Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective To develop and validate a deep learning model for automatic identification of liver CT contrast-enhanced phases.Methods A total of 766 patients with liver CT contrast-enhanced images were retrospectively collected.A three-phase classification model and an arterial phase(AP)classification model were developed,so as to automatically identify liver CT contrast-enhanced phases as early arterial phase(EAP)or late arterial phase(LAP),portal venous phase(PVP),and equilibrium phase(EP).In addition,221 patients with liver CT contrast-enhanced images in 5 different hospitals were used for external validation.The annotation results of radiologists were used as a reference standard to evaluate the model performances.Results In the external validation datasets,the accuracy in identifying each enhanced phase reached to 90.50%-99.70%.Conclusion The automatic identification model of liver CT contrast-enhanced phases based on residual network may provide an efficient,objective,and unified image quality control tool.

Objective:To investigate the application value of magnetic resonance imaging(MRI) in evaluating the efficacy of anti-PD-1 combined with neoadjuvant therapy for microsatellite stability (MSS)/proficient mismatch repair (pMMR) locally advanced rectal cancer (LARC).Methods:The prospective single-arm phase Ⅱ study was conducted. The clinicopathological data of 37 patients with MSS/pMMR LARC who were admitted to Beijing Friendship Hospital of Capital Medical University from April 2021 to September 2022 were collected. All patients underwent anti-PD-1 combined with neoadjuvant therapy and radical total mesorectal excision. Observation indicators: (1) enrolled pati-ents; (2) MRI and pathological examination; (3) concordance analysis of MRI examination reading; (4) evaluation of MRI examination. Measurement data with normal distribution were represented as Mean± SD. Count data were expressed as absolute numbers or percentages. Linear weighted κ value was used to evaluate the concordance of radiologist assessment. Sensitivity, negative predictive value, accuracy, overstaging rate and understaging rate were used to evaluate the predictive value. Results:(1) Enrolled patients. A total of 37 eligible patients were screened out, including 21 males and 16 females, aged (61±11)years. MRI examination was performed before and after combined therapy, and pathological examination was performed after radical resection. (2) MRI and pathological examination of patients. Among the 37 patients, MRI before combined therapy showed 0, 0, 5, 24 and 8 cases in stage T0, T1, T2, T3 and T4, 10, 17 and 10 cases in stage N0, N1 and N2, 28 and 9 cases of positive and negative extramural vascular invasion (EMVI), 4 and 33 cases of positive and negative mesorectal fascia (MRF), respectively. MRI examination after combined therapy showed 15, 4, 7, 10 and 1 cases in stage T0, T1, T2, T3 and T4, 34, 2 and 1 cases in stage N0, N1 and N2, 9 and 28 cases of positive and negative EMVI, 1 and 36 cases of positive and negative MRF. There were 16, 13, 8 and 0 cases of tumor regression grading (TRG) 0, 1, 2 and 3, respectively. Postoperative pathological examination showed 18, 4, 3, 11, 1 cases in stage T0, T1, T2, T3, T4, 33, 3, 1 cases in stage N0, N1, N2, positive and negative EMVI and unknown data in 1, 35, 1 cases, positive and negative circumferential margin in 0 and 37 cases, grade 0, grade 1, grade 2, grade 3 of American Joint Committee on Cancer TRG in 18, 9, 8, 2 cases, respectively. Pathological complete response rate was 48.6%(18/37) and approximate pathological complete response rate was 24.3%(9/37). (3)Concordance analysis of MRI examination reading. The κ value of T staging and N staging on MRI before combined therapy was 0.839 ( P<0.05) and 0.838 ( P<0.05), respectively. The κ value of T staging and N staging on MRI after combined therapy was 0.531 ( P<0.05) and 0.846 ( P<0.05), respectively. The κ value of EMVI and MRF was 0.708 ( P<0.05) and 0.680 ( P<0.05) before combined therapy, and they were 0.561 ( P<0.05) and 1.000 ( P<0.05) after combined therapy, respectively. The κ value of TRG 3-round reading for TRG was 0.448 ( P<0.05). (4) Evaluation of MRI examination. ① MRI evaluation of T and N staging. The accuracy of MRI examination after combined therapy for distinguishing stage T0 was 75.7%[28/37, 95% confidence interval ( CI) as 62.2%-89.2%], the understaging rate was 8.1%(3/37, 95% CI as 0-18.9%), the overstaging rate was 16.2%(6/37, 95% CI as 5.4%-29.7%). The accuracy of MRI examination for distinguishing stage T0-T2 was 86.5%(32/37, 95% CI as 73.0%-97.3%), its understaging rate and overstaging rate were 8.1%(3/37, 95% CI as 0-18.9%) and 5.4% (2/37, 95% CI as 0-13.5%), respectively. The accuracy of MRI examination for distinguishing N staging was 91.9%(34/37, 95% CI was 81.1%-100.0%), its understaging rate and overstaging rate were 5.4%(2/37, 95% CI as 0-13.5%) and 2.7%(1/37, 95% CI as 0-8.1%), respectively. Among 18 patients in pathological stage T0, the overstaging rate of MRI was 33.3%(6/18). All the 4 patients in pathological stage T1 and 3 pati-ents in pathological stage T2 had correct diagnosis. There were 3 cases with understaging among 12 patients in pathological stage T3-T4. Among the 37 patients in pathological stage N0-N2, 34 cases had correct diagnosis, 1 case was overstaged as stage N1 due to a round mesorectal lymph node with short diameter as 6 mm, and 2 cases were diagnosed as stage N0 due to the small lymph nodes with the maximum short diameter as 3 mm. ② MRI evaluation of EMVI and MRF. The accuracy, sensitivity and negative predictive value of MRI for evaluating EMVI were 86.5%(32/37, 95% CI as 75.0%-97.2%), 100.0% and 100.0%, respectively, and the overestimation rate of EMVI was 13.9%(5/36, 95% CI as 2.8%-25.0%), and no underestimation occurred. Of 35 pathologically negative EMVI patients, a rate of 14.3%(5/35) of patients were positive on MRI. The main reason for overestaging was that thickened fibrous tissue outside the rectal wall was mistaken for vascular invasion. The accuracy of MRI for evaluating MRF was 97.3%(36/37, 95% CI as 91.9%-100.0%), and 1 case (1/37, 2.7%, 95% CI as 0-8.1%) was overestimated as positive MRF due to misdiagnosis of pararectal MRF lymph nodes. The negative predictive value of MRI for assessing MRF was 100.0%. ③ MRI evaluation of TRG. The accuracy, understaging and overstaging rates of MRI for evaluating pathological TRG 0 were 78.4%(29/37, 95% CI as 64.9%-91.9%), 8.1%(3/37, 95% CI as 0-18.9%), 13.5%(5/37, 95% CI as 5.4%-27.0%), respectively. The accuracy, understaging and overstaging rates of MRI for evaluating pathological TRG 0-1 were 89.2%(33/37, 95% CI as 78.4%-97.3%), 8.1%(3/37, 95% CI as 0-18.9%), 2.7%(1/37, 95% CI as 0-8.1%), respectively. Of the 18 patients with pathologic complete response, 5 cases were diagnosed as pathological TRG 1 and 13 cases as pathological TRG 0. One near-pCR patient was assessed as pathological TRG 2. Two patients with pathological TRG 3 were incorrectly diagnosed on MRI. Conclusions:Anti-PD-1 combined with neoadjuvant therapy can downstage the LARC pati-ents with MSS/pMMR. MRI is effective in predicting T staging, N staging, EMVI, MRF and TRG. However, overstaging should be prevented.

Intervertebral disc degeneration is one of the common causes of chronic low back pain. As a common spinal disease， its clinical symptoms are mainly low back pain and limited function， which seriously affects physical and psychological health. Because of its complex and unclear pathogenesis， the treatment of intervertebral disc degeneration has been the focus of scientific researchers and clinical workers. At present， the treatment of intervertebral disc degeneration mainly includes non-surgical therapy and surgical therapy， which can alleviate the clinical symptoms of patients to a certain extent， but easily induce new complications， and it is difficult to restore the normal physiological function of the intervertebral disc. In recent years， along with the advanced research on matrix metalloproteinases （MMPs） in the tissues of intervertebral disc degeneration， it has been found that MMPs can be used as molecular therapeutic targets. The expression of MMPs in the intervertebral disc tissues can be regulated by reducing the content and composition of the extracellular matrix of the intervertebral disc， so as to slow down intervertebral disc degeneration and even reverse the occurrence of intervertebral disc degeneration. This treatment is expected to delay intervertebral disc degeneration caused by changes in extracellular matrix composition or content. In recent years， with the continuous development of network pharmacology and bioinformatics research， a large number of researchers have explored the treatment of intervertebral disc degeneration by traditional Chinese medicine （TCM） and found that TCM can reduce the degradation of extracellular matrix by inhibiting the expression of MMPs， thus alleviating the symptoms of intervertebral disc degeneration and slowing down the progression of intervertebral disc degeneration. This paper reviewed the research progress of TCM intervention in MMP expression in the treatment of intervertebral disc degeneration， aiming at providing references for the application of TCM in the prevention and treatment of intervertebral disc degeneration.

Humans ; Computed Tomography Angiography ; Deep Learning ; Coronary Angiography ; Coronary Artery Disease ; Tomography, X-Ray Computed ; Coronary Stenosis/diagnosis* ; Retrospective Studies ; Fractional Flow Reserve, Myocardial ; Predictive Value of Tests

Abdomen/diagnostic imaging* ; Artificial Intelligence ; Body Composition ; Magnetic Resonance Imaging ; Practice Guidelines as Topic