The value of CT-based radiomics in early assessment of chemotherapeutic effect in patients with advanced lung adenocarcinoma: a preliminary study.

BACKGROUND: Computed tomography (CT) is the preferred method for evaluating the therapeutic effect of lung cancer. Radiomics parameters can provide a lot of supplementary information for clinical diagnosis and treatment. PURPOSE: To investigate the value of radiomics features of CT imaging to predict and evaluate the early efficacy of chemotherapy in patients with advanced lung adenocarcinoma. MATERIAL AND METHODS: A total of 101 patients with advanced lung adenocarcinoma were enrolled. Patients were classified into a response group and non-response group according to RECIST 1.1 standard. All patients underwent chest CT examination before and after two cycles of chemotherapy. A total of 293 radiomics features were calculated. The features between response group and non-response group were compared before and after chemotherapy. The diagnostic efficacy was evaluated using the receiver operating characteristic curve. RESULTS: The six pre-chemotherapy radiomics features were selected, with area under the curve (AUC), sensitivity, and specificity at 0.720, 68.3%, and 69.0% in the training group and 0.573, 50.0%, and 76.9% in the test group, respectively. The eleven post-chemotherapy radiomics features were selected, with AUC, sensitivity, specificity at 0.789, 75.6%, and 75.9% in the training group and 0.718, 61.1%, and 76.9% in the test group, respectively. The prognostic value of △f8, △f16, %f8, and %f16 were higher than the other features with AUCs of 0.787, 0.837, 0.763, and 0.877, respectively. CONCLUSION: Radiomics is expected to provide more valuable information for evaluating the chemotherapy efficacy of lung adenocarcinoma.

LI-RADS category 3, 4, and M observations: a multiple parameters diagnostic model for hepatocellular carcinoma.

BACKGROUND: Hepatic lesions categorized as LR-3, LR-4, and LR-M are challenging to accurately assess and diagnose. PURPOSE: To combine potential clinical and/or magnetic resonance imaging (MRI) features for a more comprehensive hepatocellular carcinoma (HCC) versus non-HCC diagnosis for patients with LR-3, LR-4, and LR-M graded lesions. METHODS: Data were consecutively retrieved from 82 at-risk patients with LR-3 (n = 43), LR-4 (n = 20), and LR-M (n = 23) lesions. Significant findings for the differentiation of HCC and non-HCC, including MRI features and clinical factors, were identified with univariable and multivariable analyses. The variables for a prediction model were selected through stepwise use of Akaike's Information Criterion (AIC) to build multivariable logistic regression model. RESULTS: Serum alpha-fetoprotein (AFP) >16.2 ng/mL (odds ratio [OR] = 22.4; P = 0.006), septum (OR = 52.1; P = 0.011), and hepatobiliary phase (HBP) hypointensity (OR = 40.2; P = 0.001) were confirmed as independent predictors of HCC. When combining the three predictors and mild-moderate T2 hyperintensity, the model (AIC = 50.91) showed good accuracy with a C-index of 0.948. CONCLUSION: In at-risk patients with LR-3, LR-4, or LR-M lesions, integrating AFP, septum, HBP hypointensity, and mild-moderate T2 hyperintensity achieved high diagnostic performance for the diagnosis of HCC.

Pretreatment MR-Based Radiomics Signature as Potential Imaging Biomarker for Assessing the Expression of Topoisomerase II alpha (TOPO-IIα) in Rectal Cancer.

BACKGROUND: Rectal cancer (RC) is one of the most common cancers throughout the world. Chemotherapy or neoadjuvant chemotherapy play an important role in the treatment of advanced RC. Whether to add topoisomerase inhibitor to individualized chemotherapy is a puzzling question for clinicians. PURPOSE: To investigate whether pretreatment MR-based radiomics signature can assess the expression of topoisomerase II alpha (TOPO-IIα) in RC. STUDY TYPE: Retrospective. POPULATION: In all, 122 patients with RC. Field Strength/Sequence: Pretreatment 3.0T; T2 WI turbo spin echo (TSE) sequence. ASSESSMENT: A training group (n = 85) and a test group (n = 37) with pathologically confirmed RC. Patients underwent TOPO-IIα expression. A total of 180 radiomics features were extracted from oblique axial T2 WI TSE images of the entire primary tumor. The least absolute shrinkage and selection operator (LASSO) regression model was used to reduce the dimension of the data and select the features. STATISTICAL TESTS: The assessment models were established by multivariable logistic regression analysis. The performance of the model was assessed by the receiver operating characteristic (ROC) curve, nomogram, and calibration. RESULTS: The radiomics signature, which consisted of 10 selected optimal features, was significantly associated with TOPO-IIα expression (P < 0.01 for both training and test groups). The area under the curve (AUC), the sensitivity, and the specificity for assessing TOPO-IIα expression, were 0.859, 0.872, and 0.739, respectively, in the training group, while they were 0.762, 0.941, and 0.600 in the test group. The nomogram model of the radiomics signature (Rad-score) had good calibration. Calibration curves were plotted to assess the calibration of the radiomics nomogram that was accompanied with the Hosmer-Lemeshow test (P = 0.52). DATA CONCLUSION: The proposed pretreatment MR-based radiomics signature was associated with TOPO-IIα expression. A radiomics nomogram might be helpful in the individualized assessment of TOPO-IIα expression in patients with RC. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:1881-1889.

Diffusion kurtosis imaging and tumour microstructure for monitoring response to radiotherapy in human nasopharyngeal carcinoma xenografts.

OBJECTIVE: To investigate the correlations and feasibility of diffusion kurtosis imaging (DKI) parameters and tumour histopathology after radiotherapy in human nasopharyngeal carcinoma (NPC) xenografts on nude mice. MATERIALS AND METHODS: Seventy-two nude mice were used for the construction of CNE-1 (radio-insensitive) and CNE-2 (radio-sensitive) NPC xenograft models, followed by fraction irradiation at different doses of X-ray. The nude mice were randomly divided into six groups in each cell line models according to the dose of X-ray they have received and with six mice in each group. DKI scan was performed after radiation. DKI parameters, tumour histopathology and AQP-1 biomarkers were detected. One-way ANOVA and Pearson's correlation analysis were used in statistical analysis. RESULTS: In CNE-1 and CNE-2 NPC xenografts, D values were increased (P < 0.01 and P < 0.001), while K values (P < 0.01 and P < 0.001) and tumour size (P < 0.001 and P < 0.001) were reduced during fraction irradiation. Additionally, cell density (CD) and AQP-1 expressions were decreased, and necrosis ratio (NR) was increased in CNE-2 xenografts after fraction irradiation (P < 0.001). The changes in D values were negatively correlated with tumour size (r = -0.856, P < 0.001), CD (r = -0.918, P < 0.001), AQP-1 mRNA (r = -0.856, P < 0.001) and protein (r = -0.381, P = 0.022) expressions while positively correlated with NR (r = 0.908, P < 0.001) in CNE-2 xenografts. The changes in K values were positively correlated with tumour size (r = 0.964, P < 0.001), CD (r = 0.888, P < 0.001), AQP-1 mRNA (r = 0.955, P < 0.001) and protein (r = 0.330, P = 0.049) expression levels while negatively correlated with NR (r = -0.930, P < 0.001). However, in CNE-1 xenografts, there were no correlation between DKI parameters and the expression of AQP-1. CONCLUSION: Changes in D and K parameters after fractional irradiation are closely related with NPC cellular and pathological characteristics, especially size reduction and necrosis induction. These parameters exhibit potential abilities of monitoring the response to fractional irradiation in radio-sensitive NPC xenografts.

Integrating dynamic contrast-enhanced magnetic resonance imaging and diffusion kurtosis imaging for neoadjuvant chemotherapy assessment of nasopharyngeal carcinoma.

BACKGROUND: Since neoadjuvant chemotherapy (NAC) has proven a benefit for locally advanced nasopharyngeal carcinoma (NPC), early response evaluation after chemotherapy is important to implement individualized therapy for NPC in the era of precision medicine. PURPOSE: To determine the combined and independent contribution between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion kurtosis imaging (DKI) in the early monitoring of NAC response for NPC. STUDY TYPE: Prospective. POPULATION: Fifty-three locally advanced NPC patients. FIELD STRENGTH/SEQUENCE: Four examinations before and at 4, 20, and 40 days after NAC initiation were performed at 3T MRI including DCE-MRI and DKI (b values = 0, 500, 1000, 1500 s/mm2 ). ASSESSMENT: DCE-MRI parameters (Ktrans [the volume transfer constant of Gd-DTPA], kep [rate constant], νe [the extracellular volume fraction of the imaged tissue], and νp [the blood volume fraction]) and DKI parameters (Dapp [apparent diffusion for non-Gaussian distribution] and Kapp [apparent kurtosis coefficient]) were analyzed using dedicated software. STATISTICAL TESTS: MRI parameters and their corresponding changes were compared between responders and nonresponders after one or two NAC cycles treatment using independent-samples Student's t-test or Mann-Whitney U-test depending on the normality contribution test and then followed by logistic regression and receiver operating characteristic curve (ROC) analyses. RESULTS: The responder group (RG) patients presented significantly higher mean Ktrans and Dapp values at baseline and larger Δ K ( 0 - 4 ) trans , Δvp(0-4) , and ΔDapp(0-4) values after either one or two NAC cycles compared with the nonresponder group (NRG) patients (all P < 0.05). ROC analyses demonstrated the higher diagnostic accuracy of combined DCE-MRI and DKI model to distinguish nonresponders from responders after two NAC cycles than using DCE-MRI (0.987 vs. 0.872, P = 0.033) or DKI (0.987 vs. 0.898, P = 0.047) alone. DATA CONCLUSION: Combined DCE-MRI and DKI models had higher diagnostic accuracy for NAC assessment compared with either model used independently. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1208-1216.

Early response to chemoradiotherapy for nasopharyngeal carcinoma treatment: Value of dynamic contrast-enhanced 3.0 T MRI.

PURPOSE: To prospectively evaluate the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) value for predicting early nasopharyngeal carcinoma (NPC) chemoradiotherapy (CRT) response. MATERIALS AND METHODS: Forty-two patients with advanced NPC were recruited and received three DCE-MRI exams before treatment (Pre-Tx), as well as 3 days (Day 3-Tx) and 40 days (Day 40-Tx) after chemotherapy initiation (two neoadjuvant chemotherapy cycles, NAC). We used DCE-Tool to measure primary tumor kinetic parameters (K(trans) , Kep , ve , and vp ) using the extended Tofts model. Kinetic parameters and corresponding changes were compared between responders and nonresponders after NAC or CRT treatment using Student's t or Mann-Whitney U tests. RESULTS: Response to two NAC cycles correlated with short-term local control (P = 0.01). Compared to the nonresponder group, the responder group presented with significantly larger ΔK(trans) (0-3) , ΔKep(0-3) , and Δvp(0-3) values after NAC (P < 0.05). The complete response group after CRT exhibited significantly lower K(trans) (Day 40-Tx) and larger ΔK(trans) (0-3) values than the residual group (P = 0.05). High sensitivity (range: 74.1%-90%) and moderate-to-high specificity (range: 50%-84.3%) distinguished nonresponders from responders grouping after NAC or CRT, with diagnostic efficiency ranging from 69.3%-88%. CONCLUSION: Our study showed kinetic parameter changes earlier after chemotherapy were potential markers for NPC patients receiving CRT therapy following NAC.

Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients.

PURPOSE: To explore the clinical value of diffusion kurtosis imaging (DKI) and monoexponential diffusion-weighted imaging (DWI) for predicting early response to neoadjuvant chemotherapy (NAC) in patients with nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: Fifty-nine patients with stage III-IVb NPC underwent four 3.0T MR scans: prior to, and on the 4th, 21st, 42nd days after NAC initiation. The parameters of DKI (corrected diffusion coefficient, D; excess diffusion kurtosis coefficient, K) and monoexponential DWI (apparent diffusion coefficient, ADC) were obtained at the first three scans. Statistical methods included Student's t-test or Mann-Whitney U-test, receiver operating characteristic (ROC) curve analyses and paired X(2) test. RESULTS: D(pre) in responders group (RG) was significantly lower than nonresponders group (NRG) (1.029 ± 0.033 vs. 1.184 ± 0.055, ×10(-3) mm(2) /s, P = 0.020). ADC(day4) and ΔD(day4) were the most useful parameters of the two diffusional models to distinguish RG from NRG, respectively (area under the curve, 0.761 vs. 0.895). ΔD(day4) was more sensitive than ADC(day4) to predict treatment response to NAC (P = 0.006). CONCLUSION: Both DKI and monoexponential DWI showed potential to predict treatment response to NAC prior to morphological change. DKI may be superior to monoexponential DWI for predicting early response to NAC in patients with locally advanced NPC.

Dynamic contrast-enhanced MRI of nasopharyngeal carcinoma: a preliminary study of the correlations between quantitative parameters and clinical stage.

PURPOSE: To evaluate the relationship between quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical stage of nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: Fifty-one newly diagnosed NPC patients received MRI examination on Philips Achieva 3.0 Tesla TX MR system. We used DCE-Tool (Philips Healthcare, Best, The Netherlands) to investigate parameters from primary tumors. Tumor/node/metastasis and corresponding clinical stages were determined based on 2009 UICC 7th edition. The correlations between quantitative parameters and clinical stage were correlated using Pearson correlation analysis. RESULTS: Mean K(trans) , Kep , ve , and vp for primary tumors were 0.500 ± 0.188/min, 0.744 ± 0.273/min, 0.986 ± 0.595, and 0.052 ± 0.071, respectively. Both K(trans) and Kep of tumors showed moderate negative correlation with clinical stage, T stage and N stage (P < 0.05), while ve showed moderate positive correlation with them (P < 0.05). vp revealed a moderate negative correlation with T stage (r = -0.369; P < 0.004). Kep and ve have significant differences between many early and advanced stages patients. CONCLUSION: DCE-MRI is feasible to assess vascular permeability of NPC patients. Our results first revealed that the quantitative parameters were significantly related to clinical stage of NPC. Thus, DCE-MRI may be valuable to add noninvasive prognostic indicators in evaluating NPC.

The application value of LAVA-flex sequences in enhanced MRI scans of nasopharyngeal carcinoma: comparison with T1WI-IDEAL.

Introduction: Magnetic resonance imaging (MRI) staging scans are critical for the diagnosis and treatment of patients with nasopharyngeal cancer (NPC). We aimed to evaluate the application value of LAVA-Flex and T1WI-IDEAL sequences in MRI staging scans. Methods: Eighty-four newly diagnosed NPC patients underwent both LAVA-Flex and T1WI-IDEAL sequences during MRI examinations. Two radiologists independently scored the acquisitions of image quality, fat suppression quality, artifacts, vascular and nerve display. The obtained scores were compared using the Wilcoxon signed rank test. According to the signal intensity (SI) measurements, the uniformity of fat suppression, contrast between tumor lesions and subcutaneous fat tissue, and signal-to-noise ratio (SNR) were compared by the paired t-test. Results: Compared to the T1WI-IDEAL sequence, LAVA-Flex exhibited fewer artifacts (P<0.05), better visualization of nerves and vessels (P<0.05), and performed superior in the fat contrast ratio of the primary lesion and metastatic lymph nodes (0.80 vs. 0.52, 0.81 vs. 0.56, separately, P<0.001). There was no statistically significant difference in overall image quality, tumor signal-to-noise ratio (SNR), muscle SNR, and the detection rate of lesions between the two sequences (P>0.05). T1WI-IDEAL was superior to LAVA-Flex in the evaluation of fat suppression uniformity (P<0.05). Discussion: LAVA-Flex sequence provides satisfactory image quality and better visualization of nerves and vessels for NPC with shorter scanning times.

Automated segmentation of brain metastases with deep learning: a multi-center, randomized crossover, multi-reader evaluation study.

BACKGROUND: Artificial intelligence has been proposed for brain metastasis (BM) segmentation but it has not been fully clinically validated. The aim of this study was to develop and evaluate a system for BM segmentation. METHODS: A deep-learning-based BM segmentation system (BMSS) was developed using contrast-enhanced MR images from 488 patients with 10,338 brain metastases. A randomized crossover, multi-reader study was then conducted to evaluate the performance of the BMSS for BM segmentation using data prospectively collected from 50 patients with 203 metastases at five centers. Five radiology residents and five attending radiologists were randomly assigned to contour the same prospective set in assisted and unassisted modes. Aided and unaided Dice similarity coefficients (DSCs) and contouring times per lesion were compared. RESULTS: The BMSS alone yielded a median DSC of 0.91 (95% confidence interval, 0.90-0.92) in the multi-center set and showed comparable performance between the internal and external sets (p = 0.67). With BMSS assistance, the readers increased the median DSC from 0.87 (0.87-0.88) to 0.92 (0.92-0.92) (p < 0.001) with a median time saving of 42% (40-45%) per lesion. Resident readers showed a greater improvement than attending readers in contouring accuracy (improved median DSC, 0.05 [0.05-0.05] vs. 0.03 [0.03-0.03]; p < 0.001), but a similar time reduction (reduced median time, 44% [40-47%] vs. 40% [37-44%]; p = 0.92) with BMSS assistance. CONCLUSIONS: The BMSS can be optimally applied to improve the efficiency of brain metastasis delineation in clinical practice.

Early assessment of induction chemotherapy response of nasopharyngeal carcinoma by pretreatment diffusion-weighted magnetic resonance imaging.

OBJECTIVES: This study aimed to evaluate the feasibility of pretreatment diffusion-weighted imaging in predicting response after induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). METHODS: Fifty-four patients with stage III and IV NPC underwent MRI examination at baseline, after 2 cycles of chemotherapy, and at the end of chemoradiotherapy. Apparent diffusion coefficient (ADC) values were compared between effective and ineffective subjects after IC. RESULTS: Mean ADC in effective groups was significantly (P < 0.05) higher than that in the ineffective group. Average and minimum ADCs demonstrated higher sensitivity than maximum ADC for predicting IC response, with 68.4%, 71.1%, and 50.0%, respectively, at an equivalent 68.7% specificity. We observed negative correlations between pretreatment ADC and tumor regression after chemotherapy (γ = - 0.425, P = 0.001) and after chemoradiotherapy (γ = - 0.418, P = 0.003). CONCLUSIONS: Pretreatment ADC was a valuable biomarker for predicting IC response of NPC. Noninvasive diffusion-weighted imaging provides additional indicator in guiding optical therapeutic options for patients with NPC.

The role of radiologic extranodal extension in predicting prognosis and chemotherapy benefit for T1-2 N1 nasopharyngeal carcinoma: A multicenter retrospective study.

BACKGROUND AND PURPOSE: This multicenter retrospective study aimed to investigated the prognostic value of unequivocal radiologic extranodal extension (rENE) and the efficacy of chemotherapy for stage T1-2 N1 nasopharyngeal carcinoma (NPC) in the IMRT era. MATERIALS AND METHODS: We included 1,082 patients treated in 2005-2017 from three centers. rENE was recorded as G1 (coalescent nodal mass comprising ≥ 2 inseparable nodes) or G2 (invading beyond perinodal fat to frankly infiltrate adjacent structures). Multivariable analysis (MVA) evaluated the prognostic value of rENE. The value of chemotherapy was assessed in rENE-positive (rENE + ) and rENE-negative (rENE - ) subset separately. RESULTS: Centers 1, 2, and 3 had 139/515 (27.0 %), 100/365 (27.4 %), and 43/202 (21.3 %) cN + patients with rENE, respectively. Compared to rENE-, rENE + patients had a worse distant metastasis-free survival (DMFS) and overall survival (OS) (all p < 0.001). MVA confirmed the prognostic of both G1-rENE and G2-rENE for distant metastasis [G1: hazard ratio (HR): 2.933, G2: HR: 6.942, all p < 0.001] and death (G1: HR: 1.587, p = 0.040; G2: HR: 6.162, p < 0.001). There was no significant difference for DMFS and OS between chemo-radiotherapy and radiotherapy alone in rENE + and rENE - groups (all p > 0.1). However, rENE + patients with a cumulative cisplatin/nedaplatin dose (CCND) of > 160 mg/m2 had an improved DMFS (p = 0.033) but no OS (p = 0.197). CONCLUSION: Unequivocal rENE is prognostic in patients with T1-2 N1 NPC. Addition of chemotherapy to radiotherapy did not affect DMFS and OS in rENE - patients. Chemotherapy with a CCND of > 160 mg/m2 improved DMFS in rENE + patients.

False-negative and false-positive outcomes of computer-aided detection on brain metastasis: Secondary analysis of a multicenter, multireader study.

BACKGROUND: Errors have seldom been evaluated in computer-aided detection on brain metastases. This study aimed to analyze false negatives (FNs) and false positives (FPs) generated by a brain metastasis detection system (BMDS) and by readers. METHODS: A deep learning-based BMDS was developed and prospectively validated in a multicenter, multireader study. Ad hoc secondary analysis was restricted to the prospective participants (148 with 1,066 brain metastases and 152 normal controls). Three trainees and 3 experienced radiologists read the MRI images without and with the BMDS. The number of FNs and FPs per patient, jackknife alternative free-response receiver operating characteristic figure of merit (FOM), and lesion features associated with FNs were analyzed for the BMDS and readers using binary logistic regression. RESULTS: The FNs, FPs, and the FOM of the stand-alone BMDS were 0.49, 0.38, and 0.97, respectively. Compared with independent reading, BMDS-assisted reading generated 79% fewer FNs (1.98 vs 0.42, P < .001); 41% more FPs (0.17 vs 0.24, P < .001) but 125% more FPs for trainees (P < .001); and higher FOM (0.87 vs 0.98, P < .001). Lesions with small size, greater number, irregular shape, lower signal intensity, and located on nonbrain surface were associated with FNs for readers. Small, irregular, and necrotic lesions were more frequently found in FNs for BMDS. The FPs mainly resulted from small blood vessels for the BMDS and the readers. CONCLUSIONS: Despite the improvement in detection performance, attention should be paid to FPs and small lesions with lower enhancement for radiologists, especially for less-experienced radiologists.

Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation study.

BACKGROUND: Accurate detection is essential for brain metastasis (BM) management, but manual identification is laborious. This study developed, validated, and evaluated a BM detection (BMD) system. METHODS: Five hundred seventy-three consecutive patients (10 448 lesions) with newly diagnosed BMs and 377 patients without BMs were retrospectively enrolled to develop a multi-scale cascaded convolutional network using 3D-enhanced T1-weighted MR images. BMD was validated using a prospective validation set comprising an internal set (46 patients with 349 lesions; 44 patients without BMs) and three external sets (102 patients with 717 lesions; 108 patients without BMs). The lesion-based detection sensitivity and the number of false positives (FPs) per patient were analyzed. The detection sensitivity and reading time of three trainees and three experienced radiologists from three hospitals were evaluated using the validation set. RESULTS: The detection sensitivity and FPs were 95.8% and 0.39 in the test set, 96.0% and 0.27 in the internal validation set, and ranged from 88.9% to 95.5% and 0.29 to 0.66 in the external sets. The BMD system achieved higher detection sensitivity (93.2% [95% CI, 91.6-94.7%]) than all radiologists without BMD (ranging from 68.5% [95% CI, 65.7-71.3%] to 80.4% [95% CI, 78.0-82.8%], all P < .001). Radiologist detection sensitivity improved with BMD, reaching 92.7% to 95.0%. The mean reading time was reduced by 47% for trainees and 32% for experienced radiologists assisted by BMD relative to that without BMD. CONCLUSIONS: BMD enables accurate BM detection. Reading with BMD improves radiologists' detection sensitivity and reduces their reading times.

Evaluation of the Efficacy and Performance of a New Nano-Drug Carrier in the Treatment of Recurrent Oral Ulcerper.

Recurrent oral ulcer is a common oral mucosal disease. Due to its periodic and recurrent characteristics, the onset of burning pain is unbearable, which brings great inconvenience to the patient's life and seriously affects the patient's quality of life. There are certain limitations to conventional drug therapy. With the rapid development of nanotechnology, the obvious advantages of nanotechnology such as targeting, controlled release, biocompatibility is obviously shown. The combination of nanotechnology and medical research has led to the emergence of polymer nanoparticles and ligands. Nano-drugs for gene therapy, and many other new nano-drug carriers, polymer micelle is a new type of nano drug carrier that has appeared in recent years. It has both a hydrophilic shell and a hydrophobic core, and has a variety of excellent properties, such as higher stability in vivo and in vitro, and poorly soluble drugs. In this paper, a new method for treating recurrent oral ulcers based on a new nano-drug carrier was studied. Because of the hydrophilicity and biocompatibility of oral cell surface proteins, the research progress of nanopharmaceutical carrier in the treatment of recurrent oral ulcers is reviewed. The experimental results show that the method has good reproducibility and high efficiency in the treatment of recurrent oral ulcers. It is used to explore the application and progress of nanotechnology in the diagnosis and treatment of recurrent oral ulcers, and to provide new ideas for the clinical diagnosis and treatment of recurrent oral ulcers. This new technical method has wide practical application value.

Application Value of Magnetic Resonance Radiomics and Clinical Nomograms in Evaluating the Sensitivity of Neoadjuvant Chemotherapy for Nasopharyngeal Carcinoma.

OBJECTIVE: To predict the sensitivity of nasopharyngeal carcinoma (NPC) to neoadjuvant chemotherapy (NACT) based on magnetic resonance (MR) radiomics and clinical nomograms prior to NACT. MATERIALS AND METHODS: From January 2014 to July 2015, 284 consecutive patients with pathologically confirmed NPC underwent 3.0 T MR imaging (MRI) before initiating NACT. The patients' data were randomly assigned to a training set (n = 200) or a test set (n = 84) at a ratio of 7:3. The clinical data included sex, tumor (T) stage, lymph node (N) stage, American Joint Committee on Cancer (AJCC) stage, and the plasma concentration of Epstein-Barr virus (EBV) DNA. The regions of interest (ROI) were manually segmented on the axial T2-weighted imaging (T2WI) and enhanced T1-weighted imaging (T1WI) sequences using ITK-SNAP software. The radiomics data were post-processed using AK software. Moreover, the Maximum Relevance Minimum Redundancy (mRMR) algorithm and the Least Absolute Shrinkage and Selection Operator (LASSO) were adopted for dimensionality reduction to screen for the features that best predicted the treatment efficacy, and clinical risk factors were used in combination with radiomics scores (Rad-scores) to construct the clinical radiomics-based nomogram. DeLong's test was utilized to compare the area under the curve (AUC) values of the clinical radiomics-based nomogram, radiomics model, and clinical nomogram. Decision curve analysis (DCA) was employed to evaluate each model's net benefit. RESULTS: The clinical nomogram was constructed based on data from patients who were randomly assigned according to T2WI and enhanced T1WI sequences. In the training set, the T2WI sequence-based clinical radiomics nomogram and the radiomics model outperformed the clinical nomogram in predicting the NACT efficacy (AUC, 0.81 vs. 0.60, p = 0.001279 and 0.76 vs. 0.60, p = 0.03026). These findings were well-verified in the test set. The enhanced T1WI sequence-based clinical radiomics nomogram exhibited better performance in predicting treatment efficacy than the clinical nomogram (AUC, 0.79 vs. 0.62, respectively; p = 0.0000834). The DCA revealed that the T2WI and clinical radiomics-based nomograms resulted in a net benefit in predicting the NACT efficacy. CONCLUSION: The clinical radiomics-based nomogram improved the prediction of NACT efficacy, with the T2WI sequence-based clinical radiomics achieving the best effect.

Pretreatment MR-based radiomics nomogram as potential imaging biomarker for individualized assessment of perineural invasion status in rectal cancer.

PURPOSE: To investigate whether pretreatment magnetic resonance (MR)-based radiomics nomogram can individualize prediction of perineural invasion (PNI) status in rectal cancer (RC). MATERIAL AND METHODS: A total of 122 RC patients with pathologically confirmed were classified as training cohort (n = 87) and test cohort (n = 35). 180 radiomics features were extracted from all lesions based on oblique axial T2WI TSE images. The dimensionality reduction and feature selection in training cohort were realized by the maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression model. A predictive model combining radiomics features and clinical risk factors (pathological N stage, pathological LVI status) was established by multivariate logistic regression analysis. The performance of the model was assessed based on its receiver operating characteristic (ROC) curve, nomogram, and calibration. RESULTS: The developed radiomics nomogram that integrated the radiomics signature and clinical risk factors could provide discrimination in the training and test cohorts. The accuracy and the area under the curve (AUC) for assessing PNI status were 0.82, 0.86, respectively, in the training cohort, while they were 0.71 and 0.85 in the test cohort. The goodness-of-fit of the nomogram was evaluated using the Hosmer-Lemeshow test (p = 0.52 in training cohort and p = 0.24 in test cohort). Decision curve analysis (DCA) showed that the radiomics nomogram was clinically useful. CONCLUSION: The developed radiomics nomogram might be helpful in the individualized assessment PNI status in patients with RC. This stratification of RC patients according to their PNI status may provide the basis for individualized adjuvant therapy, especially for stage II patients.

Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer.

Radiomics is a method to mine large numbers of quantitative imaging features and develop predictive models. It has shown exciting promise for improved cancer decision support from early detection to personalized precision treatment, and therefore offers a desirable new direction for pancreatic cancer where the mortality remains high despite the current care and intense research. For radiomics, interobserver segmentation variability and its effect on radiomic feature stability is a crucial consideration. While investigations have been reported for high-contrast cancer sites such as lung cancer, no studies to date have investigated it on CT-based radiomics for pancreatic cancer. With three radiation oncology observers and three radiology observers independently contouring on the contrast CT of 21 pancreatic cancer patients, we conducted the first interobserver segmentation variability study on CT-based radiomics for pancreatic cancer. Moreover, our novel investigation assessed whether there exists an interdisciplinary difference between the two disciplines. For each patient, a consensus tumor volume was generated using the simultaneous truth and performance level expectation algorithm, using the dice similarity coefficient (DSC) to assess each observer's delineation against the consensus volume. Radiation oncology observers showed a higher average DSC of 0.81 ± 0.06 than the radiology observers at 0.69 ± 0.16 (p = 0.002). On a panel of 1277 radiomic features, the intraclass correlation coefficients (ICC) was calculated for all observers and those of each discipline. Large variations of ICCs were observed for different radiomic features, but ICCs were generally higher for the radiation oncology group than for the radiology group. Applying a threshold of ICC > 0.75 for considering a feature as stable, 448 features (35%) were found stable for the radiation oncology group and 214 features (16%) were stable from the radiology group. Among them, 205 features were found stable for both groups. Our results provide information for interobserver segmentation variability and its effect on CT-based radiomics for pancreatic cancer. An interesting interdisciplinary variability found in this study also introduces new considerations for the deployment of radiomics models.

Early diagnosis of radio-insensitive human nasopharyngeal carcinoma xenograft models by diffusion kurtosis imaging.

OBJECTIVE: To investigate the feasibility of DKI in early detection of radio-insensitive nasopharyngeal carcinoma (NPC) xenografts in nude mice. MATERIALS AND METHODS: Seventy-two nude mice were implanted with CNE-1 (low radio-sensitive) and CNE-2 (high radio-sensitive) NPC cell lines, and their respective xenografts were obtained. Then, the NPC-bearing nude mice were exposed to different doses of fraction irradiation, which are divided into non-irradiated group (G0), 10Gy group (G1), 20Gy group (G2), 30Gy group (G3), 3rd (G4) and 5th (G5) days after the entire dose (30y) of irradiation. Subsequently, DKI was performed on each group. Tumor volumes, shrink rates, D and K parameters were measured by two experienced radiologists. Student's t-test and receiver operating characteristic (ROC) curve analysis were conducted in this study. RESULTS: The differences of volume shrinkage rate between CNE-1 and -2 were observed in G2 (P = 0.032), with the shrink rates of 5.954% and 27.716%, respectively. The D values were reduced at G1 (DG1, P = 0.001) and then increased gradually after irradiation. The K values were increased at G1 (KG1, P = 0.001) and then declined sharply in CNE-2 (P < 0.01), but not in CNE-1 xenografts (P > 0.05). The respective AUC values for DG1 and KG1 were 0.875 and 0.917, with 66.7% and 83.3% sensitivity and 100% specificity, at the cutoff values of 1.27 × 10-3 mm2/s for parameter D and 0.88 for parameter K. CONCLUSION: DKI can be used for early detection of radio-insensitive NPC xenografts prior to morphological change, where DG1 and KG1 may be the most valuable indicators.

Establishment of prognostic factors in recurrent nasopharyngeal carcinoma patients who received salvage intensity-modulated radiotherapy: A meta-analysis.

Local recurrence remains a major cause of therapeutic failure in patients with nasopharyngeal carcinoma (NPC) and the effective treatment of recurrent NPC (r-NPC) is still a challenge. Intensity-modulated radiotherapy (IMRT) is considered as a favorable technique in the management of r-NPC, especially for extensive lesions. However, local r-NPC is a highly heterogeneous disease and the survival outcome following salvage IMRT varies. Furthermore, due to varied samples and therapeutic protocols, no consensus has been reached in the establishment of prognostic values. Hence, we used Medline and Embase electronic databases to conducted a meta-analysis to generate the best estimation of the prognostic factors in local r-NPC following salvage IMRT. Finally, a total of 783 patients in seven studies were enrolled. Overall, the pooled HR for OS of recurrent T stage and recurrent tumor volume was 1.77 (95% CI = 1.15-2.39) and 2.12 (95% CI = 1.42-2.82), without any heterogeneity. In addition, despite a significant association was observed in the pooled HR of significant compliance for OS, however, significant heterogeneity was also observed (I2 = 76.6%, p = 0.039). Furthermore, no significant association was observed among the pooled HRs for OS in terms of age, gender, recurrent time interval, synchronous nodal recurrence, chemotherapy and total re-irradiation dose. Therefore, the present meta-analysis demonstrated that recurrent T stage and tumor volume may serve as the prognostic factors for OS in patients with r-NPC who received salvage IMRT. The other factors such as age, gender, and optimal re-irradiation dose warranted further investigation.