Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image.

PURPOSE: To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS). METHODS: Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses. RESULTS: The area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83-0.95) for reader 1, and 0.89 (95% CI: 0.82-0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively. CONCLUSION: Our results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.

Preoperative Localization of Parathyroid Adenomas with Diffusion MR Imaging: Readout-segmented versus Single-shot Echo-planar Imaging.

PURPOSE: To evaluate whether readout-segmented echo-planar imaging (RS-EPI) diffusion-weighted imaging (DWI) can reduce image distortion and improve the lesion identification in parathyroid adenomas (PTAs) compared to single-shot EPI (SS-EPI) DWI, and to determine whether PTAs can be differentiated from other soft tissue structures of the head and neck region by using the apparent diffusion coefficient (ADC) value. METHODS: We retrospectively analyzed the preoperative MR images including DWI of 24 patients with surgically confirmed PTA. RS-EPI and SS-EPI DWI were evaluated by two independent readers for the identification of the lesions and distortion. The ADC values of the PTAs were compared with those of thyroid glands and cervical lymph nodes. RESULTS: RS-EPI provided significantly less distortion compared to SS-EPI. RS-EPI tended to have better lesion identification compared with SS-EPI without a statistically significant difference. On SS-EPI, the PTAs had significantly higher ADC values compared with the cervical lymph nodes. On RS-EPI, the PTAs had significantly higher ADC values compared with the thyroid glands and cervical lymph nodes. CONCLUSION: RS-EPI reduces the DWI distortion in PTAs. The ADC value obtained using RS-EPI enables the differentiation of PTAs from nearby structures, such as thyroid glands and cervical lymph nodes.

The added value of non-contrast 3-Tesla MRI for the pre-operative localization of hyperparathyroidism

Abstract Objective: We investigated the efficacy of non-contrast 3-Tesla MR imaging added to the combination of sestamibi with99mTc (MIBI) scintigraphy and Ultrasonography (US) for the pre-operative localization of Primary Hyperparathyroidism (PHPT) lesions. Methods: A total of 34 parathyroid glands, including nine normal glands, were examined with MIBI, US, and non-contrast 3-Tesla MRI. MRI was performed with the acquisition of T1- and T2-weighted images and fat-suppressed T2-weighted images. We calculated the sensitivities of MIBI, US, and the ‛additional' MRI, with knowledge of the former two modalities' results. Results: For the diagnosis of PHPT lesions, the sensitivity values of MIBI, US, and additional MRI were 88.0% (22/25), 84.0% (21/25), and 92.0% (23/25), respectively. Normal glands were not visualized with any modality (0/9). One lesion was detected neither with US nor MRI, but only with MIBI, with the limitation that MIBI represented no more than laterality. The two glands not identified in MRI were 4 mm and 6 mm in their size, which are within the range of normal gland's size. Two lesions were not detected with US or MIBI but were visualized with the additional MRI, which indicated that the MRI contributed an 8.0% (2/25) improvement of sensitivity, compared from that of US. Fat-suppressed T2-weighted images were useful in the identification of parathyroid lesions, as these images helped to differentiate between the lesion and the adjacent tissue. Conclusion: Additional non-contrast 3-Tesla MRI was a useful adjunctive tool for localization of PHPT, which improved the sensitivity of the pre-operative localization of PHPT lesions. Fatsuppressed T2-weighted images contributed to their identification. Level VI: Evidence from a single descriptive or qualitative study.

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype.

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively). The diagnostic performance for the detection of residual invasive cancer was calculated by ROC analysis. The size difference between MRI and pathological findings was analyzed using the Wilcoxon signed-rank test with the Bonferroni correction. The overall AUC was highest for UF (0.86 and 0.88 for readers 1 and 2, respectively). The difference in imaging and pathological sizes for UF (5.7 ± 8.2 mm) was significantly smaller than those for early, delayed, and HR (p < 0.01). For luminal subtype breast cancer, the size difference was significantly smaller for UF and early than for delayed (p < 0.01). UF-DCE MRI demonstrated higher AUC and specificity for the more accurate detection of residual cancer and the visualization of tumor extent than conventional DCE MRI.

The added value of non-contrast 3-Tesla MRI for the pre-operative localization of hyperparathyroidism.

OBJECTIVE: We investigated the efficacy of non-contrast 3-Tesla MR imaging added to the combination of sestamibi with99mTc (MIBI) scintigraphy and Ultrasonography (US) for the pre-operative localization of Primary Hyperparathyroidism (PHPT) lesions. METHODS: A total of 34 parathyroid glands, including nine normal glands, were examined with MIBI, US, and non-contrast 3-Tesla MRI. MRI was performed with the acquisition of T1- and T2-weighted images and fat-suppressed T2-weighted images. We calculated the sensitivities of MIBI, US, and the 'additional' MRI, with knowledge of the former two modalities' results. RESULTS: For the diagnosis of PHPT lesions, the sensitivity values of MIBI, US, and additional MRI were 88.0% (22/25), 84.0% (21/25), and 92.0% (23/25), respectively. Normal glands were not visualized with any modality (0/9). One lesion was detected neither with US nor MRI, but only with MIBI, with the limitation that MIBI represented no more than laterality. The two glands not identified in MRI were 4 mm and 6 mm in their size, which are within the range of normal gland's size. Two lesions were not detected with US or MIBI but were visualized with the additional MRI, which indicated that the MRI contributed an 8.0% (2/25) improvement of sensitivity, compared from that of US. Fat-suppressed T2-weighted images were useful in the identification of parathyroid lesions, as these images helped to differentiate between the lesion and the adjacent tissue. CONCLUSION: Additional non-contrast 3-Tesla MRI was a useful adjunctive tool for localization of PHPT, which improved the sensitivity of the pre-operative localization of PHPT lesions. Fat-suppressed T2-weighted images contributed to their identification. LEVEL VI: Evidence from a single descriptive or qualitative study.

High-resolution magnetic resonance and mass spectrometry imaging of the human larynx.

High-resolution, noninvasive and nondestructive imaging of the subepithelial structures of the larynx would enhance microanatomic tissue assessment and clinical decision making; similarly, in situ molecular profiling of laryngeal tissue would enhance biomarker discovery and pathology readout. Towards these goals, we assessed the capabilities of high-resolution magnetic resonance imaging (MRI) and matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS) imaging of rarely reported paediatric and adult cadaveric larynges that contained pathologies. The donors were a 13-month-old male, a 10-year-old female with an infraglottic mucus retention cyst and a 74-year-old female with advanced polypoid degeneration and a mucus retention cyst. MR and molecular imaging data were corroborated using whole-organ histology. Our MR protocols imaged the larynges at 45-117 µm2 in-plane resolution and capably resolved microanatomic structures that have not been previously reported radiographically-such as the vocal fold superficial lamina propria, vocal ligament and macula flavae; age-related tissue features-such as intramuscular fat deposition and cartilage ossification; and the lesions. Diffusion tensor imaging characterised differences in water diffusivity, primary tissue fibre orientation, and fractional anisotropy between the intrinsic laryngeal muscles, mucosae and lesions. MALDI-MS imaging revealed peptide signatures and putative protein assignments for the polypoid degeneration lesion and the N-glycan constituents of one mucus retention cyst. These imaging approaches have immediate application in experimental research and, with ongoing technology development, potential for future clinical application.

Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI.

PURPOSE: Category 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to < 95%. We classified category 4 lesions into three subcategories and analyzed the positive predictive value (PPV) of malignancy in a tertiary hospital. MATERIALS AND METHODS: This retrospective study included 346 breast MRIs with 434 category 2-5 lesions. All enhancing lesions were classified as category 2 (0% probability of malignancy), 3 (> 0%, ≤ 2%), 4 (> 2%, < 95%) and 5 (≥ 95%); category 4 lesions were further subcategorized into 4A (> 2%, ≤ 10%), 4B (> 10%, ≤ 50%) and 4C (> 50%, < 95%) at the time of diagnosis. Radiological and pathological reports were retrospectively analyzed, and the PPVs were calculated. RESULTS: We included 149 malignant and 285 benign lesions. The PPVs of subcategories 4A, 4B and 4C were 1.8%, 11.8% and 67.5%, respectively. The PPVs were higher for lesions coexisting with category 5 or 6 lesions compared with those for isolated lesions. CONCLUSION: Category 4 lesions can be classified into three subcategories depending on the likelihood of malignancy. Lesions coexisting with category 5 or 6 lesions are more likely to be malignant.

Evaluation of Malignant Breast Lesions Using High-resolution Readout-segmented Diffusion-weighted Echo-planar Imaging: Comparison with Pathology.

PURPOSE: We aimed to investigate the performance of high resolution-diffusion-weighted imaging (HR-DWI) using readout-segmented echo-planar imaging in visualizing malignant breast lesions and evaluating their extent, using pathology as a reference. METHODS: This retrospective study included patients who underwent HR-DWI with surgically confirmed malignant breast lesions. Two radiologists blinded to the final diagnosis evaluated HR-DWI independently and identified the lesions, measuring their maximum diameters. Another radiologist confirmed if those lesions were identical to the pathology. The maximum diameters of the lesions between HR-DWI and pathology were compared, and their correlations were calculated using Spearman's correlation coefficient. Apparent diffusion coefficient (ADC) values of the lesions were measured. RESULTS: Ninety-five mass/64 non-mass lesions were pathologically confirmed in 104 females. Both radiologists detected the same 93 mass lesions (97.9%). Spearman's correlation coefficient for mass lesions were 0.89 and 0.90 (P < 0.0001 and 0001) for the two radiologists, respectively. The size differences within 10 mm were 90.3% (84/93) and 94.6% (88/93) respectively. One radiologist detected 35 non-mass lesions (54.7%) and another radiologist detected 32 non-mass lesions (50.0%), of which 28 lesions were confirmed as identical. Spearman's correlation coefficient for non-mass lesions were 0.59 and 0.22 (P = 0.0002 and 0.22), respectively. The mean ADC value of mass lesions and non-mass lesions were 0.80 and 0.89 × 10-3 mm2/s, respectively. CONCLUSION: Using HR-DWI, malignant mass lesions were depicted with excellent agreement with the pathological evaluation. Approximately half of the non-mass lesions could not be identified, suggesting a current limitation of HR-DWI.

Background parenchymal enhancement and its effect on lesion detectability in ultrafast dynamic contrast-enhanced MRI.

PURPOSE: Background parenchymal enhancement (BPE) often affects interpretation of dynamic contrast-enhanced (DCE) MRI. There is limited evidence that reduced BPE is a feature of ultrafast DCE (UF-DCE) MRI. We aimed to evaluate the effect of BPE levels on lesion detectability on UF-DCE MRI in comparison with conventional DCE MRI. METHOD: MRIs of 70 patients with histologically proven breast lesions were retrospectively evaluated. The total number of analyzed lesions was 84 (56 malignant and 28 benign). Using 3 T MRI, 20 phases of UF-DCE MRI based on the three-dimensional gradient-echo VIBE sequence combined with a compressed sensing reconstruction were acquired followed by conventional DCE MRI. Three maximum intensity projection (MIP) images were generated from the 12th phase, the 20th phase of UF-DCE MRI and the initial phase of conventional DCE MRI. Two radiologists independently evaluated the degree of BPE and lesion detectability of the three MIP images for each breast with histologically confirmed lesions. The degree of BPE was scored on a four-point scale and lesion detectability (conspicuity and confidence levels) was scored on a three-point scale. Data were analyzed using the Wilcoxon signed-rank test with Bonferroni correction. RESULTS: BPE was lower on UF-DCE MRI than on conventional DCE MRI. Lesion detectability was higher on UF-DCE MRI among patients with higher BPE on conventional DCE MRI or premenopausal women. CONCLUSIONS: Images with lower BPE can be achieved using UF-DCE MRI and may be advantageous when assessing breast lesions among patients with higher BPE or premenopausal women.

A multiparametric approach to diagnosing breast lesions using diffusion-weighted imaging and ultrafast dynamic contrast-enhanced MRI.

PURPOSE: To evaluate the diagnostic performance of a multiparametric approach to breast lesions including apparent diffusion coefficient (ADC) from diffusion-weighted images (DWI), maximum slope (MS) from ultrafast dynamic contrast enhanced (UF-DCE) MRI, lesion size, and patient's age. MATERIALS AND METHODS: In total, 96 lesions (73 malignant, 23 benign) were evaluated. UF-DCE MRI was acquired using a prototype 3D-gradient-echo volumetric interpolated breath-hold examination (VIBE) with compressed sensing. Images were obtained up to 1 min after gadolinium injection. MS was calculated as the percentage relative enhancement/s. An ADC map was automatically generated from DWI at b = 0 and b = 1000 s/mm2. MS and ADC values were measured by two radiologists independently. Interrater agreement was evaluated using intraclass correlation coefficients. Univariate and multivariate logistic regression analyses were performed using MS, ADC, lesion size, and the patient's age. The parameters of the prediction model were generated from the results of the multivariate logistic regression analysis. Area under the curve (AUC) was used to compare diagnostic performance of the prediction model and each parameter. RESULTS: Interrater agreements on MS and ADC were excellent (ICC 0.99 and 0.88, respectively). MS, ADC, and patient's age remained as significant parameters after univariate and multivariate logistic regression analysis. The prediction model using these significant parameters yielded an AUC of 0.90, significantly higher than that of MS (AUC 0.74, p = 0.01). The AUCs of ADC, MS, patient's age were 0.87, 0.74 and 0.73, respectively. CONCLUSIONS: A multiparametric model using ADC from DWI, MS from UF-DCE MRI, and patient's age showed excellent diagnostic performance, with greater contribution of ADC. Combining DWI and UF-DCE MRI might reduce scanning time while preserving diagnostic performance.

The comparison of high-resolution diffusion weighted imaging (DWI) with high-resolution contrast-enhanced MRI in the evaluation of breast cancers.

PURPOSE: We sought to investigate the performance of high resolution (HR) diffusion-weighted imaging (DWI) using readout-segmented echo-planar imaging (rs-EPI), compared with high-resolution contrast-enhanced MRI (HR CE-MRI) in terms of morphological accuracy, on the basis of the Breast Imaging and Reporting and Data System (BI-RADS) MRI descriptors and lesion size. METHODS: This retrospective study included the image data of 94 patients with surgically confirmed malignant breast lesions who had undergone high resolution diffusion-weighted imaging (HR-DWI) and HR CE-MRI. Two radiologists blinded to the final diagnosis independently identified the lesions on HR-DWI, described the morphology of the lesions according to BI-RADS descriptors, and measured lesion size. HR CE-MRI was subsequently evaluated using the same procedure. The inter-method agreement of the morphology was assessed using kappa statistics. Correlation on size was also assessed. RESULTS: Reader A detected 79 mass lesions and 37 non-mass lesions on HR-DWI and HR CE-MRI. Reader B detected 81 mass lesions and 33 non-mass lesions on HR-DWI and HR CE-MRI. Very high agreement (kappa = 0.81-0.89, p < .05) was observed in the shape and margin assessment of mass lesions, where agreement on internal enhancement/signals was moderate to substantial (kappa = 0.43-0.61, p < .05). Disagreement was mostly seen in the evaluation of rim enhancement. High agreement was observed for non-mass lesion distribution (kappa = 0.76-0.84, p < .05), and agreement on internal enhancement/signals was moderate to fair (kappa = 0.34-0.49, p < .05). Agreement among heterogeneous, clumped, and clustered-ring patterns was variable. Size assessment showed very strong correlation both in mass (Spearman's rho = 0.90-0.96, p < .0001) and non-mass lesions (Spearman's rho = 0.86, p < .0001). CONCLUSIONS: The findings in morphology and lesion extent showed high agreement between HR-DWI and HR CE-MRI for malignant breast lesions. These results imply the potential of applying HR-DWI for evaluation of malignant breast lesions using BI-RADS MRI.

Dedifferentiated liposarcoma of the thyroid gland: A case report.

Liposarcoma is one of the most common soft tissue tumors that affect adults. Liposarcoma is typically identified in the retroperitoneum, trunk and extremities as a slow-growing mass, yet is rare in the thyroid gland. Herein, we report a case of dedifferentiated liposarcoma that developed in the thyroid gland, and performed a literature review. A 66-year-old male with a history of well-differentiated liposarcoma in the thymus presented with a rapidly enlarging mass in the thyroid gland. Malignancy was suspected due to the local extension of the tumor, and complete resection of the tumor was achieved. Tissue diagnosis from the tumor following surgery revealed that dedifferentiated liposarcoma, and tumor progression was difficult to control with adjuvant radiation and chemotherapy. This is, to the best of our knowledge, the first case to report dedifferentiated liposarcoma in the thyroid gland, and the difficulty in initial diagnosis as well as the aggressive features of dedifferentiated liposarcoma are highlighted.

High- and ultrahigh-field magnetic resonance imaging of naïve, injured and scarred vocal fold mucosae in rats.

Subepithelial changes to the vocal fold mucosa, such as fibrosis, are difficult to identify using visual assessment of the tissue surface. Moreover, without suspicion of neoplasm, mucosal biopsy is not a viable clinical option, as it carries its own risk of iatrogenic injury and scar formation. Given these challenges, we assessed the ability of high- (4.7 T) and ultrahigh-field (9.4 T) magnetic resonance imaging to resolve key vocal fold subepithelial tissue structures in the rat, an important and widely used preclinical model in vocal fold biology. We conducted serial in vivo and ex vivo imaging, evaluated an array of acquisition sequences and contrast agents, and successfully resolved key anatomic features of naïve, acutely injured, and chronically scarred vocal fold mucosae on the ex vivo scans. Naïve lamina propria was hyperintense on T1-weighted imaging with gadobenate dimeglumine contrast enhancement, whereas chronic scar was characterized by reduced lamina propria T1 signal intensity and mucosal volume. Acutely injured mucosa was hypointense on T2-weighted imaging; lesion volume steadily increased, peaked at 5 days post-injury, and then decreased - consistent with the physiology of acute, followed by subacute, hemorrhage and associated changes in the magnetic state of hemoglobin and its degradation products. Intravenous administration of superparamagnetic iron oxide conferred no T2 contrast enhancement during the acute injury period. These findings confirm that magnetic resonance imaging can resolve anatomic substructures within naïve vocal fold mucosa, qualitative and quantitative features of acute injury, and the presence of chronic scar.

Modeling fibrosis using fibroblasts isolated from scarred rat vocal folds.

Following injury, pathologically activated vocal fold fibroblasts (VFFs) can engage in disordered extracellular matrix (ECM) remodeling, leading to VF fibrosis and impaired voice function. Given the importance of scar VFFs to phenotypically appropriate in vitro modeling of VF fibrosis, we pursued detailed characterization of scar VFFs obtained from surgically injured rat VF mucosae, compared with those obtained from experimentally naïve, age-matched tissue. Scar VFFs initially exhibited a myofibroblast phenotype characterized by increased proliferation, increased Col1a1 transcription and collagen, type I synthesis, increased Acta2 transcription and α-smooth muscle actin synthesis, and enhanced contractile function. These features were most distinct at passage 1 (P1); we observed a coalescence of the scar and naïve VFF phenotypes at later passages. An empirical Bayes statistical analysis of the P1 cell transcriptome identified 421 genes that were differentially expressed by scar, compared with naïve, VFFs. These genes were primarily associated with the wound response, ECM regulation, and cell proliferation. Follow-up comparison of P1 scar VFFs and their in vivo tissue source showed substantial transcriptomic differences. Finally, P1 scar VFFs responded to treatment with hepatocyte growth factor and transforming growth factor-ß3, two biologics with reported therapeutic value. Despite the practical limitations inherent to working with early passage cells, this experimental model is easily implemented in any suitably equipped laboratory and has the potential to improve the applicability of preclinical VF fibrosis research.