Article of the Year 2021
Preclinical Molecular PET-CT Imaging Targeting CDCP1 in Colorectal CancerRead the full article
Contrast Media & Molecular Imaging is an exciting journal in the area of contrast agents and molecular imaging, covering all areas of imaging technologies with a special emphasis on MRI and PET.
Chief Editor, Professor Zimmer, focuses on the development and use of PET radiotracers for new applications of PET/MRI imaging in neuroscience and pharmacology.
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Image Analysis of TVCDS in Infertile Patients with Polycystic Ovary Syndrome
In order to analyze and examine the TVCDS images of infertile patients, this paper conducted an in-depth study based on the symptoms of polycystic ovary syndrome. Through the sample size estimation method, mathematical analysis, and other methods, the image examination of the polycystic ovary in TVCDS was successfully analyzed. 86 cases of infertile patients with PCS were divided into a control group treated with clomiphene alone and an observation group treated with clomiphene combined with TCM periodic therapy, with 43 patients in each group. The therapeutic effects of the two groups were compared and analyzed. Results show that the treatment effective rate and pregnancy success rate of the observation group were 95.35% and 88.37%, respectively, and those of the control group were 83.72% and 76.74%, respectively. The difference between the two groups was statistically significant . It was understood that the main pathogenesis of polycystic ovary syndrome is the abnormal balance of kidney, qi, and blood meridians. Thus, the balance of kidney-anemone-chong Ren-uprisal is broken and the result is infertility symptoms or irregular menstruation. After a study on TVCDS in infertile patients, it was observed that the levels of progesterone (P) and luteinizing hormone (LH) in patients with irregular menstruation were significantly increased. The increase was higher than that in the control group, with an overall negative rate of 4.00%, compared with 18.00% of the control group, showing a significant difference. It also indicates that TVCDS image examination has a very significant effect on improving menstrual irregularities and reducing the incidence of adverse reactions.
Manifestation of Urinary Tract Injury during Cervical Cancer Surgery Based on CT Urography Secretion Phase Images
Object. CT imaging can be processed by computer, and the absorption coefficient of each voxel to X-ray can be obtained by calculation, which can effectively improve the efficiency of surgery. Traditional treatment is based on the patient’s age, fertility requirements, and general conditions, often using a comprehensive treatment plan with surgery and radiotherapy as the mainstay, supplemented by chemotherapy, which has great limitations and side effects, in order to alleviate the loss of various body functions, especially the urinary tract during cervical cancer surgery. Methods. We grouped the patients who had undergone cervical cancer surgery in a hospital in this article and compared the nanodrug carrier system under CT imaging with traditional laparoscopy. The postoperative physical parameters of surgical patients are collected from cervical cancer patients of different degrees, and the parameters and prognostic health of patients after different operations are compared. Results. The results of the study show that the postoperative patient’s body parameters of the nanodrug delivery system under the CT imaging technology used in this article are better than those of the traditional surgery group, and the average intraoperative blood loss is about 20% less than that of the traditional surgery. Postoperative complications occur. The situation is even lower, more than 30% lower than traditional surgery. Conclusion. This shows that the operation of the nanodrug delivery system based on CT imaging technology has broken through some of the limitations of the development of laparoscopic technology and has played an important role in the surgical treatment of cervical cancer.
Surgical Strategy and Prognosis of Pancreatic Neuroendocrine Tumors Based on Smart Medical Imaging
It is imperative to seize the “golden rescue time” and implement new concepts and new skills in modern trauma rescue. Combining with the development background of smart medical image analysis, this topic focuses on surgical strategies and prognostic measures and studies a serious and difficult disease frequently occurring in middle-aged and elderly people: pancreatic neuroendocrine tumors. This article uses the comparative test method and sample collection method to collect the medical records of patients with neuroendocrine tumors diagnosed by pathology from July 2010 to January 2018 in the First Affiliated Hospital of X City and analyze the samples with gender and age. At the same time, routine tumor marker examination and the location of NEN in the digestive system were performed. The distribution analysis of EUS characteristics of neuroendocrine tumor mucosa in each site was performed after operation, and the analysis of survival-related factors was performed during postoperative follow-up. The experimental data showed that among the tumor causes, WHO tumor grade () and whether the surgical method was R0 resection () were associated with prognosis. However, factors such as gender, age, and functional status were associated with prognosis. It has successfully completed the subject of surgical strategy and prognosis of pancreatic neuroendocrine tumors based on smart medical image analysis.
Clinicopathological, Oncogenic, and 18F-FDG PET/CT Features of Primary Pulmonary Carcinoid in Resection Specimens
Objectives. The metabolic parameters which included mean standardised uptake value (SUVmean), metabolic tumour volume (MTV), total lesion glycolysis (TLG), maximum standardised uptake lean body mass (SULmax), and maximum standardised uptake body surface area (SUVbsa) have rarely been investigated in pulmonary carcinoid (PC). This study aimed to retrospectively compare the 18F-FDG PET/CT features of PC subtypes and observe clinicopathological and oncogenic characteristics of PC. Methods. We performed a retrospective review in 60 patients with PC, from January 2016 to November 2021, who underwent the 18F-FDG PET/CT scan. All the PC diagnoses were histopathologic confirmed by surgical samples. The metabolic and morphological features were obtained from 18F-FDG PET/CT images. The ratio of metabolic to morphological lesion volumes (MMVR) was calculated. Results. Sixty patients with PC were consecutively identified, including 39 patients (65.0%) with typical carcinoids (TCs) and 21 (35.0%) with atypical carcinoids (ACs). One (1/21) patient had mutation in BRAF. The ACs have a larger size ( < 0.001), more metastatic lymph nodes ( = 0.011), higher Ki-67 expression ( < 0.001), higher SUVmax values ( = 0.003), higher SUVmean values ( = 0.006), higher SULmax values ( = 0.005), higher SUVbsa values ( = 0.001), higher MTV values ( = 0.033), and higher TLG values ( = 0.002). The multivariate analysis showed that MMVR ( = 0.020) was significantly associated with AC. For predicting AC, the optimal cut-off value of SUVmax, SUVmean, SULmax, SUVbsa, MTV, TLG, and the maximum diameter was 5.19, 3.18, 2.65, 1.47, 4.36, 18.44, and 3.0, respectively. The AUC values of above mentioned parameters was 0.756 (95%CI, 0.631–881; = 0.001), 0.735 (95%CI, 0.602–868; = 0.003), 0.736 (95%CI, 0.607–865; = 0.003), 0.742 (95%CI, 0.612–873; = 0.002), 0.593 (95%CI, 0.430–755; = 0.239), 0.680 (95%CI, 0.531–829; = 0.022), and 0.733 (95%CI, 0.598–868; = 0.003), respectively. For predicting TC, the optimal cut-off value of the MMVR was 0.92, and the AUC value was 0.780 (95%CI, 0.647–0.913; < 0.001). Conclusion. 18F-FDG PET/CT can simultaneously reveal the metabolic and morphological characteristics of PC, which is important in the differentiation for histopathologic subtypes.
Application and Clinical Value of Machine Learning-Based Cervical Cancer Diagnosis and Prediction Model in Adjuvant Chemotherapy for Cervical Cancer: A Single-Center, Controlled, Non-Arbitrary Size Case-Control Study
Objective. A case-control study was conducted to explore the application and clinical value of machine learning-based cervical cancer (CC) diagnosis and prediction model in adjuvant chemotherapy of CC. Methods. From August 2019 to August 2021, 46 patients with stage IA CC (study group) and 55 patients with high-grade squamous intraepithelial lesions (HSIL) (control group) were retrospectively analyzed. All patients completed routine MRI examinations, the ADC values of diseased CC and normal cervix and cervical tissues in different stages were compared, and the changes of ADC values in CC tissues before and after chemotherapy were analyzed. The training set (IA = 37, HSIL = 44) and test set (IA = 9, HSIL = 11) are set in a ratio of 4 : 1. The preoperative MRI images were collected and uploaded to the radiomics cloud platform after preprocessing, and the cervix was manually delineated layer by layer on OSag-T2WI, OAx-T1WI, and OAx-T2FS, respectively, to obtain a three-dimensional volume of interest (VOI) of the cervix to extract omics features. Variance Threshold analysis, univariate feature selection (SelectKBest), and least absolute shrinkage and selection operator (LASSO) are adopted to reduce the dimension of data and enroll features. The arbitrary forest model was adopted for machine learning, the ROC curve was drawn, and the diagnostic performance of different sequence omics models was analyzed. Results. Compared with ADC of stage A CC and HSIL, the ADC value of CC was remarkably lower than that of normal CC (). The ROC curve analysis of ADC value to differentiate CC and normal cervix indicated that the AUC was 0.838 and the 95% confidence interval was 0.721–0.955. According to the maximum Youden index of 0.848, the optimal critical value of ADC was 1.267 × 10−3 mm2/s and the sensitivity and specificity were 92.21% and 9.48%, respectively. All results are indicated in Table 2. After CC treatment, 12 patients were effective (CR + PR) and 4 patients were ineffective (PD + SD). When the b value was 1000 s/mm2, the ADC value of the effective patients after the second chemotherapy was significantly higher than that of the first chemotherapy and before treatment (). There was no significant difference between the ADC value after the first chemotherapy and before treatment, compared with before treatment (). There was no significant difference in ADC value between the ineffective patients before treatment and after the first and second chemotherapy (). A total of 8 omics features were extracted based on OSag-T2WI, all of which were wavelet features, including 7 texture features and 1 first-order feature. A total of 10 omics features were extracted based on OAx-T1WI, including 6 wavelet first-order features, 2 gradient first-order features, and 2 wavelet texture features. Based on OAx-T2FS, 6 omics features were extracted, including 3 wavelet texture features, 2 original shape features, and 1 logarithmic first-order feature. Based on OSag-T2WI&OAx-T2FS, 9 histological features were extracted, 4 from OSag-T2WI and 5 from OAx-T2FS. The diagnostic performance of the four arbitrary forest models is indicated in Table 1, and the ROC curve is indicated in Figure 6. The diagnostic performance of the omics model based on OSag-T2WI&OAx-T2FS was the best in both the training set and the test set. The AUC of the training set was 0.991 (95% CI (0.94, 1.00)), and the accuracy rate was 0.925. The AUC of the test set was 0.894 (95% CI (0.75, 1.00)), and the accuracy rate was 0.835. On the other hand, the diagnostic efficiency of the group model based on OAx-T1WI was the worst in both the training set and the test set. The AUC of the training set was 0.713 (95% CI (0.52, 0.92)), and the accuracy rate was 0.71. The AUC of test set is 0.513 (95% CI (0.24, 0.77)), and the accuracy rate was 0.56, which has no practical clinical significance. Conclusion. A CC diagnosis and prediction model based on machine learning can better distinguish stage IA CC from HSIL in the absence of clear lesions, which is of great significance for reducing invasive examination before surgery, guiding surgical procedures and adjuvant chemotherapy for CC.
Clinical Utility of the Prenatal Ultrasound Score of the Placenta Combined with Magnetic Resonance Imaging in Diagnosis of Placenta Accreta during the Second and Third Trimester of Pregnancy
Objective. The aim is to explore the clinical utility of the prenatal ultrasound score of the placenta combined with magnetic resonance imaging (MRI) in diagnosis of placenta accreta during the second and third trimester of pregnancy. Materials and Methods. A total of 108 pregnant women with suspected placenta accreta treated in Wuhan Hankou Hospital and Yantaishan Hospital of Yantai from January 2019 to January 2022 were retrospectively analyzed, the enrolled pregnant women received MRI examination because of suspected results of ultrasonic diagnosis, and by taking pathologic findings as the gold standard, the diagnostic efficacy of the ultrasound score, MRI, and their combination to placenta accreta during the second and third trimester of pregnancy was analyzed, and the diagnostic sensitivity, specificity, the positive predictive value, and the negative predictive value of these diagnostic modalities were evaluated. Results. Among 108 patients with suspected placenta accreta, 75 with pathologically confirmed placenta accreta were included in the accreta group, and 33 without placenta accreta were included in the non-accreta group; no statistical between-group differences in the patients’ age, gestational weeks, educational degree, and other general data were observed (), but the history of cesarean section, history of induced abortion, and incidence rate of placenta praevia were significantly higher in the accreta group than in the non-accreta group (); the ultrasound score was significantly higher in the accreta group than in the non-accreta group (); the incidence rates of signs of “placental heterogeneity” and “bulge of lower segment of the uterus and local thickening of the placenta” were obviously higher in the accreta group than in the non-accreta group (); according to the comparison with pathologic findings, the accuracy rate, sensitivity, specificity, the positive predictive value, and the negative predictive value of combined diagnosis were significantly higher than those of single application of the ultrasound score and MRI diagnosis (); and ROC analysis found that the area under the curve of combined diagnosis was obviously larger than that of the ultrasound score and MRI diagnosis (). Conclusion. A combining prenatal ultrasound score of the placenta with MRI plays an important role in the diagnosis of placenta accreta during the second and third trimester of pregnancy, which can further improve the diagnostic accuracy rate of placenta accreta and provide significant guidance in preventing high-risk complications during the perinatal period.