Multiparametric MRI and Radiomics for the Prediction of HER2-Zero, -Low, and -Positive Breast Cancers.

Background Half of breast cancers exhibit low expression levels of human epidermal growth factor receptor 2 (HER2) and can be targeted by new antibody-drug conjugates. The imaging differences between HER2-zero (immunohistochemistry [IHC] score of 0), HER2-low (IHC score of 1+ or 2+ with negative findings at fluorescence in situ hybridization [FISH]), and HER2-positive (IHC score of 2+ with positive findings at FISH or IHC score of 3+) breast cancers were unknown. Purpose To assess whether multiparametric dynamic contrast-enhanced MRI-based radiomic features can help distinguish HER2 expressions in breast cancer. Materials and Methods This study included women with breast cancer who underwent MRI at two different centers between December 2020 and December 2022. Tumor segmentation and radiomic feature extraction were performed on T2-weighted and dynamic contrast-enhanced T1-weighted images. Unsupervised correlation analysis of reproducible features and least absolute shrinkage and selector operation were used for the selection of features to build a radiomics signature. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the radiomic signature. Multivariable logistic regression was used to identify independent predictors for distinguishing HER2 expressions in both the training and prospectively acquired external data set. Results The training set included 208 patients from center 1 (mean age, 53 years ± 14 [SD]), and the external test set included 131 patients from center 2 (mean age, 54 years ± 13). In the external test data set, the radiomic signature achieved an AUC of 0.80 (95% CI: 0.71, 0.89) for distinguishing HER2-low and -positive tumors versus HER2-zero tumors and was a significant predictive factor for distinguishing these two groups (odds ratio = 7.6; 95% CI: 2.9, 19.8; P < .001). Among HER2-low or -positive breast cancers, histology type, associated nonmass enhancement, and multiple lesions at MRI had an AUC of 0.77 (95% CI: 0.68, 0.86) in the external test set for the prediction of HER2-positive versus HER2-low cancers. Conclusion The radiomic signature and tumor descriptors from multiparametric breast MRI may predict distinct HER2 expressions of breast cancers with therapeutic implications. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kataoka and Honda in this issue.

Response to Induction Therapy in Pediatric Hodgkin's Lymphoma: Performance of First-Order Texture Parameters of CT Images.

Objectives: The aim of this study was to examine whether texture analysis features on pretreatment contrast-enhanced CT images could predict adequate response (AR) or inadequate response (IR) after two cycles of chemotherapy in pediatric Hodgkin's lymphoma (PHL). Materials and methods: This retrospective single-center study included 32 children and adolescents with HL. Texture analysis was independently performed by two radiologists using pretreatment CT scans. The mean gray level, standard deviation, entropy, kurtosis, and skewness were derived from pixel distribution histograms before and after spatial filtration ranging from two (fine texture) to six (coarse texture). Interobserver reliability was studied using interobserver correlation coefficients (ICCs) to select texture parameters. Relationships between early response assessment (ERA) to induction therapy and associated factors were studied using Student's t-tests and a lasso penalized logistic regression analysis. Results: Of the 32 patients, IR was observed in 13 and AR in 19. Inter-reader agreement was good to excellent (ICC > 0.75) for all parameters except skewness and kurtosis without filtration and at spatial scale filtration (SSF) = 2. These parameters were excluded from the analysis. The t-test identified only entropy at SSF = 2 (p value = 0.039) as a potential predictor of ERA. No parameters were significantly associated with ERA, according to a lasso penalized logistic regression. Conclusion: No textural parameters were identified as predictors of ERA after two cycles of chemotherapy in PHL.

CT texture analysis as a predictor of favorable response to anti-PD1 monoclonal antibodies in metastatic skin melanoma.

PURPOSE: The purpose of this study was to determine whether texture analysis features on pretreatment contrast-enhanced computed tomography (CT) images and their evolution can predict treatment response of metastatic skin melanoma (SM) treated with anti-PD1 monoclonal antibodies. MATERIALS AND METHODS: Sixty patients (29 men, 31 women; median age, 56 years; age range: 27-91 years) with metastatic SM treated with pembrolizumab (43/60; 72%) or nivolumab (17/60; 28%) were included. Texture analysis of SM metastases was performed on baseline and first post-treatment evaluation CT examinations. Mean gray-level, entropy, kurtosis, skewness, and standard deviation values were derived from the pixel distribution histogram before and after spatial filtration at different anatomic scales, ranging from fine to coarse. Lasso penalized Cox regression analyses were performed to identify independent variables associated with favorable response to treatment. RESULTS: A total of 127 metastases were analyzed, with a median of two metastases per patient. Skewness at fine texture scale (spatial scale filtration [SSF] = 2; Hazard ratio [HR]: 3.51; 95% CI: 2.08-8.57; P = 0.010), skewness at medium texture scale (SSF = 3; HR: 0.56; 95% CI: 0.11-1.59; P = 0.014), variation of entropy at fine texture scale (SSF = 2; HR: 37.76; 95% CI: 3.48-496.22; P = 0.008) and LDH above the threshold of 248 UI/L (HR: 3.56; 95% CI: 1.78-21.35; P = 0.032] were independent predictors of response to treatment. CONCLUSION: Pretreatment CT texture analysis-derived tumor skewness and variation of entropy between baseline and first control CT examination may be used as predictors of favorable response to anti-PD1 monoclonal antibodies in patients with metastatic SM.

Abdominal metastases from Merkel cell carcinoma: Prevalence and presentation on CT examination in 111 patients.

PURPOSE: The purpose of this study was to report the prevalence and imaging features of abdominal metastases from Merkel cell carcinoma (MCC) on computed tomography (CT) examinations. MATERIALS AND METHODS: A total of 111 patients with MCC from two institutions were initially identified. Of these, 27 patients (27/111; 24.3%) had abdominal metastases from MCC present on CT examination. There were 19 men and 8 women with a mean age of 75  ± 10.8 (SD) years (age range: 46-92 years). CT examinations were retrospectively reviewed by two radiologists and analyzed quantitatively for the number and dimensions of abdominal metastases from MCC and qualitatively in terms of location, margins, contours, homogeneity, patterns of enhancement, vascular involvement and extension of metastases from MCC. RESULTS: Fifteen patients (15/27; 56%) had abdominal metastatic disease at initial diagnosis and twelve (12/27; 44%) developed abdominal metastases during the course of the disease. The mean number of locations of abdominal metastases was 2.1 ± 1.12 (SD) (range: 1-5). Abdominal metastases involved abdominal lymph nodes (16/27; 59%), adrenal glands/kidneys/retroperitoneum (14/27; 52%), mesentery/peritoneum (13/27; 48%), liver (7/27; 26%) and pancreas (7/27; 26%). Vascular involvement was found in association with peritoneal/mesenteric metastases in 6/13 (46%) patients with intraperitoneal metastases or in association with abdominal lymph nodes in 4/16 (25%) patients. Ureteral encasement and/or dilatation was found in 4/14 (28%) patients with retroperitoneal metastases and 3/16 (19%) patients with abdominal lymph nodes. Metastases to the liver, pancreas, peritoneum, retroperitoneum and adrenal glands displayed internal enhancement during the arterial phase in 1/2 (50%), 4/5 (80%), 4/7 (57%) and 5/8 (62%) patients for whom arterial phase was available, respectively. CONCLUSION: Metastases from MCC have a prevalence of 24.3% on CT examination and may involve a variety of abdominal organs, mainly lymph nodes, peritoneal and retroperitoneal structures, but also the liver and pancreas. CT features of abdominal metastases from MCC include hypervascularity during the arterial phase of enhancement and eventually vascular and ureteral involvement.

Differentiation between heterogeneous adrenal adenoma and non-adenoma adrenal lesion with CT and MRI.

PURPOSE: To assess whether heterogeneous adrenal adenomas can be distinguished from heterogeneous non-adenomas with Computed Tomography (CT) and/or Magnetic Resonance Imaging (MRI). METHOD: From 2009 to 2019, 980 consecutive adrenalectomies were retrospectively identified. Patients without adequate CT/MRI, with homogeneous and/or < 1 cm lesions were excluded. Differences between adenomas and non-adenomas were analyzed using Chi-square, Student t or Fischer tests, and interobserver agreement using weighted kappa test or intraclass correlation coefficient. Independent variables associated with adenomas were searched for using multivariable analysis. Area under the receiver operating characteristic curve (AUC) of the final model and its diagnostic performances were calculated. RESULTS: Final population comprised 183 patients (106 women, 77 men, mean age 53.2 ± 14.4 years) with 124 non-adenomas and 59 heterogeneous adenomas. Macroscopic or microscopic fat on CT/MRI allowed diagnosis of adenoma with 98% specificity and 63% sensitivity. Interobserver agreement was almost perfect for macroscopic fat (k = 0.82; 95% CI 0.66; 0.94) and substantial for microscopic fat (k = 0.75; 95% CI 0.62; 0.86). A multivariable model including micro- or macroscopic fat [Odds ratio (OR) 81.19; 95% CI 20.17; 572.27], diameter < 5.5 cm (OR 7.32; 95% CI 2.17; 31.28), calcifications (OR 5.68; 95% CI 2.08; 16.18), and hemorrhage (OR 3.10; 95% CI 0.70; 15.35) had an AUC of 0.91 (95% CI 0.86; 0.96), 71% (42/59, 95% CI 58; 82) sensitivity, 93% (115/124; 95% CI 87; 97) specificity, and 86% (157/183; 95% CI 79; 90) accuracy for the diagnosis of adenoma. CONCLUSION: A multivariable model enables CT/MR diagnosis of heterogeneous adenomas. Presence of microscopic fat, even if partial, in a heterogeneous mass is highly specific of adenoma.

ADC measurement relevance to predict hemorrhage transformation after mechanical thrombectomy.

BACKGROUND: ADC (apparent coefficient diffusion) value has been known to predict hemorrhage transformation (HT) after thrombolysis and recently, after mechanical thrombectomy (MT). We aimed to evaluate that utility separately in basal ganglia and superficial territory. We used HT occurrence with or without NIHSS change as primary outcome measures. METHODS: This single-center retrospective study included consecutive stroke patients receiving MT for internal carotid artery (ICA) or middle cerebral artery (M1 or M2) occlusion. In patient with or without HT, using the Heidelberg Bleeding Classification, on follow-up CT scan at 24-48 h, we assessed the ADC value separately in basal ganglia and superficial territory on MRI before MT to search for the correlation. Multivariable analysis was performed using variables with significant differences between the HT group and non-HT group. RESULTS: One hundred seventeen patients were included in the final analysis. HT distribution was as follows: 9 patients (7.69%) HI1 or 2; 14 patients (11.97%) PH1; 21 patients (17.95%) PH2; 29 patients (24.79%) subarachnoid hemorrhage; and 21 patients (17.95%) symptomatic intracranial hemorrhage (sICH). Mean ADC minimal value in basal ganglia in the HT group was significantly lower than in the non-HT group (377.6 × 10-6 mm2/s [± 52.4] vs 413.3 × 10-6 mm2/s [± 72.5]; p = 0.0229) with an area under the curve (AUC) of 0.6622 (95% CI: 0.5-0.8; p = 0.014). MRI-MT time was significantly longer in the HT group (p = 0.0002), but there was no association between ADC value and onset-MRI or MRI-MT times (Spearman's coefficients <0.7, p > 0.05). Glycemia at admission (>1.5 g/L) (OR = 4.2; 95% CI [1.611; 10.961]) and carotid occlusion (OR = 2.835; 95% CI [1.134; 7.091]) were independently associated with HT. CONCLUSIONS: ADC value in basal ganglia, unlike brain superficial territory, are correlated to HT risk after MT.

Diagnosis of postoperative recurrence of Crohn disease with MR-enterography: Value of diffusion-weighted imaging.

PURPOSE: To compare the diagnostic capabilities of MR enterography (MRE) using contrast-enhanced (CE) sequences with those of MRE using diffusion-weighted (DW) imaging for the diagnosis of postoperative recurrence at the neo-terminal ileum and/or anastomosis after ileocolonic resection in patients with Crohn disease (CD), and to clarify the role of additional DW imaging to CE-MRE in this context. MATERIAL AND METHODS: Forty patients who underwent ileal resection for CD, and both endoscopy and MRE within the first year after surgery were included. There were 21 men and 19 women, with a mean age of 38 years±12 (SD) years (range: 18-67 years). MRE examinations were blindly analyzed independently by one senior (R1) and one junior (R2) radiologist for the presence of small bowel postoperative recurrence at the anastomotic site. During a first reading session, T2-, steady-state- and DW-MRE were reviewed (DW-MRE or set 1). During a separate distant session, T2-, steady-state- and CE-MRE were reviewed (CE-MRE or set 2). Lastly, all sequences were analyzed altogether (set 3). Performances of each reader for the diagnosis of postoperative recurrence were evaluated using endoscopic findings as the standard of reference (Rutgeerts score≥i2b). RESULTS: Fifteen patients out of 40 (37.5%) had endoscopic postoperative recurrence at the anastomotic site. Sensitivity for the diagnosis of postoperative recurrence was 73% (95% CI: 51-96%) for R1 and 67% (95% CI: 43-91%) for R2 using set 1, and 80% (95% CI: 60-100%) for both readers using set 2. There was no significant differences in sensitivity between reading set 1 and reading set 2, for either R1 or R2 (R1, P> 0.99; R2, P=0.48). Specificity was 96% (95% CI: 88-100%) for both readers using set 1 or using set 2. Reading set 3 yielded an area under the ROC curve (AUC) of 0.93 (95% CI: 0.84-1) versus 0.89 (95% CI: 0.75-1) with set 1 (P=0.18) and versus 0.89 (95% CI: 0.78-1) with set 2 (P=0.21). No significant differences in AUC were found between set 1 or 2 and set 3 (P=0.18), nor between set 1 and 2 (P=0.76). Accuracies were 88% (95% CI: 74-95%) and 85% (95% CI: 71-93%) for DW-MRE for R1 and R2, respectively; 90% (95% CI: 77-96%) for CE-MRE for both readers; and 93% (95% CI: 80-97%) and 88% (95% CI: 74-95%) for R1 and R2 with set 3, respectively. CONCLUSION: DW-MRE has diagnostic capabilities similar to those of CE-MRE for the diagnosis of postoperative recurrence of CD at the anastomotic site.

MR Imaging of the Perihepatic Space.

The perihepatic space is frequently involved in a spectrum of diseases, including intrahepatic lesions extending to the liver capsule and disease conditions involving adjacent organs extending to the perihepatic space or spreading thanks to the communication from intraperitoneal or extraperitoneal sites through the hepatic ligaments. Lesions resulting from the dissemination of peritoneal processes may also affect the perihepatic space. Here we discuss how to assess the perihepatic origin of a lesion and describe the magnetic resonance imaging (MRI) features of normal structures and fluids that may be abnormally located in the perihepatic space. We then review and illustrate the MRI findings present in cases of perihepatic infectious, tumor-related, and miscellaneous conditions. Finally, we highlight the value of MRI over computed tomography.

COVID-19: A qualitative chest CT model to identify severe form of the disease.

PURPOSE: The purpose of this study was to identify clinical and chest computed tomography (CT) features associated with a severe form of coronavirus disease 2019 (COVID-19) and to propose a quick and easy to use model to identify patients at risk of a severe form. MATERIALS AND METHODS: A total of 158 patients with biologically confirmed COVID-19 who underwent a chest CT after the onset of the symptoms were included. There were 84 men and 74 women with a mean age of 68±14 (SD) years (range: 24-96years). There were 100 non-severe and 58 severe cases. Their clinical data were recorded and the first chest CT examination was reviewed using a computerized standardized report. Univariate and multivariate analyses were performed in order to identify the risk factors associated with disease severity. Two models were built: one was based only on qualitative CT features and the other one included a semi-quantitative total CT score to replace the variable representing the extent of the disease. Areas under the ROC curves (AUC) of the two models were compared with DeLong's method. RESULTS: Central involvement of lung parenchyma (P<0.001), area of consolidation (P<0.008), air bronchogram sign (P<0.001), bronchiectasis (P<0.001), traction bronchiectasis (P<0.011), pleural effusion (P<0.026), large involvement of either one of the upper lobes or of the middle lobe (P<0.001) and total CT score≥15 (P<0.001) were more often observed in the severe group than in the non-severe group. No significant differences were found between the qualitative model (large involvement of either upper lobes or middle lobe [odd ratio (OR)=2.473], central involvement [OR=2.760], pleural effusion [OR=2.699]) and the semi-quantitative model (total CT score≥15 [OR=3.342], central involvement [OR=2.344], pleural effusion [OR=2.754]) with AUC of 0.722 (95% CI: 0.638-0.806) vs. 0.739 (95% CI: 0.656-0.823), respectively (P=0.209). CONCLUSION: We have developed a new qualitative chest CT-based multivariate model that provides independent risk factors associated with severe form of COVID-19.

Involvement of small bowel in systemic disease: CT and MR imaging finding.

Computerized tomography (CT) and magnetic resonance imaging (MRI), particularly MR Enterography, are the standard cross-sectional imaging modalities used to study small bowel involvement in a context of multiorgan disease. Clinical symptoms are generally nonspecific in such cases. Moreover, imaging findings of the different conditions often overlap. However, analysis of the location, distribution of the lesions on the small bowel wall, as well as of the rest of the bowel and of distant organs, may help narrow the spectrum of diagnoses of multiorgan conditions involving both the small bowel and other organs. The purpose of this presentation is to review and illustrate the CT and MRI features of small bowel involvement in systemic disease. Based on the underlying mechanism, we will categorize them as follows: congenital/hereditary, immunologic, infiltrative, vascular, infectious and miscellaneous.

Magnetic resonance imaging evaluation of cervical length by the women's age: a retrospective cohort study.

OBJECTIVE: The anthropometric characteristics of the uterus evolve with pubertal development in girls. It is therefore permissible to ask until these anthropometric characteristics change, in order to know if the cervical length criterion defined for preterm delivery threats is applicable to all ages. The main objective of our study was to analyze the evolution of cervical length with the women's age outside pregnancy to overcome factors related to pregnancy that can affect cervical length. MATERIAL AND METHODS: This retrospective descriptive study over a period of 1 year from March 2017 to March 2018. The cervical length measurements were performed by Magnetic Resonnance Imaging. The cervical length was defined by sagittal T2-weighted magnetic resonance imaging (MRI) as the distance on a straight line between the external cervical os (at the point of divergence of the anterior and posterior lips) and the internal cervical os identified by an intersection between the line of the hypersignal of the glandular epithelium and a line passing through the isthmus. RESULTS: A total of 209 patients were included. The cervical length ranged from 25.2 mm on average in children under 16 years (23.6-27.1 mm) to 39.7 mm between 36 and 40 years (27.9 -58.9 mm). There was a linear association between age and cervical length, irrespective of maternal anthropometric data (Pearson's coefficient ρ = 0.43, 95% CI 0.32-0.54 (p < 0.01). In multivariate analysis, the only factors associated with cervical length were women's age (p < 0.01) and the prior delivery (p < 0.01). CONCLUSION: The cervical length is correlated with women age and the prior delivery.