Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer.

Objective: To investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spread ≤ 5 mm). Methods: This retrospective study enrolled 303 patients with low T-staging rectal cancer (training cohort, n = 213, testing cohort n = 90). A total of 960 radiomics features were extracted from T2WI. Minimum redundancy and maximum relevance (mRMR) and support vector machine were performed to select the best performed radiomics features for predicting LN metastasis. Multivariate logistic regression analysis was then used to construct the clinical and clinical-radiomics combined models. The model performance for predicting LN metastasis was assessed by receiver operator characteristic curve (ROC) and clinical utility implementing a nomogram and decision curve analysis (DCA). The predictive performance for LN metastasis was also compared between the combined model and human readers (2 seniors). Results: Fourteen radiomics features and 2 clinical characteristics were selected for predicting LN metastasis. In the testing cohort, a higher positive predictive value of 75.9% for the combined model was achieved than those of the clinical model (44.8%) and two readers (reader 1: 54.9%, reader 2: 56.3%) in identifying LN metastasis. The interobserver agreement between 2 readers was moderate with a kappa value of 0.416. A clinical-radiomics nomogram and decision curve analysis demonstrated that the combined model was clinically useful. Conclusion: T2WI-based radiomics combined with clinical data could improve the efficacy in noninvasively evaluating LN metastasis for the low T-staging rectal cancer and aid in tailoring treatment strategies.

MRI Radiomics Signature of Pediatric Medulloblastoma Improves Risk Stratification Beyond Clinical and Conventional MR Imaging Features.

BACKGROUND: Prognostic evaluation is important for personalized treatment in children with medulloblastoma (MB). Limited data are available for risk stratification using a radiomics-based model. PURPOSE: To evaluate the incremental value of an MRI radiomics signature in stratifying the risk of pediatric MB in terms of overall survival (OS). STUDY TYPE: Retrospective. SUBJECTS: A total of 111 children (mean age 5.82 years) with pathologically confirmed MB divided into training and validation cohorts (77 and 34 children, respectively). FIELD STRENGTH/SEQUENCE: A 3 T, contrast-enhanced T1-weighted imaging with inversion recovery. ASSESSMENT: The study endpoint was OS defined as the time between the preoperative MRI study and death or last follow-up. The radiomics signature model and a clinical-MRI model were developed for personalized OS prediction. An integrative model, which combined the radiomics signature and clinical-MRI features, was also built using multivariable Cox regression model. The performance of the three models was evaluated with the C-index. The performance of integrative model was assessed by calibration curve and decision curve analysis (DCA). STATISTICAL TESTS: Independent T-test, Mann-Whitney U test, Fisher's exact tests or chi-square test, logistic regression analysis, Kaplan-Meier survival analysis, C-index, intraclass correlation coefficients (ICC). P < 0.05 was considered statistically significant. RESULTS: The media OS was 2.83 years (3.87 ± 1.85 years). Two clinical and one conventional MR imaging features (remnant, adjuvant treatment, and peritumoral edema) were selected for clinical-MRI model building. The integrative model evaluated OS (C-index 0.823) better than either the radiomics signature (C-index 0.702) or the clinical-MRI model (C-index 0.771). And it also showed good performance in the validation cohort (C-indices: 0.786, 0.756, 0.721), which was validated by the good calibration (P > 0.05) and more benefit. DATA CONCLUSIONS: This study demonstrated that the integrative model, which combined radiomics signature, clinical, and conventional MRI features, showed best performance in OS evaluation for children with MB. The radiomics signature may confer incremental value over clinical-MRI features. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer.

BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatment response in rectal cancer, but the role of MRI-based DL in evaluating Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation remains unclear. PURPOSE: To develop a DL method based on T2-weighted imaging (T2WI) and clinical factors for noninvasively evaluating KRAS mutation in rectal cancer. STUDY TYPE: Retrospective. SUBJECTS: A total of 376 patients (108 women [28.7%]) with histopathology-confirmed rectal adenocarcinoma and KRAS mutation status. FIELD STRENGTH/SEQUENCE: A 3 T, turbo spin echo T2WI and single-shot echo-planar diffusion-weighted imaging (b = 0, 1000 sec/mm2 ). ASSESSMENT: A clinical model was constructed with clinical factors (age, gender, carcinoembryonic antigen level, and carbohydrate antigen 199 level) and MRI features (tumor length, tumor location, tumor stage, lymph node stage, and extramural vascular invasion), and two DL models based on modified MobileNetV2 architecture were evaluated for diagnosing KRAS mutation based on T2WI alone (image model) or both T2WI and clinical factors (combined model). The clinical usefulness of these models was evaluated through calibration analysis and decision curve analysis (DCA). STATISTICAL TESTS: Mann-Whitney U test, Chi-squared test, Fisher's exact test, logistic regression analysis, receiver operating characteristic curve (ROC), Delong's test, Hosmer-Lemeshow test, interclass correlation coefficients, and Fleiss kappa coefficients (P < 0.05 was considered statistically significant). RESULTS: All the nine clinical-MRI characteristics were included for clinical model development. The clinical model, image model, and combined model in the testing cohort demonstrated good calibration and achieved areas under the curve (AUCs) of 0.668, 0.765, and 0.841, respectively. The combined model showed improved performance compared to the clinical model and image model in two cohorts. DCA confirmed the higher net benefit of the combined model than the other two models when the threshold probability is between 0.05 and 0.85. DATA CONCLUSION: The proposed combined DL model incorporating T2WI and clinical factors may show good diagnostic performance. Thus, it could potentially serve as a supplementary approach for noninvasively evaluating KRAS mutation in rectal cancer. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Clinical and magnetic resonance imaging features of 14 patients with trilateral retinoblastoma.

BACKGROUND: Our study aimed to comprehensively investigate the age of onset, magnetic resonance imaging (MRI) features, and prognosis of children with trilateral retinoblastoma (TRB). METHODS: We included 14 patients with TRB diagnosed or followed up in our hospital. The age of onset and MRI features of the intraocular tumor and intracranial lesions were evaluated. A follow-up study was also conducted. RESULTS: A total of 11 participants were diagnosed with concurrent TRB at the age of 11.1±7.4 months, and 3 participants had late-onset TRB at age 37±19.1 months. The incidence of TRB with unilateral eye involvement was 7.1% (1/14). The intraocular tumors showed intense enhancement in contrast-enhanced T1-weighted images (WI) and significant diffusion restriction in diffusion WI (DWI) with an apparent diffusion coefficient (ADC) of (0.619±0.22)×10-3 mm2/s. The intracranial lesions showed similar DWI aspects with an ADC value of (0.680±0.206)×10-3 mm2/s. Therapeutically, 8 participants had a period of intraocular tumor stabilization and significant intracranial lesion volume reduction after chemotherapy, and 6 participants had given up treatment. Only 2 participants who simultaneously received high-dose chemotherapy and autologous hematopoietic stem cell rescue were still alive with no recurrence at 24 and 54 months of follow-up. The 1-, 2-, and 3-year overall survival (OS) rates were 80%, 18.75%, and 12.5%, respectively. CONCLUSIONS: Patients with unilateral or bilateral RB can develop TRB. The intraocular and intracranial tumors showed slightly different ADC values. High-dose chemotherapy, combined with stem cell rescue can significantly improve survival. A long term and scheduled follow-up before 60 months of age is necessary for screening later-onset TRB patients.

Pure dysgerminoma of the ovary: CT and MRI features with pathological correlation in 13 tumors.

BACKGROUND: To investigate the spectrum of CT and MRI findings of dysgerminoma of the ovary. METHODS: CT and MRI imaging of 12 patients with 13 histologically proven dysgerminomas of the ovary were retrospectively reviewed. Patients, ages ranged from 6 ~ 27 years (mean, 17.2 years). Two observers evaluated the following CT and MRI features of the tumor by consensus: (i) location, shape, and size; (ii) attenuation, T2 signal intensity, and ADC value; (iii) patterns of contrast enhancement; (iv) presence of fibrovascular septa; (v) presence of necrosis, hemorrhage, and calcification; (vi) presence of "ovarian vascular pedicle" sign. We also noted the extent or stage of the tumors. RESULTS: 75% lesions arised in the right ovary. Bilateral ovaries were involved in one case. Tumors displayed as a purely or predominantly solid mass (mean size, 17.0 ± 7.8 cm). Ten tumors were shaped multilobulated. The mean ADC value of lesions was 0.830 ± 0.154 × 10- 3 mm2/s. Characteristic fibrovascular septa were observed in all lesions. Among them, classic septa were present in 69% lesions. They were thin, hypointense on T2WI with a linear intense enhancement indicating the blood vessels in septa. Due to the stromal edema, fibrovascular septa may become thick even amorphous in shape, hyperintense on T2WI and even low attenuation on CT with a slight enhancement except for a bright blood vessel on the edge. Massive necrosis was observed only in one lesion. Calcification was present in 3 of the 5 tumors on CT. "Ovarian vascular pedicle" sign was present in 12 lesions. Lymphadenopathy, retroperitoneal spread, and distant metastases combined with an implantation in Douglas' cul-de-sac were present in one patient respectively. CONCLUSION: On CT and MR images, ovarian dysgerminoma often appears as a large solid mass. The edematous condition of characteristic fibrovascular septa can be well displayed by imaging which then can guide the radiologists to make an accurate diagnosis. Calcifications often occur in the tumor. Nonspecific low ADC value and "ovarian vascular pedicle" sign may narrow the differential diagnosis.

MRI radiomics analysis for predicting preoperative synchronous distant metastasis in patients with rectal cancer.

OBJECTIVES: To investigate the value of MRI radiomics based on T2-weighted (T2W) images in predicting preoperative synchronous distant metastasis (SDM) in patients with rectal cancer. METHODS: This retrospective study enrolled 177 patients with histopathology-confirmed rectal adenocarcinoma (123 patients in the training cohort and 54 in the validation cohort). A total of 385 radiomics features were extracted from pretreatment T2W images. Five steps, including univariate statistical tests and a random forest algorithm, were performed to select the best preforming features for predicting SDM. Multivariate logistic regression analysis was conducted to build the clinical and clinical-radiomics combined models in the training cohort. The predictive performance was validated by receiver operating characteristics curve (ROC) analysis and clinical utility implementing a nomogram and decision curve analysis. RESULTS: Fifty-nine patients (33.3%) were confirmed to have SDM. Six radiomics features and four clinical characteristics were selected for predicting SDM. The clinical-radiomics combined model performed better than the clinical model in both the training and validation datasets. A threshold of 0.44 yielded an area under the ROC (AUC) value of 0.827 (95% confidence interval (CI), 0.6963-0.9580), a sensitivity of 72.2%, a specificity of 94.4%, and an accuracy of 87.0% in the validation cohort for the combined model. A clinical-radiomics nomogram and decision curve analysis confirmed the clinical utility of the combined model. CONCLUSIONS: Our proposed clinical-radiomics combined model could be utilized as a noninvasive biomarker for identifying patients at high risk of SDM, which could aid in tailoring treatment strategies. KEY POINTS: • T2WI-based radiomics analysis helps predict synchronous distant metastasis (SDM) of rectal cancer. • The clinical-radiomics combined model could be utilized as a noninvasive biomarker for predicting SDM. • Personalized treatment can be carried out with greater confidence based on the risk stratification for SDM in rectal cancer.

The value of MRI in evaluating the efficacy and complications with the treatment of intra-arterial chemotherapy for retinoblastoma.

Retinoblastoma is the most common intraocular malignant tumor of childhood. Intra-arterial chemotherapy (IAC) is a recently popularized technique used for the treatment of retinoblastoma, to decrease mortality, increase preservation of the eye, and prevent blindness. Along with the extensive use of IAC, it is important to apply noninvasive examination methods to assess the activity of the tumor and the risk factors for disease dissemination without histopathological confirmation. There are few studies that have assessed the value of magnetic resonance imaging (MRI) in evaluating the efficacy and complications of IAC for retinoblastoma. We retrospectively analyzed the MRI features of 60 patients with unilateral retinoblastoma given the primary treatment of IAC from January 2014 to February 2016 in our hospital. Our study showed that MRI could well assess the decreased activity of the tumor after IAC, presenting with diminished tumor size, increased apparent diffusion coefficient (ADC) values (from 0.94 ± 0.24 × 10-3 mm2/s to 2.24 ± 0.40 × 10-3 mm2/s), and a reduced degree of enhancement of the tumor. Our study also showed that MRI can monitor the risk factors of abnormal enhancement of the postlaminar optic nerve, to avoid unnecessary enucleation. Meanwhile, the results showed that the main late complications after IAC included affected eyeball volume reduction, subretinal hemorrhage, vitreous hemorrhage, vitreous opacity, cataractous len, and choroidal vascular ischemia.