Application of CT pulmonary function imaging in convalescent COVID-19 patients / 中华放射学杂志

Objective:To explore the application value of CT pulmonary function imaging in patients with Coronavirus Disease 2019 (COVID-19) in the convalescent phase.Methods:The COVID-19 patients who were clinically cured and discharged from Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were prospectively collected from January to April 2020. Clinical pulmonary function tests (PFTs) and CT pulmonary function imaging were performed 3 months after discharge. The Philips IntelliSpace Portal image post-processing workstation was used to obtain the paired inspiratory-expiratory CT quantitative indexes of the whole lung, left lung, right lung and five lobes. The patients were divided into two groups according to whether residual lesions remain in inspiratory CT images: non-residual lesion group and residual lesion group. The chi-square test was used to compare the differences in the PFT results between groups; the Mann-Whitney U test was used to compare the differences in PFT indexes [forced expiratory volume in the first second as percentage of predicted value (FEV 1%), FEV 1/forced vital capacity (FEV 1/FVC), total lung capacity as percentage of predicted value (TLC%), FVC%] and the differences in quantitative CT indexes [lung volume (LV), mean lung density (MLD), volume change in inspiratory phase and expiratory phase (?LV)] between groups. Multiple linear regression was used to analyze the relationship between CT pulmonary function imaging and PFT indexes of convalescent COVID-19 patients. Results:Of the 90 patients with COVID-19, 35 were males and 55 were females; 45 were included in the non-residual lesion group and 45 were included in the residual lesion group. Fifty-three patients had clinical pulmonary dysfunction 3 months after discharge, including 22 patients in the non-residual lesion group and 31 patients in the residual lesion group. In patients with residual disease, left lower lobe and right lower lobe LV, left lower lobe and right lower lobe ?LV in the inspiratory and expiratory phase were smaller than those without residual disease; whole lung, left lung, right lung, left upper lobe, left lower lobe and right lower lobe MLD in the inspiratory phase and left lower lobe and right lower lobe MLD in the expiratory phase were greater than those without residual disease ( P<0.05). Since there was no significant difference in FEV 1/FVC and FVC% between residual and non-residual lesion groups ( P>0.05), FEV 1/FVC and FVC% of two groups were combined. Multiple linear regression analysis showed FEV 1/FVC=91.765-0.016×LV in-right middle lobe+0.014×MLD ex-left lower lobe ( R2=0.200, P<0.001), FVC%=-184.122-0.358×MLD in-right lung-0.024×?LV left upper lobe ( R2=0.261, P<0.001). There was significant difference in TLC% between residual and non-residual lesion groups ( P<0.05), so multiple linear regression analysis was performed both in the two groups. In the non-residual lesion group, TLC%=80.645+0.031×LV ex-right lower lobe ( R2=0.132, P<0.001); In the residual lesion group, TLC%=-110.237-0.163×MLD in-right upper lobe-0.098×MLD ex-left upper lobe -0.025×LV ex-right lower lobe ( R2=0.473, P<0.001). Conclusion:CT pulmonary function imaging can quantitatively analyze the whole lung, unilateral lung and lobulated lung, thus reflecting the regional pulmonary function, providing more valuable diagnostic information for the assessment of pulmonary function in convalescent patients with COVID-19.

Preliminary study on the optimal keV of virtual monoenergetic images in transplanted renal artery on a dual-layer spectral detector CT / 中华放射学杂志

Objective:To investigate the optimal monoenergetic level of virtual monoenergetic images (VMI) in transplanted renal artery on a dual-layer spectral detector CT.Methods:A retrospective study was performed on 16 renal transplant patients who underwent transplanted renal angiography on a dual-layer spectral detector CT in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from June 2020 to April 2021. Conventional 120 kVp polyenergetic images (PI) were reconstructed, and virtual monoenergetic images (VMIs) in range of 40-200 keV with interval of 10 keV were reconstructed, too. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 120 kVp PI and VMIs were measured. Meanwhile, the subjective scores of the display of transplanted renal artery were performed on volume rendering images of 120 kVp PI and VMIs. Spearman correlation analysis was used to explore the correlation between energy levels and SNR or CNR. Rank sum tests were performed to compare the parameters of image quality between the VMI which had the highest SNR and CNR, and the other VMIs, or 120 kVp PI.Results:Among the VMIs, SNR or CNR was negatively correlated with energy levels ( r =-0.86 and -0.88, all P<0.001). The SNR [22.80(18.57, 34.16)] and CNR [35.38(25.97, 39.01)] of 40 keV VMI were the highest, and significantly higher than that of 120 kVp PI and 50-200 keV VMIs, all the differences were statistically significant (all P<0.05). The subjective scores of 40 keV VMI and 120 kVp PI were 5 (5, 5) and 4 (3, 5), respectively. The score of 40 keV VMI was significantly higher than that of 120 kVp PI ( Z=-2.60, P=0.009). There were no significant differences in subjective scores between 40 keV VMI and 50-70 keV VMIs ( Z=-1.00, -1.41, -1.73, P=0.317, 0.157, 0.083), but the subjective score of 40 keV VMI was higher than that of 80-200 keV VMIs and the differences were statistically significant (all P<0.05). Conclusions:As for the images of transplanted renal angiography on a dual-layer spectral detector CT, the image quality of 40 keV VMI was best, thus 40 keV was the optimal monoenergetic level.

Feasibility of constructing a unilateral sudden sensorineural hearing loss machine learning classification model based on diffusion tensor imaging / 中华放射学杂志

Objective@#To explore the feasibility of constructing a machine learning classification model for unilateral sudden sensorineural hearing loss (SSHL) patients and normal controls based on diffusion tensor imaging.@*Methods@#Prospective collection of 84 patients with untreated SSHL were recruited from the otolaryngology department of the Union Hospital of Tongji Medical College of Huazhong University of Science and Technology between June 2013 to May 2015 as the SSHL group. Meanwhile, a total of 63 healthy volunteers who were no any ear disease history, and the hearing function were confirmed with pure tone audiometry, were collected as the control group. All subjects underwent a brain DTI scan. The data were divided into the training set and validation set according to the ratio of 7 to 3, that was, the training set contained 58 cases of SSHL patients and 44 control groups, and the validation set included 26 cases of SSHL patients and 19 control groups. A vector which included the DTI parameters such as fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity was constructed with the software R. The LASSO regression of machine learning method was used to perform feature dimensionality reduction and construct a classification model. The training set samples were used to map the nomogram based on the multivariate logistic analysis method, the validation set and the AUC were used to evaluate the prediction ability of the nomogram, and the calibration curve was used to evaluate the model.@*Results@#From the 200 feature vectors including the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values of each brain region, after each dimension reduction process, a total of six features were retained, which were the MD of left superior corona radiate and right superior fronto-occipital fasciculus, the AD of the body of corpus callosum, and the RD of left inferior cerebellar peduncle, left superior corona radiate and right posterior limb of internal capsule. The six features of patients with unilateral SSHL were higher than the control group, and the difference was statistically significant (P<0.05). Based on this, a two-class model is constructed and a nomogram is drawn. The sensitivity, specificity, accuracy and AUC of the training set were 93.1% (54/58), 72.7% (32/44), 84.3% (86/102) and 0.854, respectively; the sensitivity, specificity, accuracy and AUC of validation set were 80.8% (21/26), 84.2% (16/19), 82.2% (37/45), 0.870, respectively. Nomogram could significantly improve the classification efficiency of the control group and patients, and the model with the LASSO method showed a higher prediction curve than other models.@*Conclusions@#The machine learning classification model based on DTI metrics can effectively distinguish patients with unilateral sudden sensorineural deafness from healthy control people.

Feasibility of constructing a unilateral sudden sensorineural hearing loss machine learning classification model based on diffusion tensor imaging / 中华放射学杂志

Objective To explore the feasibility of constructing a machine learning classification model for unilateral sudden sensorineural hearing loss (SSHL) patients and normal controls based on diffusion tensor imaging. Methods Prospective collection of 84 patients with untreated SSHL were recruited from the otolaryngology department of the Union Hospital of Tongji Medical College of Huazhong University of Science and Technology between June 2013 to May 2015 as the SSHL group. Meanwhile, a total of 63 healthy volunteers who were no any ear disease history, and the hearing function were confirmed with pure tone audiometry, were collected as the control group. All subjects underwent a brain DTI scan. The data were divided into the training set and validation set according to the ratio of 7 to 3, that was, the training set contained 58 cases of SSHL patients and 44 control groups, and the validation set included 26 cases of SSHL patients and 19 control groups. A vector which included the DTI parameters such as fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity was constructed with the software R. The LASSO regression of machine learning method was used to perform feature dimensionality reduction and construct a classification model. The training set samples were used to map the nomogram based on the multivariate logistic analysis method, the validation set and the AUC were used to evaluate the prediction ability of the nomogram, and the calibration curve was used to evaluate the model. Results From the 200 feature vectors including the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values of each brain region, after each dimension reduction process, a total of six features were retained, which were the MD of left superior corona radiate and right superior fronto-occipital fasciculus, the AD of the body of corpus callosum, and the RD of left inferior cerebellar peduncle, left superior corona radiate and right posterior limb of internal capsule. The six features of patients with unilateral SSHL were higher than the control group, and the difference was statistically significant (P<0.05). Based on this, a two-class model is constructed and a nomogram is drawn. The sensitivity, specificity, accuracy and AUC of the training set were 93.1% (54/58), 72.7% (32/44), 84.3% (86/102) and 0.854, respectively; the sensitivity, specificity, accuracy and AUC of validation set were 80.8% (21/26), 84.2% (16/19), 82.2% (37/45), 0.870, respectively. Nomogram could significantly improve the classification efficiency of the control group and patients, and the model with the LASSO method showed a higher prediction curve than other models. Conclusions The machine learning classification model based on DTI metrics can effectively distinguish patients with unilateral sudden sensorineural deafness from healthy control people.

Nonenhanced electrocardiogram?gated quiescent?interval single?shot MR angiography of the lower extremities:comparison with CT angiography / 中华放射学杂志

Objective To evaluate the diagnose value of nonenhanced electrocardiogram (ECG)?gated quiescent?interval single?shot MR angiography (QISS MRA) in lower extremity arterial stenosis. Methods A retrospective analysis of 30 patients with lower extremity ischemic manifestations and concurrent lower extremity arterial CTA and QISS MRA was performed from April to December 2017 at the Union Hospital of Tongji Medical College, Huazhong University of Science and Technology. All patients underwent CTA and ECG?gated non?contrast?enhanced QISS MRA. The entire lower extremity arteries were divided into 19 segments (lower abdominal aorta, common iliac artery, internal iliac artery, external iliac artery, superficial femoral artery, deep femoral artery, radial artery, anterior tibialis anterior tibial artery, posterior tibial artery, radial artery). Two radiologists scored QISS MRA and CTA image quality using a 4?point scale and assessed the severity of arterial stenosis. Kappa analysis was used to evaluate the degree of stenosis of different examination methods in the same patient and the consistency of the scores of different radiologsts in the same patient. Result A total of 570 vessel segments were collected from 30 patients. The image quality of 560/570 (98.2%) and 548/570 (96.1%) of radiologist 1 was rated as excellent or good by CTA and QISS?MRA (grades 3 and 4), and 561/570 (98.4% of radiologist 2) The image quality of the segment and the 544/570 (95.4%) segment were rated as excellent or good by CTA and QISS?MRA, respectively. The image quality scores of radiologist 1 to CTA and QISS MRA were (3.87±0.38) and (3.70± 0.53), respectively, and radiologist 2 were (3.86±0.40) and (3.68±0.54) respectively. On the QISS?MRA, only 7 of the 570 segments (1.2%, 7/570) obtained images that could not satisfy the diagnostic image quality. The two radiologists used CTA and QISS MRA to evaluate the consistency of different degrees of vascular stenosis. The radiologist 1 evaluated the Kappa value of CTA and QISS MRA between 0.714 and 0.939 for different degrees of vascular stenosis. Radiologist 2 had a Kappa value of 0.603 to 0.939. QISS MRA was used to evaluate the consistency of vascular stenosis in different segments between the two radiologists. The Kappa value ranged from 0.813 to 0.933. Conclusion QISS?MRA is of great value in the diagnosis of lower extremity arterial stenosis.

Size-specific dose estimation for chest CT examination in pediatric and adult patients / 中华放射医学与防护杂志

Objective To compare the differences in radiation doses from CT scanning between children of different age groups and adult patients by using both traditional radiation dose assessment parameters and size-specific dose estimates (SSDE).Methods A total of 406 patients undergoing lung CT examination were studied.They were sampled retrospectively and continuously from the Union Hospital and divided into six groups by age distritution (0-2,3-6,7-10,11-14,15-18,＞18 years old).The CTDIvol and DLP values were randomly sampled using MATLAB platform-based dicom data software.The SSDE and water equivalent diameter were also calculated according to the AAPM 220 Report.The differences in radiation doses from lung CT scaning between children and adult patients were analysed.Results The CTDIvol values for all age groups were significantly lower than the SSDE values.The differences were statistically significant (t =-36.36,-32.83,-30.36,-28.74,-23.89,P＜0.05).The SSDE values were 137％,94％,79％,57％ and 42％ higher than the CTDIvol values,respectively.The CTDIvol values for the adult group were also lower than the SSDE values,and the difference was statistically significant (t=-21.92,P＜0.05),and the SSDE value was about 41％ higher than the CTDIvol value.With the increased age,CTDIvol value,DLP value,Dw value and SSDE value for children of all age groups gradually increased and were significantly smaller than those for the adult group.The difference was statistically significant (F=63.39,203.28,89.27,103.44,P＜0.05).The conversion coefficient f for all age groups decreased significantly with age,which was significantly higher than that for the adult group,and the difference was statistically significant (F =109.83,P ＜ 0.05).Conclusions In lung CT scanning,the CTDIvol value significantly underestimated the radiation doses to children as compared to adults.CTDIvol values are more easily underestimated for younger patients.The SSDE method allows for more accurate reflection of the radiation doses to different patients,taking into account differences in the examined patient size.

Feasibility study of automatic spectral imaging protocol selection combined with double low technique in CT portal vein imaging / 中华放射医学与防护杂志

Objective To explore the application value of virtual monochromatic imaging combined with adaptive statistical iterative reconstruction (ASIR) and automatic spectral imageing mode selection(ASIS) in reducing the radiation dose and contrast dose of CT portal venography.Methods We retrospectively collected 120 cases (80 males and 40 females) who underwent upper abdominal enhancement CT from January 2017 to April 2017.Patients were divided into 3 groups (40 cases in each group) according to the scanning program.Group A used conventional 120 kVp scan,NI =10,contrast agent dosage was 450 mgI/kg of body weight,image was reconstructed with 50％ ASIR technique;Groups B and C used spectral CT mode,NI =10 (Group B),NI =13 (Group C),the amount of contrast agent was 300 mgI/kg of body weight,and the image was reconstructed with 60 keV +50％ ASIR.One-way analysis of variance was used to compare the mean CT values and their differences,image noise,SNR and CNR of portal vein and liver parenchyma in three groups of images.Subjective image quality scores were performed on three groups of images by two senior radiologists.The patient's CTDIvol,DLP were recorded and the E was calculated.Results The amount of contrast agent in group B and C was reduced by about 30％ compared with group A.The portal vein CT values of groups A,B,and C were 168.22± 17.82,209.06±20.07,and 211.03±25.60.The portal vein CT values of group B and C were significantly higher than those of group A,respectively (t =-9.625,-8.680,P ＜ 0.05).The CT value difference between portal vein and liver parenchyma was 60.01± 17.01,106.63±25.83,107.72±25.39,respectively.SNRs were 8.48±1.41,12.64±2.94,10.77±1.94,and CNR were 5.16±1.80,8.13±2.54,7.32±1.84,respectively.The image quality scores were 3.53±0.68,4.75±0.54 and 4.53±0.64,respectively.The CT value difference,SNR,CNR and image quality scores of group B and group C were significantly higher than those in group A(t=-9.536,-9.857,-8.082,-6.064,-6.050,-5.308,-8.912,-6.779,P＜0.05).The CTDIvolof groups A,B and C were (12.15±5.02) mGy,(12.34±4.18) mGy,(10.03±3.13) mGy,DLP were (348.62± 155.99) mGy· cm,(355.56± 131.07) mGy·cm,(287.10±92.25) mGy·cm,respectively,E were (5.23±2.34) mSv,(5.33±1.97) mSv,(4.31±.1.38) mSv,compared with the A and B groups,the CTDI,ol,DLP and E of the C group were significantly lower(t=2.274,2.147,2.147,2.812,2.702,2.702,P＜0.05),and CTDIvol,DLP and E were decreased by 19％.Conclusions In CT portal venography,NI =13,60 keV combined with 50％ ASIR reconstruction and ASIS can be used to personalize the contrast dose and radiation dose of the patient and provide images that meet the diagnostic requirements.