differentiation D-SMC from other neoplasia was 99.8%-100.0%. This classification would enable endoscopists to identify almost all neoplasia, to appropriately determine whether to perform en bloc resection or not, and to avoid unnecessary surgery. This article is the first review about the diagnostic performance of the JNET classification. Previous reports about the diagnostic performance have all been retrospective single center studies. A large-scale prospective multicenter evaluation study is awaited for the validation.
基金Supported by Shanghai Leading Academic Discipline Project,No.S30203
文摘AIM:To retrospectively evaluate the imaging features of pancreatic intraductal papillary mucinous neoplasms (IPMNs) in multi-detector row computed tomography (MDCT).METHODS: A total of 20 patients with pathologically-confirmed intraductal papillary mucinous neoplasms (IPMNs) were included in this study. Axial MDCT images combined with CT angiography (CTA) and multiplanar volume reformations (MPVR) or curved reformations (CR) were preoperatively acquired. Two radiologists (Tan L and Wang DB) reviewed all the images in consensus using an interactive picture archiving and communication system. The disputes in readings were resolved through consultation with a third experienced radiologist (Chen KM). Finally, the findings and diagnoses were compared with the pathologic results.RESULTS: The pathological study revealed 12 malignant IPMNs and eight benign IPMNs. The diameters of the cystic lesions and main pancreatic ducts (MPDs) were significantly larger in malignant IPMNs compared with those of the benign IPMNs (P<0.05). The combined-type IPMNs had a higher rate of malignancy than the other two types of IPMNs (P<0.05). Tumors with mural nodules and thick septa had a significantly higher incidence of malignancy than tumors without these features (P<0.05). Communication of side-branch IPMNs with the MPD was present in nine cases at pathologic examination. Seven of them were identified from CTA and MPVR or CR images. From comparison with the pathological diagnosis, the sensitivity, specificity, and accuracy of MDCT in characterizing the malignancy of IPMN of the pancreas were determined to be 100%, 87.5% and 95%, respectively.CONCLUSION: MDCT with CTA and MPVR or CR techniques can elucidate the imaging features of IPMNs and help predict the malignancy of these tumors.
文摘AIM To establish the ability of magnetic resonance(MR) and computer tomography(CT) to predict pathologic dimensions of pancreatic neuroendocrine tumors(Pan NET) in a caseload of a tertiary referral center.METHODS Patients submitted to surgery for Pan NET at the Surgical Unit of the Pancreas Institute with at least 1 preoperative imaging examination(MR or CT scan) from January 2005 to December 2015 were included and data retrospectively collected. Exclusion criteria were: multifocal lesions, genetic syndromes, microadenomas or mixed tumors, metastatic disease and neoadjuvant therapy. Bland-Altman(BA) and Mountain-Plot(MP) statistics were used to compare size measured by each modality with the pathology size. Passing-Bablok(PB) regression analysis was used to check the agreement between MR and CT.RESULTS Our study population consisted of 292 patients. Seventy-nine(27.1%) were functioning Pan NET. The mean biases were 0.17 ± 7.99 mm, 1 ± 8.51 mm and 0.23 ± 9 mm, 1.2 ± 9.8 mm for MR and CT, considering the overall population and the subgroup of non-functioning-Pan NET, respectively. Limits of agreement(LOA) included the vast majority of observations, indicating a good agreement between imaging and pathology. The MP further confirmed this finding and showed that the two methods are unbiased with respect to each other. Considering ≤ 2 cm non-functioning-Pan NET, no statistical significance was found in the size estimation rate of MR and CT(P = 0.433). PBR analysis did not reveal significant differences between MR, CT and pathology.CONCLUSION MR and CT scan are accurate and interchangeable imaging techniques in predicting pathologic dimensions of Pan NET.
文摘BACKGROUND It is unclear whether the Japan Narrow-Band Imaging Expert Team(JNET)classification and pit pattern classification are applicable for diagnosing neoplastic lesions in patients with ulcerative colitis(UC).AIM To clarify the diagnostic performance of these classifications for neoplastic lesions in patients with UC.METHODS This study was conducted as a single-center,retrospective case-control study.Twenty-one lesions in 19 patients with UC-associated neoplasms(UCAN)and 23 lesions in 22 UC patients with sporadic neoplasms(SN),evaluated by magnifying image-enhanced endoscopy,were retrospectively and separately assessed by six endoscopists(three experts,three non-experts),using the JNET and pit pattern classifications.The results were compared with the pathological diagnoses to evaluate the diagnostic performance.Inter-and intra-observer agreements were calculated.RESULTS In this study,JNET type 2 A and pit pattern typeⅢ/Ⅳwere used as indicators of low-grade dysplasia,JNET type 2 B and pit pattern typeⅥlow irregularity were used as indicators of highgrade dysplasia to shallow submucosal invasive carcinoma,JNET type 3 and pit pattern typeⅥhigh irregularity/VN were used as indicators of deep submucosal invasive carcinoma.In the UCAN group,JNET type 2 A and pit pattern typeⅢ/Ⅳhad a low positive predictive value(PPV;50.0%and 40.0%,respectively);however,they had a high negative predictive value(NPV;94.7%and 100%,respectively).Conversely,in the SN group,JNET type 2 A and pit pattern typeⅢ/Ⅳhad a high PPV(100%for both)but a low NPV(63.6%and 77.8%,respectively).In both groups,JNET type 3 and pit pattern typeⅥ-high irregularity/VN showed high specificity.The interobserver agreement of JNET classification and pit pattern classification for UCAN among experts were 0.401 and 0.364,in the same manner for SN,0.666 and 0.597,respectively.The intra-observer agreements of JNET classification and pit pattern classification for UCAN among experts were 0.387,0.454,for SN,0.803 and 0.567,respectively.CONCLUSION The accuracy of endoscopic diagnosis using both classifications was lower for UCAN than for SN.Endoscopic diagnosis of UCAN tended to be underestimated compared with the pathological results.
文摘BACKGROUND Challenging lesions,difficult to diagnose through non-invasive methods,constitute an important emotional burden for each patient regarding a still uncertain diagnosis(malignant x benign).In addition,from a therapeutic and prognostic point of view,delay in a definitive diagnosis can lead to worse outcomes.One of the main innovative trends currently is the use of molecular and functional methods to diagnosis.Numerous liver-specific contrast agents havebeen developed and studied in recent years to improve the performance of liver magnetic resonance imaging(MRI).More recently,one of the contrast agents introduced in clinical practice is gadoxetic acid(gadoxetate disodium).AIM To demonstrate the value of the hepatobiliary phases using gadoxetic acid in MRI for the characterization of focal liver lesions(FLL)in clinical practice.METHODS Overall,302 Lesions were studied in 136 patients who underwent MRI exams using gadoxetic acid for the assessment of FLL.Two radiologists independently reviewed the MRI exams using four stages,and categorized them on a 6-point scale,from 0(lesion not detected)to 5(definitely malignant).The stages were:stage 1-images without contrast,stage 2-addition of dynamic phases after contrast(analogous to usual extracellular contrasts),stage 3-addition of hepatobiliary phase after 10 min(HBP 10’),stage 4-hepatobiliary phase after 20 min(HBP 20’)in addition to stage 2.RESULTS The interobserver agreement was high(weighted Kappa coefficient:0.81-1)at all stages in the characterization of benign and malignant FLL.The diagnostic weighted accuracy(Az)was 0.80 in stage 1 and was increased to 0.90 in stage 2.Addition of the hepatobiliary phase increased Az to 0.98 in stage 3,which was also 0.98 in stage 4.CONCLUSION The hepatobiliary sequences improve diagnostic accuracy.With growing potential in the era of precision medicine,the improvement and dissemination of the method among medical specialties can bring benefits in the management of patients with FLL that are difficult to diagnose.
文摘BACKGROUND Appendiceal tumors are rare lesions that may not be easily differentiated from primary ovarian lesions preoperatively,despite the use of advanced diagnostic methods by experienced clinicians.CASE SUMMARY A 59-year-old G2P2 woman,with chronic pelvic pain,underwent a pelvic ultrasound that revealed an adnexal mass measuring 58 mm×34 mm×36 mm,with irregular borders,heterogeneous echogenicity,no color Doppler vascularization and without acoustic shadowing.Normal ovarian tissue was visualized in contact with the lesion,and it was impossible to separate the lesion from the ovary by applying pressure with the ultrasound probe.Ascites,peritoneal metastases or other alterations were not observed.With the international ovarian tumor analysis ADNEX model,the lesion was classified as a malignant tumor(the risk of malignancy was 27.1%,corresponding to Ovarian-Adnexal Reporting Data System category 4).Magnetic resonance imaging confirmed the presence of a right adnexal mass,apparently an ovarian tumor measuring 65 mm×35 mm,without signs of invasive or metastatic disease.During explorative laparotomy,normal morphology of the internal reproductive organs was noted.A solid mobile lesion involved the entire appendix.Appendectomy was performed.Inspection of the abdominal cavity revealed no signs of malignant dissemination.Histopathologically,the appendiceal lesion corresponded to a completely resected low-grade mucinous appendiceal neoplasm(LAMN).CONCLUSION The appropriate treatment and team of specialists who should provide health care to patients with seemingly adnexal lesions depend on the nature(benign vs malignant)and origin(gynecological vs nongynecological)of the lesion.Radiologists,gynecologists and other pelvic surgeons should be familiar with the imaging signs of LAMN whose clinical presentation is silent or nonspecific.The assistance of a consultant specializing in intestinal tumors is important support that gynecological surgeons can receive during the operation to offer the patient with intestinal pathology an optimal intervention.
文摘BACKGROUND This study investigated the construction and clinical validation of a predictive model for neuroaggression in patients with gastric cancer.Gastric cancer is one of the most common malignant tumors in the world,and neuroinvasion is the key factor affecting the prognosis of patients.However,there is a lack of systematic analysis on the construction and clinical application of its prediction model.This study adopted a single-center retrospective study method,collected a large amo-unt of clinical data,and applied statistics and machine learning technology to build and verify an effective prediction model for neuroaggression,with a view to providing scientific basis for clinical treatment decisions and improving the tr-eatment effect and survival rate of patients with gastric cancer.AIM To investigate the value of a model based on clinical data,spectral computed to-mography(CT)parameters and image omics characteristics for the preoperative prediction of nerve invasion in patients with gastric cancer.METHODS A retrospective analysis was performed on 80 gastric cancer patients who under-went preoperative energy spectrum CT at our hospital between January 2022 and August 2023,these patients were divided into a positive group and a negative group according to their pathological results.Clinicopathological data were collected,the energy spectrum parameters of primary gastric cancer lesions were measured,and single factor analysis was performed.A total of 214 image omics features were extracted from two-phase mixed energy images,and the features were screened by single factor analysis and a support vector machine.The variables with statist-ically significant differences were included in logistic regression analysis to construct a prediction model,and the performance of the model was evaluated using the subject working characteristic curve.There were statistically significant differences in sex,carbohydrate antigen 199 expression,tumor thickness,Lauren classification and Borrmann classification between the two groups(all P<0.05).Among the energy spectrum parameters,there were statistically significant differences in the single energy values(CT60-CT110 keV)at the arterial stage between the two groups(all P<0.05)and statistically significant differences in CT values,iodide group values,standardized iodide group values and single energy values except CT80 keV at the portal vein stage between the two groups(all P<0.05).The support vector machine model with the largest area under the curve was selected by image omics analysis,and its area under the curve,sensitivity,specificity,accuracy,P value and pa-rameters were 0.843,0.923,0.714,0.925,<0.001,and c:g 2.64:10.56,respectively.Finally,based on the logistic regression algorithm,a clinical model,an energy spectrum CT model,an imaging model,a clinical+energy spe-ctrum model,a clinical+imaging model,an energy spectrum+imaging model,and a clinical+energy spectrum+imaging model were established,among which the clinical+energy spectrum+imaging model had the best efficacy in diagnosing gastric cancer nerve invasion.The area under the curve,optimal threshold,Youden index,sensitivity and specificity were 0.927(95%CI:0.850-1.000),0.879,0.778,0.778,and 1.000,respectively.CONCLUSION The combined model based on clinical features,spectral CT parameters and imaging data has good value for the preoperative prediction of gastric cancer neuroinvasion.
