Machine learning-based MRI radiomics for assessing the level of tumor infiltrating lymphocytes in oral tongue squamous cell carcinoma: a pilot study.

BACKGROUND: To investigate the value of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics in assessing tumor-infiltrating lymphocyte (TIL) levels in patients with oral tongue squamous cell carcinoma (OTSCC). METHODS: The study included 68 patients with pathologically diagnosed OTSCC (30 with high TILs and 38 with low TILs) who underwent pretreatment MRI. Based on the regions of interest encompassing the entire tumor, a total of 750 radiomics features were extracted from T2-weighted (T2WI) and contrast-enhanced T1-weighted (ceT1WI) imaging. To reduce dimensionality, reproducibility analysis by two radiologists and collinearity analysis were performed. The top six features were selected from each sequence alone, as well as their combination, using the minimum-redundancy maximum-relevance algorithm. Random forest, logistic regression, and support vector machine models were used to predict TIL levels in OTSCC, and 10-fold cross-validation was employed to assess the performance of the classifiers. RESULTS: Based on the features selected from each sequence alone, the ceT1WI models outperformed the T2WI models, with a maximum area under the curve (AUC) of 0.820 versus 0.754. When combining the two sequences, the optimal features consisted of one T2WI and five ceT1WI features, all of which exhibited significant differences between patients with low and high TILs (all P < 0.05). The logistic regression model constructed using these features demonstrated the best predictive performance, with an AUC of 0.846 and an accuracy of 80.9%. CONCLUSIONS: ML-based T2WI and ceT1WI radiomics can serve as valuable tools for determining the level of TILs in patients with OTSCC.

Machine learning based on magnetic resonance imaging and clinical parameters helps predict mesenchymal-epithelial transition factor expression in oral tongue squamous cell carcinoma: a pilot study.

OBJECTIVES: This study aimed to develop machine learning models to predict phosphorylated mesenchymal-epithelial transition factor (p-MET) expression in oral tongue squamous cell carcinoma (OTSCC) using magnetic resonance imaging (MRI)-derived texture features and clinical features. METHODS: Thirty-four patients with OTSCC were retrospectively collected. Texture features were derived from preoperative MR images, including T2WI, apparent diffusion coefficient mapping, and contrast-enhanced (ce)-T1WI. Dimension reduction was performed consecutively with reproducibility analysis and an information gain algorithm. Five machine learning methods-AdaBoost, logistic regression (LR), naïve Bayes (NB), random forest (RF), and support vector machine (SVM)-were adopted to create models predicting p-MET expression. Their performance was assessed with fivefold cross-validation. RESULTS: In total, 22 and 12 cases showed low and high p-MET expression, respectively. After dimension reduction, 3 texture features (ADC-Minimum, ce-T1WI-Imc2, and ce-T1WI-DependenceVariance) and 2 clinical features (depth of invasion [DOI] and T-stage) were selected with good reproducibility and best correlation with p-MET expression levels. The RF model yielded the best overall performance, correctly classifying p-MET expression status in 87.5% of OTSCCs with an area under the receiver operating characteristic curve of 0.875. CONCLUSION: Differences in p-MET expression in OTSCCs can be noninvasively reflected in MRI-based texture features and clinical parameters. Machine learning can potentially predict biomarker expression levels, such as MET, in patients with OTSCC.

A Targeted Multi-Crystalline Manganese Oxide as a Tumor-Selective Nano-Sized MRI Contrast Agent for Early and Accurate Diagnosis of Tumors.

Introduction: Magnetic resonance imaging (MRI) is an important tool for the accurate diagnosis of malignant tumors in clinical settings. However, the lack of tumor-specific MRI contrast agents limits diagnostic accuracy. Methods: Herein, we developed αv integrin receptor-targeting multi-crystalline manganese oxide (MCMO) as a novel MRI contrast agent for accurate diagnosis of tumors by coupling iRGD cyclopeptide PEGylation polymer onto the surface of MCMO (iRGD-pMCMO). Results: The MCMO consisted of numerous small crystals and exhibited an oval structure of 200 nm in size. The iRGD-pMCMO actively recognizes tumor cells and effectively accumulates at the tumor site, consequently releasing abundant Mn2+ ions in a weakly acidic and high-GSH-expressing tumor microenvironment. Subsequently, Mn2+ ions interact with cellular GSH to form Mn-GSH chelates, enabling efficient T1-weighted MR contrast imaging. In vivo experiments indicated that iRGD-pMCMO significantly improved T1-weighted images, achieving an accurate diagnosis of subcutaneous and orthotopic tumors. The results verified that the T1 contrast effect of iRGD-pMCMO was closely associated with the expression of GSH in tumor cells. Conclusion: Altogether, the novel tumor-targeting, highly sensitive MRI contrast agent developed in this study can improve the accuracy of MRI for tumor diagnosis.

Evaluating the capacity of heavy metal pollution enrichment in green vegetation in the industrial zone, Northwest China.

It focused on heavy metal pollution of green vegetation in Tuokexun County, Xinjiang Northwest China's suburban industrial area, using inductively coupled plasma emission spectrometer to analyze the samples for Mn, Ni, Zn, Cd, Hg, Pb, As, Cu, and Cr contents. The soil's heavy metal content in the study area indicated a minor level of pollution overall (P = 1.77), with the most severe contamination being Hg, which is more likely to be caused by human activities. Heavy metal elements in trees have the most stable composition in comparison to grass and shrubs, with varying concentrations across different vegetation. The concentrations of Mn, Cd and Hg were highest in the Haloxylon ammodendron, Ni in Morus alba, Pb, As and Cu in Nitraria tangutorums, and Cr in Phragmites australis. Heavy metal restoration is most effectively performed by shrubs, and there are disparities in heavy metal enrichment among various vegetation. No significant difference was found in heavy metal enrichment between the aboveground and underground parts of vegetation. Based on the average of the membership function, Tamarix exhibits the strongest ability to enrich heavy metals, while Nitraria tangutorum comes in second, and Cynanchum chinense R.Br. is the least effective among all plant species. Morus alba is recommended as the primary planting species in the area. Nitraria tangutorum and Haloxylon ammodendron have good potential for Cd and As restoration and can be used as supporting vegetation.

Differentiation of geniculate ganglion venous malformation from schwannoma: dynamic T1-weighted imaging provides unique diagnostic value.

OBJECTIVE: To distinguish geniculate ganglion venous malformation (GGVM) from schwannoma (GGS) by using high-resolution CT (HRCT), routine MRI, and dynamic T1-weighted imaging (T1WI) characteristics. METHODS: Surgically confirmed GGVMs and GGSs between 2016 and 2021 were retrospectively included. Preoperative HRCT, routine MR, and dynamic T1WI were performed on all patients. Clinical data, imaging characteristics including lesion size, involvement of facial nerve (FN), signal intensity, enhancement pattern on dynamic T1WI, and bone destruction on HRCT were evaluated. Logistic regression model was developed to identify independent factors for GGVMs, and the diagnostic performance was accessed by receiving operative curve (ROC) analysis. Histological characteristics were explored for both GGVMs and GGSs. RESULTS: Twenty GGVMs and 23 GGSs with mean age of 31 were included. On dynamic T1WI, 18 GGVMs (18/20) showed "pattern A" enhancement (a progressive filling enhancement), while all 23 GGSs showed "pattern B" enhancement (a gradual whole-lesion enhancement) (p < 0.001). Thirteen GGVMs (13/20) showed the "honeycomb" sign whereas all GGS (23/23) showed extensive bone changes on HRCT (p < 0.001). Lesion size, involvement of FN segment, signal intensity on non-contrast T1WI and T2-weighted imaging (T2WI), and homogeneity on enhanced T1WI were obviously differed between two lesions (p < 0.001, p = 0.002, p < 0.001, p = 0.01, p = 0.02, respectively). Regression model showed the "honeycomb" sign and "pattern A" enhancement were independent risk factors. Histologically, GGVM was characterized by interwoven dilated and tortuous veins, while GGS was characterized by abundant spindle cells with dense arterioles or capillaries. CONCLUSIONS: The "honeycomb" sign on HRCT and "pattern A" enhancement on dynamic T1WI are the most promising imaging characteristics for differentiating GGVM from GGS. CLINICAL RELEVANCE STATEMENT: The characteristic sign and enhancement pattern on HRCT and dynamic T1-weighted imaging allow preoperative differentiation of geniculate ganglion venous malformation and schwannoma feasible, which will improve clinical management and benefit patient prognosis. KEY POINTS: • The "honeycomb" sign on HRCT is a reliable finding to differentiate GGVM from GGS. • GGVM typically shows "pattern A" enhancement (focal enhancement of the tumor on early dynamic T1WI, followed by progressive contrast filling of the tumor in the delayed phase), while "pattern B" enhancement (gradual heterogeneous or homogeneous enhancement of the whole lesion) is observed in GGS on dynamic T1WI.

A c-MET-Targeted Topical Fluorescent Probe cMBP-ICG Improves Oral Squamous Cell Carcinoma Detection in Humans.

INTRODUCTION: The postoperative survival of oral squamous cell carcinoma (SCC) relies on precise detection and complete resection of original tumors. The mucosal extension of the tumor is evaluated visually during surgery, but small and flat foci are difficult to detect. Real-time fluorescence imaging may improve detection of tumor margins. MATERIALS AND METHODS: In the current study, a peptide-based near-infrared (NIR) fluorescence dye, c-MET-binding peptide-indocyanine green (cMBP-ICG), which specifically targets tumor via c-MET binding, was synthetized. A prospective pilot clinical trial then was conducted with oral SCC patients and intraoperatively to assess the feasibility of cMBP-ICG used to detect tumors margins. Fluorescence was histologically correlated to determine sensitivity and specificity. RESULTS: The immunohistochemistry (IHC) results demonstrated increased c-Met expression in oral SCC compared with normal mucosa. Tumor-to-background ratios ranged from 2.71 ± 0.7 to 3.11 ± 1.2 in different concentration groups. From 10 patients with oral SCC, 60 specimens were collected from tumor margins. The sensitivity and specificity of discriminative value derived from cMBP-ICG application in humans were respectively 100% and 75%. CONCLUSIONS: Topical application of cMBP-ICG is feasible and safe for optimizing intraoperative visualization and tumor margin detection in oral SCC patients, which could clinically increase the probability of complete resections and improve oncologic outcomes.

The combination of T2-mapping value of lacrimal gland and clinical indicators can improve the stage prediction of Graves' ophthalmopathy compared to clinical activity scores.

PURPOSE: To explore radiological changes of the lacrimal gland (LG) in Graves' ophthalmopathy (GO) and whether a combination of MRI parameters and clinical indicators would be more effective in predicting individual clinical manifestation of GO compared to clinical activity scores (CAS) assessment. METHODS: A total of 28 patients with GO (56 eyes) and 14 healthy controls (HCs) (28 eyes) were enrolled between July 2020 and July 2021. Patients were classified into the active GO group (CAS ≥ 3) and the inactive GO group (CAS < 3). MRI data and clinical data of LG were collected. The diagnostic performance of MRI parameters and models was assessed by receiver operating characteristic curve analysis. Logistic regression predictive models for staging GO were compared. RESULTS: LG in GO groups had significantly higher Ktrans, Ve, IAUC, ADC, and T2-mapping values (p = 0.006, p < 0.001, p < 0.001, p = 0.048, and p = 0.001, respectively), and significant lower Kep and Vp values (p < 0.001 and p < 0.001 respectively). There were statistically significant differences in T2-mapping value (p < 0.001), the proportion of mild or no obvious redness of conjunctiva (p < 0.001), and the proportion of swelling of caruncle or plica (p < 0.001) between inactive and active groups. In MRI based logistic regression model, the T2-mapping value was an independent risk factor (AUC = 0.832). When combining MRI and clinical indicators, T2-mapping value and age resulted in independent risk factors (AUC = 0.928). Swelling of eyelids, redness of the conjunctiva, swelling of the conjunctiva, swelling of caruncle or plica, and spontaneous retrobulbar pain could be replaced by other objective indicators (AUC = 0.937, 0.852, 0.876, 0.896, and 0.891, respectively). CONCLUSION: There were significant differences in MRI quantitative parameters of LG between HCs and GO patients. The combination of the T2-mapping value of LG and clinical indicators improved the stage prediction of Graves' ophthalmopathy compared to CAS, thus providing a new idea for enhancing the objectification level of GO data collection.

Management of Complications in 257 Cases of Breast Augmentation with Polyacrylamide Hydrogel, using Two Different Strategies: A Retrospective Study.

BACKGROUND: Polyacrylamide hydrogel (PAAG) has been used globally for breast augmentation, leading to long-term clinical complications. However, whether the infiltrated fibrotic capsule should be removed with PAAG to alleviate the complications remains unclear. This study aimed to ascertain different causes of complications and proper management strategies for PAAG removal in augmented breasts. METHODS: From July 2015 to December 2019, patients who underwent breast augmentation with PAAG and in whom surgical intervention was undertaken for PAAG-associated adverse events at Shanghai Ninth People's Hospital were retrospectively reviewed. Patients were categorized into two groups according to whether the fibrotic capsule was removed (RFC) or not (NRFC). Aesthetic outcomes, PAAG residues, and adverse events were evaluated post-operatively to assess whether important issues pertaining to these arose following fibrotic capsule removal. Tissue histology and PAAG degradation analysis were implemented to investigate immune response, degradability, and toxicity of PAAG. RESULTS: Altogether, 257 patients (88 RFC and 169 NRFC patients) were enrolled. 73.4% and 79.5% of the RFC and NRFC groups showed fairly good outcomes, with no significant difference, respectively. (X2 = 0.0804, p = 0.79) Significant differences were found between two surgical techniques upon patient satisfaction, respectively. (X2 = 3.529; p = 0.0301). Predictor of poor outcomes identified scar (OR, 4.555, p = 0.0019) and PAAG residue (OR, 5.379, p = 0.0003). Predictor of patient satisfaction identified post-operative outcomes (OR, 3.797; 95% CI, 1.860-8.923; p = 0.0002) and surgical technique (NRFC) (OR, 2.519; 95% CI, 1.449-4.434; p = 0.0008). CONCLUSIONS: Both treatment strategies showed good results in our study. Removal of the fibrotic capsule from infiltration of PAAG largely depends on the individual psychological condition, aesthetic expectations, complications, and magnetic resonance imaging results. While PAAG does not degrade in the host's body over time, it may elicit immune reactions and chronic inflammation in the long term. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine Ratings, please refer to Table of Contents or online Instructions to Authors www.springer.com/00266.

Correlation Between Body Mass Index and Anterolateral Thigh Flap Thickness: A Retrospective Study From a Single Center in China.

Background: During repair of oral and maxillofacial soft tissue defects, organ function is largely related to the amount of thickness of the flap. However, there are few studies on the influencing factors of the thickness of the flap. In this retrospective study, we aim to explore the correlation between body mass index (BMI) and anterolateral thigh (ALT) flap thickness by computed tomography (CT) and ultrasound and provide guidance for evaluating the ALT flap thickness before surgery. Methods: We selected three points A, B, and C on ALT flap and two skilled clinicians measured the thickness of these points. Age and gender as covariates and evaluated by the Chi-square analysis. Inter-group differences between the two BMI groups were examined by the student t test. Intra-group differences within each BMI group were tested by ANOVA. Linear regression analysis was performed to examine the relationship between BMI and ALT flap thickness. Results: One hundred sixty patients measured by CT were included in this study, and the ALT flap thickness measured by CT were 8.96 mm and 11.00 mm (P < 0.0001, t test) at point B in groups with BMI<24.0 and BMI≥24.0, respectively. The thicknesses at points A, B, and C were significantly correlated with the BMI (P < 0.001, correlation analysis, r = 0.462, 0.372, and 0.349 at the points A, B, and C, retrospectively, Pearson test). Conclusion: There was a significant correlation between the ALT flap thickness and BMI. A higher BMI was correlated with a thicker ALT flap.

Determination of Cervical Lymph Nodes Metastasis and Extra Nodal Extension Status by Quantitative Assessment of Border Irregularity and Apparent Diffusion Coefficient in Patients With Tongue Squamous Cell Carcinoma.

OBJECTIVE: The objective of this study was to determine the diagnostic value of quantitative border irregularity assessment and apparent diffusion coefficient (ADC) in patients with squamous cell carcinoma of the tongue (SCCT). METHODS: Cervical lymph nodes (n = 192) from 63 patients with SCCT were examined preoperatively by magnetic resonance imaging, including routine head and neck sequences, dynamic contrast-enhanced magnetic resonance imaging, diffusion-weighted imaging, ADC, surface regularity (SR), and visually assessed variables, and evaluated pathologically after surgery. RESULTS: Necrosis, lymphatic hilum, unclear margin, higher SR, long to short axis ratio, and ADC were associated with metastasis in cervical lymph nodes (M-cLNs) and extranodal extension (ENE), and thickened nodal rim with ENE alone. Apparent diffusion coefficient, SR, unclear margin, and visible necrosis were strongly associated with M-cLN, whereas SR, unclear margin, and visible necrosis were associated with ENE status on logistic regression analysis. CONCLUSIONS: Quantitative SR and ADC data greatly improved diagnosis of M-cLNs and ENE, relative to visible variables alone in patients with SCCT.

Multi-parametric effect in predicting tumor histological grade by using susceptibility weighted magnetic resonance imaging in tongue squamous cell carcinoma.

BACKGROUND: Susceptibility weighted imaging (SWI) is helpful for depicting hemorrhage, calcification, and increased vascularity in some neoplasms, which may reflect tumor grade. In this study, we aimed to apply SWI in patients with oral tongue squamous cell carcinomas (OTSCCs) and relate multi-parametric effect to tumor histological grade prediction. METHODS: Preoperative MR examinations were performed on a 1 .5T MRI scanner with T1-, T2- and contrast-enhanced (CE) T1-weighted imaging. In addition to routine head and neck MRI sequences, SWI was performed. Tumor thickness and volume were measured. Intratumoral susceptibility signal intensities (ITSSs), ITSS score and ITSS ratio on SWI were evaluated and recorded. Subjects were sub-grouped into low- and high-grade according to the histological findings post operation. Parameters such as tumor thickness, tumor volume and three ITSS related parameters were compared between low- and high-grade groups. ROC analysis was performed on above parameters to access the capability in predicting tumor histological grade. Different multi-parametric models were run to access multi-parametric combination effect. RESULTS: Thirty patients with OTSCC were finally included in the study. Twenty of them were categorized as low-grade SCC and the other ten subjects were high-grade SCC according to the pathologic findings. No significant difference was seen for tumor thickness or tumor volume between two sub-groups. ITSSs were seen in 23/30 patients. Significant difference of ITSS scores between low- and high-grade OTSCCs was observed, with mean value of 0.95 ± 0.83 and 1.70 ± 0.95, respectively. Univariate ROC analysis demonstrated ITSSs, ITSS score and ITSS ratio were valuable parameters for predicting tumor histological grade and ITSSs was superior to the other two parameters, with an area under ROC curve of 0.790. Multi-parametric model using combination of ITSSs and tumor thickness would greatly improve the predictive capability in comparison with a univariate approach, yielding the area under ROC curve of 0.84(0.69,0.99). On contrast-enhanced SWI (CE-SWI), ITSSs were shown more clearly delineated in comparison with non-contrast enhanced SWI. CONCLUSIONS: In conclusion, SWI was superior in depiction of internal characteristics of OTSCCs, which would potentially provide more diagnostic information. Multi-parametric model using combination of ITSSs and tumor thickness would be valuable in predicting tumor histological grade.

The value of combining conventional, diffusion-weighted and dynamic contrast-enhanced MR imaging for the diagnosis of parotid gland tumours.

OBJECTIVES: The aim of this study was to determine the value of combining conventional MRI, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE)-MRI in diagnosing solid neoplasms in the parotid gland. METHODS: A total of 148 subjects (101 subjects with benign and 47 subjects with malignant tumours) were evaluated with conventional MRI, DWI and DCE-MRI prior to surgery and pathologic verification. The items observed with conventional MRI included the shape, capsule and signal intensity of parotid masses. The apparent diffusion coefficient (ADC) was calculated from DWI that was obtained with a b-factor of 0 and 1000 s mm-2. A time-intensity curve (TIC) was obtained from DCE-MRI. RESULTS: There were significant differences (p < 0.01) in the shape, capsule, ADC and TIC between benign and malignant parotid tumours. Irregular neoplasms without a capsule, ADC <1.12 × 10-3 mm2 s-1 and a plateau enhancement pattern were valuable parameters for predicting malignant neoplasms. A combination of all of these parameters yielded sensitivity, specificity, accuracy, positive-predictive value and negative-predictive value of 85.1%, 94.1%, 91.2%, 87.0% and 93.1%, respectively. CONCLUSIONS: A combined analysis using conventional MRI, DWI and DCE-MRI is helpful in distinguishing benign from malignant tumours in the parotid gland.