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Background Dermatofibrosarcoma protuberans (DFSP) is a kind of low‐grade malignant spindle cell neoplasm, the diagnosis, and treatment, which have markedly attracted clinicians’ attention for its repeated recurrence. High‐resolution magnetic resonance imaging (HR‐MRI) has shown unique capabilities in diagnosis of various cutaneous tumors. Materials and methods Data of 29 patients with clinically suspected DFSPs and undergoing dynamic contrast‐enhanced (DCE) HR‐MRI preoperatively were prospectively collected. The HR‐MRI qualitative features were evaluated and compared. The DCE‐associated quantitative parameters and the time‐signal intensity curve (TIC) types were provided using DCE sequences. Results A total of 7 DFSPs, nine dermatofibromas (DF, including four cases of cellular variant [CDF]), 12 keloids, and one nodular fasciitis were enrolled. DFSP showed the largest major diameter and the deepest depth. Five DFSPs (71.4%) showed ill‐defined margins as well as infiltration of peripheral adipose. All DFSPs showed irregular shape. Most DFSPs presented hyperintensity on T2WI (71.4%) and iso‐intensity on T1WI (85.7%). Six cases (85.7%) had significant enhancement, and six cases (85.7%) had homogeneous enhancement. There were significant differences of Ktrans, Kep, Ve and iAUC values among DFSPs, DFs, and keloids, and DFSP had the highest values for these parameters. Six DFSPs (85.7%) and four CDFs (100%) showed type‐III TICs, while the other lesions showed type‐Ⅰor type‐Ⅱ TICs. Conclusions DCE‐HR‐MRI could show the growth characteristics of DFSPs, which was of great value for the diagnosis and differential diagnosis of DFSPs and was helpful for the determination of treatment options, thereby to improve the prognosis of patients.

Objective To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors. Methods Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed. Results Mean Kep was significantly higher in cancers showing initial rapid enhancement ( P  = 0.002) and a delayed washout pattern ( P  = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern ( P  = 0.015). Kep significantly correlated with time to peak enhancement (TTP) ( ρ  = −0.33, P  < 0.001) and washout slope ( ρ  = 0.39, P  = 0.002). Ve was significantly correlated with TTP ( ρ  = 0.33, P  = 0.002). Mean Kep was higher in tumours with high nuclear grade ( P  = 0.017). Mean Ve was lower in tumours with high histologic grade ( P  = 0.005) and in tumours with negative oestrogen receptor status ( P  = 0.047). TTP was shorter in tumours with negative oestrogen receptor status ( P  = 0.037). Conclusions We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters. Key points • Kep mainly affected the initial and delayed curve pattern in time–signal intensity curve. • There is significant correlation between model-based and model-free parameters. • We acquired information about tumour vascular physiology, interstitial space volume and prognostic factors.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used in preoperative diagnosis of various tumors. We investigated the clinical value of DCE-MRI in differential diagnosis of malignant and benign ovarian lesions. The study involved 48 subjects with surgical pathology-confirmed ovarian tumors with solid components. Early dynamic phase enhancement performances of the ovarian lesions in patients were assessed, including the enhancement pattern, time-signal intensity curve (TIC), signal intensity rate at the initial 60 s (SI 60 ), time to peak within 200 s (TTP 200 ), and slope ratio. There were significant differences in enhancement patterns between benign and malignant ovarian tumors ( P  < 0.05). A total of 30 malignant tumors (30/31) displayed type I TIC, 8 benign tumors (8/13) showed type III TIC, and significant differences were found in TIC type between malignant and benign ovarian lesions ( P  < 0.01). Benign ovarian tumors showed lower SI 60 (%) and slope ratio, as well as significantly prolonged TTP 20 , compared to malignant ovarian tumors (all P  < 0.01). The microvessel count (MVC) of malignant tumors was significantly higher than that of benign tumors ( P  < 0.05). Receiver operating characteristic (ROC) curve analyses revealed that DCE-MRI provided an optimal diagnostic performance with threshold values of SI 60 at 83.40 %, TTP 200 at 77.65 s, and slope ratio at 4.12. These findings revealed that DCE-MRI provides critical information required for differential diagnosis of malignant and benign ovarian lesions.

We aimed to evaluate the use of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) at 3.0 T for differentiating the benign from malignant soft tissue tumors. Also we aimed to assess whether the shorter length of DCE-MRI protocols are adequate, and to evaluate the effect of temporal resolution. Dynamic contrast-enhanced magnetic resonance imaging, at 3.0 T with a 1 second temporal resolution in 13 patients with pathologically confirmed soft tissue tumors, was analyzed. Visual assessment of time-signal curves, subtraction images, maximal relative enhancement at the first (maximal peak enhancement [Emax]/1) and second (Emax/2) minutes, Emax, steepest slope calculated by using various time intervals (5, 30, 60 seconds), and the start of dynamic enhancement were analyzed. The 13 tumors were comprised of seven benign and six malignant soft tissue neoplasms. Washout on time-signal curves was seen on three (50%) malignant tumors and one (14%) benign one. The most discriminating DCE-MRI parameter was the steepest slope calculated, by using at 5-second intervals, followed by Emax/1 and Emax/2. All of the steepest slope values occurred within 2 minutes of the dynamic study. Start of dynamic enhancement did not show a significant difference, but no malignant tumor rendered a value greater than 14 seconds. The steepest slope and early relative enhancement have the potential for differentiating benign from malignant soft tissue tumors. Short-length rather than long-length DCE-MRI protocol may be adequate for our purpose. The steepest slope parameters require a short temporal resolution, while maximal peak enhancement parameter may be more optimal for a longer temporal resolution.

Quantitative DCE-MRI parameters including K trans (transfer constant min −1 ) can predict both response and outcome in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Quantitative methods are time-consuming to calculate, requiring expensive software and interpretive expertise. For diagnostic purposes, signal intensity–time curves (SITCs) are used for tissue characterisation. In this study, we compare the ability of NAC-related changes in SITCs with K trans to predict response and outcomes. 73 women with primary breast cancer underwent DCE-MRI studies before and after two cycles of NAC. Patients received anthracycline and/or docetaxel-based chemotherapy. At completion of NAC, patients had local treatment with surgery & radiotherapy and further systemic treatments. SITCs for paired DCE-MRI studies were visually scored using a five-curve type classification schema encompassing wash-in and wash-out phases and correlated with K trans values and to the endpoints of pathological response, OS and DFS. 58 paired patients studies were evaluable. The median size by MRI measurement for 52 tumours was 38 mm (range 17–86 mm) at baseline and 26 mm (range 10–85 mm) after two cycles of NAC. Median baseline K trans (min −1 ) was 0.214 (range 0.085–0.469), and post-two cycles of NAC was 0.128 (range 0.013–0.603). SITC shapes were significantly related to K trans values both before ( χ 2  = 43.3, P  = 0.000) and after two cycles of NAC ( χ 2 = 60.5, P  = 0.000). Changes in curve shapes were significantly related to changes in K trans ( χ 2  = 53.5, P  = 0.000). Changes in curve shape were significantly correlated with clinical ( P  = 0.005) and pathological response ( P  = 0.005). Reductions in curve shape of ≥1 point were significant for overall improved survival using Kaplan–Meier analysis with a 5-year OS of 80.9 versus 68.6 % ( P  = 0.048). SITCs require no special software to generate and provide a useful method of assessing the effectiveness of NAC for primary breast cancer.

Purpose To assess Crohn’s disease (CD) activity through analysis of time–signal intensity curves and quantitative contrast-enhancement parameters on dynamic contrast-enhanced MRI. Materials and methods 70 patients (male:female = 44:26, age 15–45 years, mean 27.8 years) with biopsy-proven clinically active or inactive CD, underwent dynamic contrast-enhanced MRI after oral administration of iso-osmotic solution. Time–signal intensity curves were classified according to their shape as type I (early upslope with late plateau) and type II (slow contrast material wash-in with late wash-out). Curve parameters such as maximum enhancement (ME), the ratio between late and ME (LE/ME), and UpSlope (US) were compared between patients with active and inactive CD (two-tailed Mann–Whitney test). Sensitivity, specificity, and cut-off for each parameter were calculated by means of receiver operating characteristic curve (ROC) analysis. Results 53/53 patients with active CD and 17/17 with inactive CD showed type I and type II curves, respectively. ME, LE/ME, and US were significantly higher in active than in inactive CD. ME, LE/ME, and US had sensitivity and specificity of 100%:100%:100% and 100%:83%:100% with cut-offs of 135.5:0.8909:2, respectively. Conclusions Qualitative and quantitative analysis of time–signal intensity curves obtained with dynamic contrast-enhanced MRI allow reliable noninvasive differentiation between active and inactive CD.

Aims: The study highlights diffusion-weighted imaging (DWI) and dynamic enhancement features of DFSP and characterizes unenhanced and enhanced computed tomography (CT) and magnetic resonance imaging (MRI) scans. Settings and Design: Image findings and clinical histories of 23 patients with DFSP were reviewed. Nine patients underwent CT before and after intravenous administration of contrast material. MRI was performed for 17 patients. CT and MRI findings were analyzed using location, size, edge, shape, infiltration sign, density and signal enhancement mode, and degree. Results: Patients showed 26 superficial and one deep lesion. Ten superficial lesions bulged onto the skin surface. Fourteen lesions were well-defined and 13 ill-defined. All lesions were nodular, with nine being multilobular. Thirteen showed infiltration to adjacent skin, fat, and fascia. Seven lesions on CT were iso- or hypo-dense to muscle without calcification. Contrast-enhanced CT showed inhomogeneous moderate and progressive enhancement in the arterial phase. Small tortuous vessels were seen in the arterial phase in one case. Sixteen tumors displayed signals that were similar to muscle by T1WI. Ten lesions were either hyper-intense to muscle or iso-intense to fat; the deep DFSP was hypo-intense by T2WI. All lesions were hyper-intense homogeneously or heterogeneously under fat-suppressed T2WI. Twelve superficial lesions showed high-intermediate signal, and one deep lesion showed low-intermediate signal with DWI. Seven cases showed low signal diffusion coefficient (ADC) images. Dynamic enhancement and signal intensity-time (SI-T) curves of four tumors showed rapid SI increases followed by steady or slightly rising SI. All lesions showed inhomogeneous, progressive enhancement in the arterial phase. Conclusions: This report is the first on dynamic curves and highlights DWI and T2WI features of DFSP. DFSP can be correctly diagnosed by combining a patient's clinical manifestations with imaging characteristics.