Pretreatment Prognostic Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Vascular, Texture, Shape, and Size Parameters Compared With Traditional Survival Indicators Obtained From Locally Advanced Breast Cancer Patients.

OBJECTIVES: The aim of this study was to determine if associations exist between pretreatment dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI)-based metrics (vascular kinetics, texture, shape, size) and survival intervals. Furthermore, the aim of this study was to compare the prognostic value of DCE-MRI parameters against traditional pretreatment survival indicators. MATERIALS AND METHODS: A retrospective study was undertaken. Approval had previously been granted for the retrospective use of such data, and the need for informed consent was waived. Prognostic value of pretreatment DCE-MRI parameters and clinical data was assessed via Cox proportional hazards models. The variables retained by the final overall survival Cox proportional hazards model were utilized to stratify risk of death within 5 years. RESULTS: One hundred twelve subjects were entered into the analysis. Regarding disease-free survival-negative estrogen receptor status, T3 or higher clinical tumor stage, large (>9.8 cm) MR tumor volume, higher 95th percentile (>79%) percentage enhancement, and reduced (>0.22) circularity represented the retained model variables. Similar results were noted for the overall survival with negative estrogen receptor status, T3 or higher clinical tumor stage, and large (>9.8 cm) MR tumor volume, again all been retained by the model in addition to higher (>0.71) 25th percentile area under the enhancement curve.Accuracy of risk stratification based on either traditional (59%) or DCE-MRI (65%) survival indicators performed to a similar level. However, combined traditional and MR risk stratification resulted in the highest accuracy (86%). CONCLUSIONS: Multivariate survival analysis has revealed that model-retained DCE-MRI variables provide independent prognostic information complementing traditional survival indicators and as such could help to appropriately stratify treatment.

High proportion of cactus species threatened with extinction.

A high proportion of plant species is predicted to be threatened with extinction in the near future. However, the threat status of only a small number has been evaluated compared with key animal groups, rendering the magnitude and nature of the risks plants face unclear. Here we report the results of a global species assessment for the largest plant taxon evaluated to date under the International Union for Conservation of Nature (IUCN) Red List Categories and Criteria, the iconic Cactaceae (cacti). We show that cacti are among the most threatened taxonomic groups assessed to date, with 31% of the 1,478 evaluated species threatened, demonstrating the high anthropogenic pressures on biodiversity in arid lands. The distribution of threatened species and the predominant threatening processes and drivers are different to those described for other taxa. The most significant threat processes comprise land conversion to agriculture and aquaculture, collection as biological resources, and residential and commercial development. The dominant drivers of extinction risk are the unscrupulous collection of live plants and seeds for horticultural trade and private ornamental collections, smallholder livestock ranching and smallholder annual agriculture. Our findings demonstrate that global species assessments are readily achievable for major groups of plants with relatively moderate resources, and highlight different conservation priorities and actions to those derived from species assessments of key animal groups.

Prognostic value of DCE-MRI in breast cancer patients undergoing neoadjuvant chemotherapy: a comparison with traditional survival indicators.

OBJECTIVES: To determine associations between dynamic contrast-enhanced MR imaging (DCE-MRI) parameters and survival intervals in patients with locally advanced breast cancer treated with neoadjuvant chemotherapy (NAC), surgery, and adjuvant therapies. Further, to compare the prognostic value of DCE-MRI parameters against traditional survival indicators. METHODS: DCE-MRI and MR tumour volume measures were obtained prior to treatment and post 2nd NAC cycle. To demonstrate which parameters were associated with survival, Cox's proportional hazards models (CPHM) were employed. To avoid over-parameterisation, only those MR parameters with at least a borderline significant result were entered into the final CPHM. RESULTS: When considering disease-free survival positive axillary nodal status (hazard ratio [HR] 6.79), younger age (HR 3.37), negative oestrogen receptor status (HR 3.24), pre-treatment Maximum Enhancement Index (MaxEI) (HR 6.51), and percentage change in MaxEI (HR 1.02) represented the retained CPHM covariates. Similarly, positive axillary nodal status (HR 11.47), negative progesterone receptor status (HR 4.37) and percentage change in AUC90 (HR 1.01) represented the retained predictive variables for overall survival. CONCLUSIONS: Multivariate survival analysis has demonstrated that DCE-MRI parameters obtained prior to NAC and/or post 2nd cycle can provide independent prognostic information that can complement traditional prognostic indicators available prior to treatment. KEY POINTS: • MR-derived DCE-MRI parameters obtained prior to treatment have prognostic value. • Early treatment-induced reductions in DCE-MRI parameters represents a positive prognostic indicator. • DCE-MRI parameters provide independent prognostic information that can complement traditional prognostic indicators.

Analysis of prostate DCE-MRI: comparison of fast exchange limit and fast exchange regimen pharmacokinetic models in the discrimination of malignant from normal tissue.

OBJECTIVES: The ability to detect and identify malignant lesions within the prostate with conventional T2-weighted imaging is still limited. Although lesion conspicuity is improved with dynamic contrast-enhanced imaging there still remains some ambiguity as all tissues within the prostate may enhance. The aim of the current study was to take advantage of the improved signal-to-noise ratio at 3 T and assess the ability of 2 alternative pharmacokinetic models to clearly identify malignant areas within the prostate. We also aspire to assess the impact of tissue heterogeneity on variation in estimated pharmacokinetic parameters. MATERIALS AND METHODS: Quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the prostate was implemented using multiple flip angles for T1 determination, and a rapid dynamic 3D T1-weighted acquisition with parallel imaging and a temporal resolution of 6.7 s. Pharmacokinetic analysis was performed for regions of tumor, normal-appearing peripheral zone (PZ), and central gland (CG) using fast exchange limit (FXL) or fast exchange regimen (FXR) models. Cell density was obtained from hematoxylin and eosin stained whole mount radical prostatectomy specimens. RESULTS: Native tissue T1 was significantly lower in tumor and PZ tissue than in CG. The FXL model revealed increased mean K(trans), k(ep), and v(e) in tumor and CG compared with PZ. With the FXR model, fitting was improved and all parameters were significantly increased, however, there were no longer significant differences between regions for v(e). The additional parameter of the FXR model, tau(i), nominally representing mean lifetime of intracellular water, was significantly decreased in tumor compared with both PZ and CG. Rate constants for CG were significantly lower than those of tumor for both models. In addition, for all tissues, K(trans) and v(e) were positively correlated with cell density. CONCLUSIONS: Accounting for a finite water exchange rate between cells and their environment improves the discrimination of malignant from benign tissues within the prostate and may aid staging accuracy and ability to monitor response to treatment.

Description of magnetic resonance imaging-derived enhancement variables in pathologically confirmed prostate cancer and normal peripheral zone regions.

OBJECTIVE: To assess the use of a semiquantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to produce indices for enhancement curves that might enable differentiation between malignant prostatic lesions and normal peripheral zone (PZ). PATIENTS AND METHODS: Fifty-two patients scheduled for radical prostatectomy underwent DCE-MRI before surgery using a 3 T scanner. The DCE images were used to generate variables from changes in signal intensity for pathologically confirmed malignant areas and the normal PZ, using whole-mounted pathology specimens as a reference to delineate regions of interest (ROI). These variables included maximum enhancement index (MaxEI), time to MaxEI at 30 s, the initial and final slopes of signal intensity change, and the area under curve. A threshold value for each DCE variable was identified, and the sensitivity and specificity were obtained. RESULTS: Malignant lesions had a 56% higher MaxEI than normal PZ and took half the time to reach MaxEI (P<0.001). Hence, at 30 s, cancer lesions have double the mean (sd) EI than normal PZ, of 2.22 (1.04) vs 1.04 (0.51), respectively. Tumours showed significant washout of contrast medium, which was reflected in the final slope of the curve being negative, as opposed to positive for normal PZ. The combined data of DCE variables, using a logistic regression test, gave a mean (95% confidence interval) sensitivity and specificity of 89 (81-96)% and 90 (83-97)%, respectively. CONCLUSION: This technique provides good discrimination of malignant lesions that might enable accurate localisation of the lesion. It is a simple, semiquantitive, noninvasive method that reflects the unusual vascular characteristics of newly formed microvessels and the changes in the interstitium that occur in prostate cancer.

Prognostic value of pre-treatment DCE-MRI parameters in predicting disease free and overall survival for breast cancer patients undergoing neoadjuvant chemotherapy.

The purpose of this study was to investigate whether dynamic contrast enhanced MRI (DCE-MRI) data, both pharmacokinetic and empirical, can predict, prior to neoadjuvant chemotherapy, which patients are likely to have a shorter disease free survival (DFS) and overall survival (OS) interval following surgery. Traditional prognostic parameters were also included in the survival analysis. Consequently, a comparison of the prognostic value could be made between all the parameters studied. MR examinations were conducted on a 1.5 T system in 68 patients prior to the initiation of neoadjuvant chemotherapy. DCE-MRI consisted of a fast spoiled gradient echo sequence acquired over 35 phases with a mean temporal resolution of 11.3s. Both pharmacokinetic and empirical parameters were derived from the DCE-MRI data. Kaplan-Meier survival plots were generated for each parameter and group comparisons were made utilising logrank tests. The results from the 54 patients entered into the univariate survival analysis demonstrated that traditional prognostic parameters (tumour grade, hormonal status and size), empirical parameters (maximum enhancement index, enhancement index at 30s, area under the curve and initial slope) and adjuvant therapies demonstrated significant differences in survival intervals. Further multivariate Cox regression survival analysis revealed that empirical enhancement parameters contributed the greatest prediction of both DFS and OS in the resulting models. In conclusion, this study has demonstrated that in patients who exhibit high levels of perfusion and vessel permeability pre-treatment, evidenced by elevated empirical DCE-MRI parameters, a significantly lower disease free survival and overall survival can be expected.

Lesion T(2) relaxation times and volumes predict the response of malignant breast lesions to neoadjuvant chemotherapy.

The aim of this study was to investigate the utility of the water T(2) values of malignant breast lesions in predicting response after the first and second cycles of neoadjuvant chemotherapy (NAC), both alone and in combination with lesion volumes. Thirty-five patients were scanned before the commencement of chemotherapy and again after the first, second and final treatment cycles. Two methods of obtaining lesion T(2) were used: imaging, where a series of T(2)-weighted images was acquired (T(R)/T(E)=1000/30, 60, 90 and 120 ms), and spectroscopy, where the T(2) value of unsuppressed water signal was determined with a multiecho sequence (T(R)=1.5 s; initial T(E)=35 ms; 64 steps of 2.5 ms; 2 unsuppressed acquisitions per T(E)). Lesion volumes were computed from contrast-enhanced 3D fat-suppressed images. The study found that, using the imaging method of obtaining T(2), the ratio of the product of lesion T(2) and volume after the second cycle of NAC to pretreatment value is a good predictor of ultimate lesion response, defined as a > or =65% reduction in tumor volume after the final treatment cycle, with positive and negative predictive values of 95.5% and 84.6%, respectively.

Mechanism of action of octreotide in acromegalic tumours in vivo using dynamic contrast-enhanced magnetic resonance imaging.

CONTEXT: Octreotide causes significant tumour shrinkage in patients with acromegaly but the exact mechanism of action is unclear in vivo. OBJECTIVE: To determine the mechanism of action of octreotide in vivo using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). DESIGN: Five patients with acromegaly were treated with octreotide as primary medical therapy. DCE-MRI was done at baseline and 24 weeks. Local ethical committee approval was granted. SETTING: Study was done in a tertiary care centre. PATIENTS: Five patients with newly diagnosed acromegaly were recruited. INTERVENTION: Patients were started on subcutaneous octreotide and DCE-MRI was done on 0 and 24 weeks. MAIN OUTCOME MEASURES: Amplitude of contrast intake, exchange rate and maximum enhancement index of tumour tissue was compared before and after treatment. RESULTS: Amplitude of contrast intake (9.87 +/- 3.52 vs. 4.97 +/- 1.96 P < or = 0.05) and exchange rate (6.27 +/- 1.57 vs. 1.63 +/- 0.76 P value < or = 0.01) were significantly higher at baseline in adenoma compared to normal pituitary tissue but was comparable to normal pituitary tissue after treatment. There was a significant decrease in amplitude of contrast intake and exchange rate which relates to functional vascularity of adenoma at 24 weeks compared to baseline (P-values 0.026 and 0.002 respectively) but there were no significant changes in the normal pituitary tissue. CONCLUSION: DCE-MRI in acromegalic tumours treated with octreotide showed a significant reduction in functional vascularity after octreotide therapy compared to baseline in pituitary adenomas. This supports the antiangiogenic action of somatostatin analogue therapy in vitro, but it remains unclear if this mechanism is important clinically in analogue pre-treatment reducing the effect of radiotherapy on these pituitary tumours.

Effect of dopamine agonists on prolactinomas and normal pituitary assessed by dynamic contrast enhanced magnetic resonance imaging (DCE-MRI).

CONTEXT: Dopamine agonists (DA) may act on prolactinoma size and secretion through additional effects on adenoma vascularity that can be visualized using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). OBJECTIVE: We hypothesized that DAs may exert their effect through a change in tumour functional vascularity leading to a reduction of prolactin (PRL) levels and tumour size. SUBJECTS AND METHODS: To investigate this, 23 subjects were studied comprising five with macroprolactinomas, 11 with microprolactinomas, seven with non-lesion hyperprolactinemia and 15 normal volunteers (including five females on oral contraceptive pills). Patients with macroprolactinomas were treated with cabergoline 4 mg weekly and microprolactinomas were treated with quinagolide 75 microg daily for the duration of study. DCE-MRI was performed immediately pre-treatment and at 3-4 days, 1 and 3-4 months after treatment. Normal volunteers took three 75 microg quinagolide doses and were scanned pre-treatment and at 3 days. Data were analysed using the Brix model, producing a measure of vascular permeability and leakage space. RESULTS: PRL levels were significantly reduced in all patients and volunteers. Vascular parameters decreased significantly for four of five macroprolactinomas and all microprolactinomas which were maintained during the treatment period (p < 0.01). No changes were seen in normal volunteers or non-lesion hyperprolactinemia. One of five macroprolactinomas showed no change in either permeability or tumour size. CONCLUSION: Functional prolactinoma vascularity differs from non-lesion hyperprolactinemic pituitary and normal pituitary, and is responsive to DA therapy. The reduction in vascular parameters precedes shrinkage in macroprolactinomas, and if not seen within days of treatment may indicate DA resistance requiring early surgery.

Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer.

Traditionally, tumor response has been assessed via tumor size measurements during the course of a treatment. However, changes in these morphologically based measures occur relatively late in the course of a treatment. Alternative biomarkers are currently being evaluated to enable an earlier assessment of treatment to facilitate early cessation and cost savings. Diffusion-weighted imaging (DWI) has been identified by preclinical studies to be a likely alternative to tumor size measurements. In this study, 10 patients were examined prior to and after the first and second chemotherapy cycle time points. Longest diameter tumor measurements and apparent diffusion coefficients (ADCs) were recorded at each exam. An increase in the mean (normalized) ADC was noted as early as the first cycle time point. However, a reduction in the mean (normalized) longest diameter was only noted at the second cycle time point. Significant alterations from the baseline value were noted for ADC at the first (P=.005) and second cycle time points (P=.004). Longest diameter measurements only achieved a borderline significance at the second time point (P=.057). These results indicate that DWI may provide a suitable biomarker capable of providing an indication of response to treatment prior to tumor size measurements.

Role of dynamic contrast enhanced MRI in monitoring early response of locally advanced breast cancer to neoadjuvant chemotherapy.

Neoadjuvant chemotherapy has become the standard treatment for patients with locally advanced breast cancer; however a technique that can accurately differentiate responders from non-responders at an early time point during treatment has still to be identified. The purpose of this work was to evaluate the ability of pharmacokinetically modelled dynamic contrast-enhanced MRI data to predict and monitor response of patients diagnosed with locally advanced breast cancer to neoadjuvant chemotherapy, at an early time point during treatment. Sixty-eight patients with histology proven breast cancer underwent MRI examination prior to treatment, early during treatment and following the final cycle of chemotherapy. A two compartment pharmacokinetic model provided the kinetic parameters transfer constant (Ktrans), rate constant (Kep) and extracellular extravascular space (Ve) for a region of interest encompassing the whole lesion (ROIwhole) and a 3x3 pixel 'hot-spot' showing the greatest mean maximum percentage enhancement from within that region (ROIhs). Following treatment 48 patients were classified as responders and 20 as non-responders based on total tumour volume reduction. Tumour volume changes between the pre-treatment and early treatment time points demonstrated differences between responders and non-responders with percentage change revealing the most significant result (p<0.001). Analysis based on ROIhs provided more statistically significant differences between responders and non-responders then ROIwhole analysis. ROIhs analysis demonstrated differences between responders and non-responders both prior to and early during treatment. A highly significant reduction in both Ktrans and Kep (p<0.001) was noted for responders between the pre-treatment and early treatment time points, while Ve significantly increased during the same time period for non-responders (p<0.001). Quantification of dynamic contrast enhancement parameters provides a potential means for differentiating responders from non-responders early during their treatment, thereby allowing a prompt change in treatment if necessary.