Bi-regional dynamic contrast-enhanced MRI for prediction of microvascular invasion in solitary BCLC stage A hepatocellular carcinoma

OBJECTIVES

To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy.

METHODS

Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (CDCE) were constructed to predict MVI. The combined model incorporating CDCE and CR features was developed and evaluated. Kaplan-Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches.

RESULTS

A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. CDCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and CDCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05).

CONCLUSION

The combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making.

CRITICAL RELEVANCE STATEMENT

The combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies.

KEY POINTS

Microvascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC). Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance. The combined model could help stratify the risk of recurrence and aid treatment planning.

Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion

OBJECTIVES

To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS.

METHODS

Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOVSTA) DWI, and fast rFOV with DLR (rFOVDLR) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS). Qualitative image quality scoring, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC value were evaluated. Friedman test with post hoc test revealed the difference across the three DWIs. Receiver operating characteristic analysis was performed to calculate the areas under the curve (AUCs).

RESULTS

The AUC of the rFOVSTA DWI and rFOVDLR DWI were higher than that of fFOV DWI. rFOVDLR DWI reduced the acquisition time from 5:02 min to 3:25 min, and showed higher scores in overall image quality with higher CNR and SNR, compared to rFOVSTA DWI (p < 0.05). The mean ADC of all cases of rFOVSTA DWI and rFOVDLR DWI was significantly lower than that of fFOV DWI (all p < 0.05). There was no difference in mean ADC value and the AUC for evaluating muscle invasion between rFOVSTA DWI and rFOVDLR DWI (p > 0.05).

CONCLUSIONS

rFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy.

CRITICAL RELEVANCE STATEMENT

The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality.

KEY POINTS

Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI.

Improving chilling tolerance of peanut seedlings by enhancing antioxidant-modulated ROS scavenging ability, alleviating photosynthetic inhibition, and mobilizing nutrient absorption

Peanut production is threatened by climate change. Damage to seedlings from low temperatures in early spring can limit yield. Plant adaptations to chilling stress remain unclear in peanut seedlings. It is essential to understand how peanut acquires chilling tolerance. We evaluated effects of chilling stress on growth and recovery of peanut seedlings. We compared and analysed biological characteristics, antioxidants, photosynthesis, biochemical and physiological responses, and nutrient absorption at varying levels of chilling. Compared with chilling-sensitive FH18, the reduced impact of chilling stress on chilling-tolerant NH5 was associated with reduced ROS accumulation, higher ascorbate peroxidase activity and soluble sugar content, lower soluble protein content, and smaller reductions in nutrient content during stress. After removal of chilling stress, FH18 had significant accumulation of O2 •- and H2O2, which decreased photosynthesis, nutrient absorption, and transport. ROS-scavenging reduced damage from chilling stress, allowed remobilization of nutrients, improved chilling tolerance, and restored plant functioning after chilling stress removal. These findings provide a reference for targeted research on peanut seedling tolerance to chilling and lay the foundation for bioinformatics-based research on peanut chilling tolerance mechanisms.

The Value of LI-RADS and Radiomic Features from MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma within 5 cm

RATIONALE AND OBJECTIVES

To explore and compare the performance of LI-RADS® and radiomics from multiparametric MRI in predicting microvascular invasion (MVI) preoperatively in patients with solitary hepatocellular carcinoma (HCC)< 5 cm.

METHODS

We enrolled 143 patients with pathologically proven HCC and randomly stratified them into training (n = 100) and internal validation (n = 43) cohorts. Besides, 53 patients were enrolled to constitute an independent test cohort. Clinical factors and imaging features, including LI-RADS and three other features (non-smooth margin, incomplete capsule, and two-trait predictor of venous invasion), were reviewed and analyzed. Radiomic features from four MRI sequences were extracted. The independent clinic-imaging (clinical) and radiomics model for MVI-prediction were constructed by logistic regression and AdaBoost respectively. And the clinic-radiomics combined model was further constructed by logistic regression. We assessed the model discrimination, calibration, and clinical usefulness by using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision-curve analysis respectively.

RESULTS

Incomplete tumor capsule, corona enhancement, and radiomic features were related to MVI in solitary HCC＜5 cm. The clinical model achieved AUC of 0.694/0.661 (training/internal validation). The single-sequence-based radiomic model's AUCs were 0.753-0.843/0.698-0.767 (training/internal validation). The combination model exhibited superior diagnostic performance to the clinical model (AUC: 0.895/0.848 [training/ internal validation]) and yielded an AUC of 0.858 in an independent test cohort.

CONCLUSION

Incomplete tumor capsule and corona enhancement on preoperative MRI were significantly related to MVI in solitary HCC＜5 cm. Multiple-sequence radiomic features potentially improve MVI-prediction-model performance, which could potentially help determining HCC's appropriate therapy.

Prognostic performance of MRI LI-RADS version 2018 features and clinical-pathological factors in alpha-fetoprotein-negative hepatocellular carcinoma

PURPOSE

To evaluate the role of the magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) version 2018 features and clinical-pathological factors for predicting the prognosis of alpha-fetoprotein (AFP)-negative (≤ 20 ng/ml) hepatocellular carcinoma (HCC) patients, and to compare with other traditional staging systems.

METHODS

We retrospectively enrolled 169 patients with AFP-negative HCC who received preoperative MRI and hepatectomy between January 2015 and August 2020 (derivation dataset:validation dataset = 118:51). A prognostic model was constructed using the risk factors identified via Cox regression analysis. Predictive performance and discrimination capability were evaluated and compared with those of two traditional staging systems.

RESULTS

Six risk factors, namely the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin-bilirubin grade, were associated with recurrence-free survival. The prognostic model constructed using these factors achieved C-index of 0.705 and 0.674 in the derivation and validation datasets, respectively. Furthermore, the model performed better in predicting patient prognosis than traditional staging systems. The model effectively stratified patients with AFP-negative HCC into high- and low-risk groups with significantly different outcomes (p < 0.05).

CONCLUSION

A prognostic model integrating the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin-bilirubin grade may serve as a valuable tool for refining risk stratification in patients with AFP-negative HCC.

An Acid-Responsive Iron-Based Nanocomposite for OSCC Treatment

Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, characterized by invasiveness, local lymph node metastasis, and poor prognosis. Traditional treatment and medications have limitations, making the specific inhibition of OSCC growth, invasion, and metastasis a challenge. The tumor microenvironment exhibits mildly acidity and high concentrations of H2O2, and its exploitation for cancer treatment has been widely researched across various cancers, but research in the oral cancer field is relatively limited. In this study, by loading ultra-small Prussian blue nanoparticles (USPBNPs) into mesoporous calcium-silicate nanoparticles (MCSNs), we developed an acid-responsive iron-based nanocomposite, USPBNPs@MCSNs (UPM), for the OSCC treatment. UPM demonstrated excellent dual enzyme activities, generating toxic ·OH in a mildly acidic environment, effectively killing OSCC cells and producing O2 in a neutral environment to alleviate tissue hypoxia. The results showed that UPM could effectively inhibit the proliferation, migration, and invasion of OSCC cells, as well as the growth of mice solid tumors, without obvious systemic toxicity. The mechanisms may involve UPM inducing ferroptosis of OSCC cells by downregulating the xCT/GPX4/glutathione (GSH) axis, characterized by intracellular iron accumulation, reactive oxygen species accumulation, GSH depletion, lipid peroxidation, and abnormal changes in mitochondrial morphology. Therefore, this study provides empirical support for ferroptosis as an emerging therapeutic target for OSCC and offers a valuable insight for future OSCC treatment.

Standardization method, testing scenario, and accuracy of the infrared prediction model affect the standardization accuracy of milk mid-infrared spectra

The widespread use of milk mid-infrared (MIR) spectroscopy for phenotype prediction has urged the application of prediction models across regions and countries. Spectra standardization is the most effective way to reduce the variability in the spectral signal provided by different instruments and labs. This study aimed to develop different standardization models for MIR spectra collected by multiple instruments, across 2 provinces of China, and investigate whether the standardization method (piecewise direct standardization, PDS, and direct standardization, DS), testing scenario (standardization of spectra collected on the same day or after 7 mo), infrared prediction model accuracy (high or low), and instrument (6 instruments from 2 brands) affect the performance of the standardization model. The results showed that the determination coefficient (R2) between absorbance values at each wavenumber provided by the primary and the secondary instruments increased from less than 0.90 to nearly 1.00 after standardization. Both PDS and DS successfully reduced spectra variation among instruments, and performed significantly better than non-standardization (P < 0.05). However, DS was more prone to overfitting than PDS. Standardization accuracy was higher when tested using spectra collected on the same time compared with those collected 7 mo after (P < 0.05), but great improvement in model transferability was obtained for both scenarios compared with the non-standardized spectra. The less accurate infrared prediction model (for C8:0 and C10:0 content) benefited the most (P < 0.05) from spectra standardization compared with the more accurate model (for total fat and protein content). For spectra collected after 7 mo from standardization, after PDS the RMSE between predictions obtained by different machines decreased on average by 86 and 94% compared with the values before standardization, for C8:0 and C10:0 respectively. The secondary instrument had no significant effect on the R2 between predictions (P > 0.05). The variation in the spectral signal provided by different instruments was successfully reduced by standardization across 2 provinces in China. This study lays the foundations for developing a national MIR spectra database to provide consistent predictions across provinces to be used in dairy farm management and breeding programs in China. Besides, this provides opportunities for data exchange and cooperation at international levels.

Value of Semi-Quantitative Parameters of 68Ga-FAPI-04 PET/CT in Primary Malignant and Benign Diseases: A Comparison with 18F-FDG

Objectives: We aimed to compare the value of the semiquantitative parameters of 68Ga-labeled FAP inhibitor (68Ga-FAPI)-04 positron emission tomography/computed tomography (PET/CT) and 18F-fluorodeoxyglucose (18F-FDG) in diagnosing primary malignant and benign diseases. Materials and Methods: 18F-FDG and 68Ga-FAPI-04 PET/CT images of 80 patients were compared. Semiquantitative parameters, including maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), peak SUV by lean body mass (SULpeak), metabolic tumor volume (or tumor volume of FAPI; FAPI-TV), and TLG (or total lesion activity of FAPI; FAPI-TLA), were automatically obtained using the IntelliSpace Portal image processing workstation with a threshold of 40% SUVmax. The liver blood pool was measured as the background, and the tumor-to-background ratio (TBRliver) was calculated. Results: In all malignant lesions, FAPI-TV and FAPI-TLA were higher in 68Ga-FAPI-04 PET/CT than in 18F-FDG. In the subgroup analysis, 68Ga-FAPI-04 had higher FAPI-TV and FAPI-TLA and lower SUVmax than 18F-FDG had in group A, including gynecological tumor, esophageal, and colorectal cancers. However, six semiquantitative parameters were higher in group B (the other malignant tumors). For the benign diseases, SUVmax, SUVmean, SUVpeak, and SULpeak were lower in 68Ga-FAPI-04 PET/CT than in 18F-FDG. 68Ga-FAPI-04 PET/CT showed a lower liver background and a higher TBRliver than 18F-FDG did. 68Ga-FAPI-04 PET/CT had higher accuracy, sensitivity, and specificity than 18F-FDG had. Conclusion: More accurate semiquantitative parameters and lower abdominal background in 68Ga-FAPI-04 PET/CT make it more competitive in the differential diagnosis of malignant and benign diseases than in 18F-FDG.

Molecular imprinting-based triple-emission ratiometric fluorescence sensor with aggregation-induced emission effect for visual detection of doxycycline

The development of high-performance sensors for doxycycline (DOX) detection is necessary because its residue accumulation will cause serious harm to human health and the environment. Here, a novel tri-emission ratiometric fluorescence sensor was proposed by using "post-mixing" strategy of different emissions fluorescence molecularly imprinted polymers with salicylamide as dummy template (DMIPs). BSA was chosen as assistant functional monomer, and also acted as sensitizers for the aggregation-induced emission (AIE) effect of DOX. The blue-emitting carbon dots and the red-emitting CdTe quantum dots were separately introduced into DMIPs as the response signals. Upon DOX recognition within 2 min, blue and red fluorescence of the tri-emission DMIPs sensor were quenched while green fluorescence of DOX was enhanced, resulting in a wide range of color variations observed over bluish violet-rosered-light pink-orange-yellow-green with a detection limit of 0.061 μM. The sensor possessed highly selective recognition and was successfully applied to detect DOX in complicated real samples. Moreover, with the fluorescent color collection and data processing, the smartphone-assisted visual detection of the sensors showed satisfied sensitivity with low detection limit. This work provides great potential applications for rapid and visual detection of antibiotics in complex substrates.

Extracellular volume-based scoring system for tracking tumor progression in pancreatic cancer patients receiving intraoperative radiotherapy

OBJECTIVES

To investigate the value of extracellular volume (ECV) derived from portal-venous phase (PVP) in predicting prognosis in locally advanced pancreatic cancer (LAPC) patients receiving intraoperative radiotherapy (IORT) with initial stable disease (SD) and to construct a risk-scoring system based on ECV and clinical-radiological features.

MATERIALS AND METHODS

One hundred and three patients with LAPC who received IORT demonstrating SD were enrolled and underwent multiphasic contrast-enhanced CT (CECT) before and after IORT. ECV maps were generated from unenhanced and PVP CT images. Clinical and CT imaging features were analyzed. The independent predictors of progression-free survival (PFS) determined by multivariate Cox regression model were used to construct the risk-scoring system. Time-dependent receiver operating characteristic (ROC) curve analysis and the Kaplan-Meier method were used to evaluate the predictive performance of the scoring system.

RESULTS

Multivariable analysis revealed that ECV, rim-enhancement, peripancreatic fat infiltration, and carbohydrate antigen 19-9 (CA19-9) response were significant predictors of PFS (all p < 0.05). Time-dependent ROC of the risk-scoring system showed a satisfactory predictive performance for disease progression with area under the curve (AUC) all above 0.70. High-risk patients (risk score ≥ 2) progress significantly faster than low-risk patients (risk score < 2) (p < 0.001).

CONCLUSION

ECV derived from PVP of conventional CECT was an independent predictor for progression in LAPC patients assessed as SD after IORT. The scoring system integrating ECV, radiological features, and CA19-9 response can be used as a practical tool for stratifying prognosis in these patients, assisting clinicians in developing an appropriate treatment approach.

CRITICAL RELEVANCE STATEMENT

The scoring system integrating ECV fraction, radiological features, and CA19-9 response can track tumor progression in patients with LAPC receiving IORT, aiding clinicians in choosing individual treatment strategies and improving their prognosis.

KEY POINTS

Predicting the progression of LAPC in patients receiving IORT is important. Our ECV-based scoring system can risk stratifying patients with initial SD. Appropriate prognostication can assist clinicians in developing appropriate treatment approaches.

Ratio of 4:1 between ZnGeAs2and MnAs phases in a single composite and its impact on the structure-driven magnetoresistance

A strong influence of the lattice degree of freedom on magnetoresistance (MR) under high pressure underlies the conception of 'structure-driven' magnetoresistance (SDMR). In most magnetic or topological materials, the suppression of MR with increasing pressure is a general trend, while for some magnetic composites the MR enhances and even shows unusual behavior as a consequence of structural transition. Here we investigated the SDMR in the composite material based on the ZnGeAs2semiconductor matrix and MnAs magnetic inclusions in a phase ratio of 4:1. At ambient pressure, its magnetic and transport properties are governed by MnAs inclusions, i.e. it shows a Curie temperatureTC≈ 320 K and metallic-like conductivity. Under high pressure, the low-field room temperature MR undergoes multiple changes in the pressure range up to 7.2 GPa. The structural transition in the ZnGeAs2matrix has been found at ∼6 GPa, slightly lower than in the pure ZnGeAs2(6.2 GPa). The huge SDMR as high as 85% at 6.8 GPa and 2.5 kOe, which contains both positive and negative MR components, is accompanied by a pressure-induced metallic-like-to-semiconductor-like transition and the enhanced ferromagnetic order of MnAs inclusions. This observation offers a competing mechanism between the robust extrinsic ferromagnetism and high-pressure electronic properties of ZnGeAs2.

Claudin 18.2 expression in digestive neuroendocrine neoplasms: a clinicopathological study

BACKGROUND

Claudin 18.2-targeted therapy has shown significant efficacy in treating claudin 18.2-positive cancers. However, limited systematic studies have investigated characteristics of claudin 18.2 expression in neuroendocrine neoplasms (NENs).

METHODS

Data and specimens from 403 cases of digestive NENs were retrospectively collected, and claudin 18.2 expression was detected using immunochemical staining.

RESULTS

Claudin 18.2 was positive in 19.6% (79/403) of the digestive NENs. The highest positive rate of claudin 18.2 was observed in gastric NENs (72/259, 27.8%), accounting for 91.1% (72/79) of all positive cases. The positivity rate was significantly higher in gastric NENs compared to pancreatic (2/78, 2.6%) or colorectal NENs (2/38, 5.3%; p < 0.05). For digestive NENs, claudin 18.2 positivity was significantly higher in neuroendocrine carcinomas (NECs) (37/144, 25.7%) than in neuroendocrine tumours (NETs; 14/160, 8.8%; p < 0.001), but no significant difference was found between gastric NECs (59/213, 27.7%) and gastric NETs (13/46, 28.3%; p > 0.05). The positivity was significantly higher in large-cell NECs (LCNECs; 28/79, 35.4%) and MiNEN (mixed neuroendocrine-non- neuroendocrine neoplasms)-LCNECs (23/66, 34.8%) compared to small-cell NECs (SCNECs; 9/65, 13.8%) and MiNEN-SCNECs (5/33, 15.2%; p < 0.05). Claudin 18.2 expression was more prevalent in gastric NENs than in pancreatic (12.5 ×; p = 0.001) and colorectal NENs (5.9 ×; p = 0.021). Claudin 18.2 staining was a useful method for identify the gastric origins of NETs, with a sensitivity of 28.3% and a specificity of 99.1%.

CONCLUSION

The expression characteristics of claudin 18.2 in NENs were characterized, which may provide a clinicopathological reference for targeted therapies in patients with NENs.

CT-based quantification of trachea shape to detect invasion by thyroid cancer

OBJECTIVE

This study aims to develop a CT-based method for quantifying tracheal shape and evaluating its ability to distinguish between cases with or without tracheal invasion in patients with thyroid carcinoma.

METHODS

A total of 116 quantitative shape features, including 56 geometric moments and 60 bounding shape features, were defined. The tracheal lumen was semi-automatically defined with a CT threshold of less than - 500 HU. Three contiguous slices with the 1st, 2nd, and 3rd smallest trachea lumen areas were contiguously selected, and the appropriate number of slices to be included was determined. Fifty-six patients with differentiated thyroid carcinoma (DTC) invading the trachea and 22 patients with DTC but without invasion were retrospectively included. A receiver operating characteristic (ROC) curve was applied to select the representative shape features and determine the optimal threshold.

RESULTS

23.3%, 25.9%, and 24.1% of the features displayed an area under the ROC curve (AUC) ≥ 0.800 when derived from 1, 2, and 3 slices, respectively. Calculating feature values from two slices with the 1st and 2nd smallest tracheal lumen area were considered appropriate. Six final features, including 3 geometric moments and 3 bounding shape features, were selected to determine the tracheal invasion status of DTC and displayed AUCs of 0.875-0.918, accuracies of 0.821-0.891, sensitivities of 0.813-0.893, and specificities of 0.818-0.932, outperforming the visual evaluation results.

CONCLUSIONS

Geometric moments and bounding shape features can quantify the tracheal shape and are reliable for identifying DTC tracheal invasion. The selected features quantified the extent of tracheal deformity in DTC patients with and without tracheal invasion.

CLINICAL RELEVANCE STATEMENT

Six geometric features provide a non-invasive, semi-automated evaluation of the tracheal invasion status of thyroid cancer.

KEY POINTS

• A novel method for quantifying tracheal shape using 56 geometric moments and 60 bounding shape features was developed. • Six features identify tracheal invasion by thyroid carcinoma. • The selected features quantified the extent of tracheal deformity in differentiated thyroid carcinoma patients with and without tracheal invasion.

Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS

PURPOSE

To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical cohort.

METHODS

Seventy participants with bladder cancer who underwent MRI between August 2022 and February 2023 with a protocol containing standard T2-weighted imaging (T2WIS), standard diffusion-weighted imaging (DWIS), fast T2WI with DLR (T2WIDL), and fast DWI with DLR (DWIDL) were enrolled in this prospective study. Imaging quality was evaluated by measuring signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and qualitative image quality scoring. Additionally, the apparent diffusion coefficient (ADC) of bladder lesions derived from DWIS and DWIDL was measured and VI-RADS scoring was performed. Paired t-test or paired Wilcoxon signed-rank test were performed to compare image quality score, SNR, CNR, and ADC between standard sequences and fast sequences with DLR. The diagnostic performance for VI-RADS was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

Compared to T2WIS and DWIS, T2WIDL and DWIDL reduced the acquisition time from 5:57 min to 3:13 min and showed significantly higher SNR, CNR, qualitative image quality score of overall image quality, image sharpness, and lesion conspicuity. There were no significant differences in ADC and AUC of VI-RADS between standard sequences and fast sequences with DLR.

CONCLUSIONS

The application of DLR to T2WI and DWI reduced examination time and significantly improved image quality, maintaining ADC and the diagnostic performance of VI-RADS for evaluating muscle invasion in bladder cancer.

[Application of optical coherence tomography in the evaluation of cervical lesions: a multicenter study]

Objective: To explore the value of optical coherence tomography (OCT) imaging system in evaluating cervical lesions in vivo. Methods: A total of 1 214 patients with cervical lesions were collected from January 2020 to December 2021 in the Third Affiliated Hospital of Zhengzhou University, Maternal and Chlid Heaith Hospital of Gushi County, Xinyang City, Henan Province, and Maternal and Chlid Heaith Hospital of Sui County, Shangqiu City, Henan Province. The age of the patients was (38.9±10.5) years (range: 16-77 years). All patients underwent in vivo cervical OCT examination and cervical biopsy pathology examination, and summarized the OCT image features of in vivo cervical lesions. Using the pathological diagnosis as the "gold standard", the accuracy, specificity, sensitivity, positive predictive value (PPV) and negative predictive value (NPV) of OCT image interpretation results were evaluated, as well as the consistency of OCT image diagnosis and pathological diagnosis. At the same time, the in vivo cervical OCT imaging system, as a newly developed screening tool, was compared with the traditional combined screening of human papillomavirus (HPV) and Thinprep cytologic test (TCT), to assess the screening effect. Results: By comparing the OCT images of the cervix in vivo with the corresponding HE images, the OCT image characteristics of the normal cervix and various types of cervical lesions in vivo were summarized. The accuracy, sensitivity, specificity, PPV and NPV of OCT image in the diagnosis of high-grade squamous intraepithelial lesion (HSIL) and above (HSIL+) were 93.4%, 88.5%, 95.0%, 85.0% and 96.2%, respectively. The accuracy, sensitivity, specificity, PPV and NPV of OCT for low-grade squamous intraepithelial lesion (LSIL) were 84.7%, 61.7%, 96.3%, 89.3% and 83.2%, respectively. The consistency between OCT image diagnosis and pathological diagnosis was strong (Kappa value was 0.701).The accuracy, sensitivity and specificity of OCT screening, HPV and TCT combined screening were 83.7% vs 64.9% (χ²=128.82, P<0.001), 77.8% vs 64.5% (χ²=39.01, P<0.001), 91.8% vs 65.4% (χ²=98.12, P<0.001), respectively. The differences were statistically significant. Conclusions: OCT imaging system has high sensitivity and specificity in the evaluation of cervical lesions in vivo, and has the characteristics of non-invasive, real-time and high efficiency. OCT examination is expected to become an effective method for the diagnosis of cervical lesions and cervical cancer screening.

MRI evaluation of vesical imaging reporting and data system for bladder cancer after neoadjuvant chemotherapy

BACKGROUND

The Vesical Imaging-Reporting and Data System (VI-RADS) has demonstrated effectiveness in predicting muscle invasion in bladder cancer before treatment. The urgent need currently is to evaluate the muscle invasion status after neoadjuvant chemotherapy (NAC) for bladder cancer. This study aims to ascertain the accuracy of VI-RADS in detecting muscle invasion post-NAC treatment and assess its diagnostic performance across readers with varying experience levels.

METHODS

In this retrospective study, patients with muscle-invasive bladder cancer who underwent magnetic resonance imaging (MRI) after NAC from September 2015 to September 2018 were included. VI-RADS scores were independently assessed by five radiologists, consisting of three experienced in bladder MRI and two inexperienced radiologists. Comparison of VI-RADS scores was made with postoperative histopathological diagnosis. Receiver operating characteristic curve analysis (ROC) was used for evaluating diagnostic performance, calculating sensitivity, specificity, and area under ROC (AUC)). Interobserver agreement was assessed using the weighted kappa statistic.

RESULTS

The final analysis included 46 patients (mean age: 61 years ± 9 [standard deviation]; age range: 39-70 years; 42 men). The pooled AUC for predicting muscle invasion was 0.945 (95% confidence interval (CI): 0.893-0.977) for experienced readers, and 0.910 (95% CI: 0.831-0.959) for inexperienced readers, and 0.932 (95% CI: 0.892-0.961) for all readers. At an optimal cut-off value ≥ 4, pooled sensitivity and specificity were 74.1% (range: 66.0-80.9%) and 94.1% (range: 88.6-97.7%) for experienced readers, and 63.9% (range: 59.6-68.1%) and 86.4% (range: 84.1-88.6%) for inexperienced readers. Interobserver agreement ranged from substantial to excellent between all readers (k = 0.79-0.92).

CONCLUSIONS

VI-RADS accurately assesses muscle invasion in bladder cancer patients after NAC and exhibits good diagnostic performance across readers with different experience levels.

Noninvasive Assessment of HER2 Expression Status in Gastric Cancer Using 18F-FDG Positron Emission Tomography/Computed Tomography-Based Radiomics: A Pilot Study

Purpose: Immunohistochemistry (IHC) is the main method to detect human epidermal growth factor receptor 2 (HER2) expression levels. However, IHC is invasive and cannot reflect HER2 expression status in real time. The aim of this study was to construct and verify three types of radiomics models based on 18F-fuorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging and to evaluate the predictive ability of these radiomics models for the expression status of HER2 in patients with gastric cancer (GC). Patients and Methods: A total of 118 patients with GC were enrolled in this study. 18F-FDG PET/CT imaging was performed prior to surgery. The LIFEx software package was applied to extract PET and CT radiomics features. The minimum absolute contraction and selection operator (least absolute shrinkage and selection operator [LASSO]) algorithm was used to select the best radiomics features. Three machine learning methods, logistic regression (LR), support vector machine (SVM), and random forest (RF) models, were constructed and verified. The Synthetic Minority Oversampling Technique (SMOTE) was applied to address data imbalance. Results: In the training and test sets, the area under the curve (AUC) values of the LR, SVM, and RF models were 0.809, 0.761, 0.861 and 0.628, 0.993, 0.717, respectively, and the Brier scores were 0.118, 0.214, and 0.143, respectively. Among the three models, the LR and RF models exhibited extremely good prediction performance. The AUC values of the three models significantly improved after SMOTE balanced the data. Conclusions: 18F-FDG PET/CT-based radiomics models, especially LR and RF models, demonstrate good performance in predicting HER2 expression status in patients with GC and can be used to preselect patients who may benefit from HER2-targeted therapy.

Reclassification of therapeutic response of unresectable hepatocellular carcinoma to anti-angiogenic therapy and immunotherapy using alpha RECIST

OBJECTIVES

To assess the therapeutic response of HCC to antiangiogenic therapy plus immunotherapy by integrating RECIST 1.1 and alpha-fetoprotein (AFP) response at the 6th week to predict overall survival (OS).

METHODS

This retrospective study included 150 and 214 patients with HCC who received combination therapy in training and validation cohorts. The medical images and AFP levels obtained at baseline and 6th week were collected. AFP response stratification: partial response (PR): AFP% ≥ 75% decline; stable disease (SD): AFP% < 75% decline and  ≤ 10% elevation; progressive disease (PD): AFP% > 10% elevation. The alpha-RECIST was: PR: RECIST 1.1-PR or AFP-PR; PD: AFP-PD or RECIST 1.1-PD and does not satisfy AFP-PR; SD: neither PR nor PD. OS was compared using Kaplan-Meier curves. The predictive ability of various criteria was evaluated using the concordance index and time-dependent area under the receiver-operating characteristic curve.

RESULTS

RECIST 1.1 achieved significant OS stratification (p = 0.020) for AFP < 20 ng/mL. For AFP ≥ 20 ng/mL, alpha-RECIST showed better performance than RECIST 1.1, mRECIST, and AFP response according to C-index (0.73 vs 0.66 vs 0.68 vs 0.69). The National Cancer Center (NCC) strategy utilized RECIST 1.1 for AFP < 20 ng/mL and alpha-RECIST for AFP ≥ 20 ng/mL and showed better performance than RECIST 1.1, mRECIST and AFP response according to C-index (0.73 vs 0.67 vs 0.69 vs 0.64). The performances of alpha-RECIST and NCC Strategy were confirmed in the validation cohort (C-index = 0.77 and 0.74).

CONCLUSIONS

The alpha-RECIST and NCC Strategy achieved better survival stratification in patients with HCC under combination therapy in the AFP ≥ 20 ng/mL group and the whole cohort compared to the RECIST 1.1, mRECIST, and AFP response.

CLINICAL TRANSLATIONAL RELEVANCE

The alpha-RECIST and National Cancer Center strategy are optimal methods for determining therapeutic response to a combination of anti-angiogenic therapy plus immunotherapy and facilitating accurate prognostic stratification for HCC in the AFP ≥ 20 ng/mL group and the whole cohort, which may help oncologists for early identification of responders and progression at 6 weeks and clinical decision-making.

KEY POINTS

• RECIST 1.1 is indicated for patients with baseline alpha-fetoprotein (AFP) < 20 ng/mL. • For patients with baseline AFP ≥ 20 ng/mL, integrating RECIST 1.1 and AFP response (alpha-RECIST) may aid in the early identification of survival benefits and progression definition prior to the administration of additional efficacious drugs. • The National Cancer Center strategy is an optimal stratified strategy for determining therapeutic response to a combination of anti-angiogenic therapy and immunotherapy for HCC based on baseline AFP levels.

[Characteristics of baseline viral load before antiretroviral therapy in newly reported HIV-infected patients in Tianjin, 2019-2022]

Objective: To understand the baseline viral load (VL) of newly reported HIV- infected patients before antiretroviral therapy and related factors in Tianjin. Methods: Data were obtained from the China Disease Control and Prevention Information System, and the study subjects were HIV-infected patients before the first antiretroviral therapy in Tianjin from 2019 to 2022, and the information about their socio-demographic characteristics, baseline CD4+T lymphocyte (CD4) counts before antiretroviral therapy and baseline VL test results were collected, the baseline high VL was defined as ≥100 000 copies/ml. The effect of different factors on viral load were analyzed. Software SPSS 24.0 was used for statistical analysis. Results: A total of 1 296 newly reported HIV-infected patients were included in the study, in whom 15.89% (206/1 296) had high baseline VL, and multifactorial logistic regression analysis showed that those with history of STD (aOR=1.45, 95%CI:1.00-2.08) were more likely to have high baseline VL. Compared with those with baseline CD4 counts <200 cells/μl, those with baseline CD4 counts 200-350 cells/μl (aOR=0.40, 95%CI: 0.27-0.57), 351-500 cells/μl (aOR=0.32, 95%CI: 0.20-0.49), and >500 cells/μl (aOR=0.30, 95%CI: 0.18-0.49) were less likely to have high baseline VL. Conclusions: The proportion of HIV-infected patients with high baseline VL before antiretroviral therapy was low in Tianjin during 2019-2022. History of STD and baseline CD4 counts <200 cells/μl were associated with high baseline VL in HIV-infected patients, to which close attention needs to be paid in AIDS prevention and control.

circNOX4 activates an inflammatory fibroblast niche to promote tumor growth and metastasis in NSCLC via FAP/IL-6 axis

BACKGROUND

Cancer-associated fibroblasts (CAFs) orchestrate a supportive niche that fuels cancer metastatic development in non-small cell lung cancer (NSCLC). Due to the heterogeneity and plasticity of CAFs, manipulating the activated phenotype of fibroblasts is a promising strategy for cancer therapy. However, the underlying mechanisms of fibroblast activation and phenotype switching that drive metastasis remain elusive.

METHODS

The clinical implications of fibroblast activation protein (FAP)-positive CAFs (FAP+CAFs) were evaluated based on tumor specimens from NSCLC patients and bioinformatic analysis of online databases. CAF-specific circular RNAs (circRNAs) were screened by circRNA microarrays of primary human CAFs and matched normal fibroblasts (NFs). Survival analyses were performed to assess the prognostic value of circNOX4 in NSCLC clinical samples. The biological effects of circNOX4 were investigated by gain- and loss-of-function experiments in vitro and in vivo. Fluorescence in situ hybridization, luciferase reporter assays, RNA immunoprecipitation, and miRNA rescue experiments were conducted to elucidate the underlying mechanisms of fibroblast activation. Cytokine antibody array, transwell coculture system, and enzyme-linked immunosorbent assay (ELISA) were performed to investigate the downstream effectors that promote cancer metastasis.

RESULTS

FAP+CAFs were significantly enriched in metastatic cancer samples, and their higher abundance was correlated with the worse overall survival in NSCLC patients. A novel CAF-specific circRNA, circNOX4 (hsa_circ_0023988), evoked the phenotypic transition from NFs into CAFs and promoted the migration and invasion of NSCLC in vitro and in vivo. Clinically, circNOX4 correlated with the poor prognosis of advanced NSCLC patients. Mechanistically, circNOX4 upregulated FAP by sponging miR-329-5p, which led to fibroblast activation. Furthermore, the circNOX4/miR-329-5p/FAP axis activated an inflammatory fibroblast niche by preferentially inducing interleukin-6 (IL-6) and eventually promoting NSCLC progression. Disruption of the intercellular circNOX4/IL-6 axis significantly suppressed tumor growth and metastatic colonization in vivo.

CONCLUSIONS

Our study reveals a role of the circRNA-induced fibroblast niche in tumor metastasis and highlights that targeting the circNOX4/FAP/IL-6 axis is a promising strategy for the intervention of NSCLC metastasis.

The GRAPHS-CRAFITY score: a novel efficacy predictive tool for unresectable hepatocellular carcinoma treated with immunotherapy

OBJECTIVES

To investigate MR features associated with prognosis of unresectable HCC receiving immunotherapy and establish a MR feature-based scoring system to predict efficacy of immunotherapy.

METHODS

This retrospective study included patients with unresectable HCC who received immunotherapy at 2 hospitals between August 2018 and February 2022. The last follow-up was October 2022. Clinical variables and MR features were assessed using univariate and multivariate Cox regression analyses. A new scoring system was constructed based on independent risk factors and the CRAFITY score consisting of AFP (≥ 100 ng/ml) and CRP (≥ 1 mg/dl). And the predictive performance of CRAFITY core and new score were compared by receiver-operating-characteristics curves (ROCs), area under ROCs (AUCs), and calibration curves.

RESULTS

A total of 166 patients (55.6 ± 10.4 years) were included in training cohort and 77 patients (55.4 ± 10.7 years) were included in validation cohort. There were significant differences in BCLC stage, max size, macrovascular invasion, intratumoral artery, and enhancing capsule between the 2 groups. Based on independent risk factors (gross GRowtH type, intratumoral fAt, enhancing tumor caPsule, Sex and CRAFITY score), a novel efficacy predictive tool named the GRAPHS-CRAFITY score was developed to predict OS. The OS was significantly different among the 3 groups according to GRAPHS-CRAFITY score (p value < 0.001). The GRAPHS-CRAFITY score could predict tumor response and disease control (p value < 0.001, p value < 0.001).

CONCLUSIONS

The GRAPHS-CRAFITY score is a reliable and easily applicable tool to predict the efficacy of unresectable HCC receiving immunotherapy.