Amber Jones

A phase 2 study of the safety, tolerability and pharmacodynamics of FBS0701, a novel oral iron chelator, in transfusional iron overload

This was a 24-week, multicenter phase-2 study designed to assess safety, tolerability, and pharmacodynamics of FBS0701, a novel oral chelator, in adults with transfusional iron overload. Fifty-one patients, stratified by transfusional iron intake, were randomized to FBS0701 at either 14.5 or 29 mg/kg/d (16 and 32 mg/kg/d salt form). FBS0701 was generally well tolerated at both doses. Forty-nine patients (96%) completed the study. There were no drug-related serious adverse events. No adverse events (AEs) showed dose-dependency in frequency or severity. Treatment-related nausea, vomiting, abdominal pain, and diarrhea were each noted in < 5% of patients. Mean serum creatinine did not change significantly from Baseline or between dose groups. Transaminases wer increased in 8 (16%), three of whom acquired HCV on-study from a single blood bank while five had an abnormal baseline ALT. The 24 week mean change in liver iron concentration (ΔLIC) at 14.5 mg/kg/d was +3.1 mg/g (dw); 29% achieved a decrease in LIC. Mean ΔLIC at 29 mg/kg/d was -0.3 mg/g (dw); 44% achieved a decrease in LIC (P < .03 for ΔLIC between doses). The safety and tolerability profile at therapeutic doses compare favorably to other oral chelators.

The use of appropriate calibration curves corrects for systematic differences in liver R2* values measured using different software packages.

Precise, reproducible measurements of liver iron concentration (LIC) are critical for the early diagnosis, treatment and follow-up of patients with primary or secondary iron overload. Magnetic resonance imaging (MRI), which exploits the paramagnetic properties of iron, has gained acceptance as a noninvasive and accurate tool for LIC assessment. Two different techniques have been described: methods measuring signal intensity ratio between liver and muscles (Gandon, et al 2004), and relaxometry methods measuring absolute R2 (St Pierre, et al 2005) or R2* (Wood, et al 2005) values, which increase proportionally to iron concentration. The gradient-echo R2* technique is most widely used in clinical practice (Anderson, et al 2001, Hankins, et al 2009, Meloni, et al 2011, Wood, et al 2005), because it is faster and easier than R2 acquisition. R2* values can be converted to underlying tissue iron concentration, using appropriate calibration curves. The first calibration curve was proposed by Anderson et al (2001) and later updated by Garbowski et al (2009). This methodology has been implemented in a popular analysis software named “ThalassaemiaTools”, a CMRtools (Cardiovascular Imaging Solutions Ltd, London, UK) plug-in. A second calibration curve was proposed (Wood et al 2005) and later confirmed (Hankins et al 2009), but it demonstrated a 15% lower scaling coefficient between R2* and LIC. The two R2* analysis methods differ in the size of analysed region of interest (ROI) and the model used to fit the signal decay at different echo times. A systematic comparison of R2* and LIC values obtained with the two methodologies has never been reported. This study aimed to detect the potential differences in R2* values obtained with different post-processing approaches and to explore whether the detected differences would be corrected when converted into LIC values. Single- and multi-centre patient cohorts were used. The single-centre cohort included 45 patients (25 males, 16.4±10.2 years) scanned at the Children’s Hospital of Los Angeles (CHLA). The multi-centre cohort (N=47; 19 females, 28.1±8.9 years) was baseline data from a phase II clinical trial of the iron chelator FBS0701 and was included to obtain higher generalizability The study was approved by the CHLA Committee for the Protection of Human Subjects and the institutional review boards of all participating hospitals. With the ThalassaemiaTools, a ROI was defined in an area of homogeneous liver tissue. All pixels were averaged together and fit to a single-exponential model. Later echo times were manually excluded from the fit in images where iron-mediated signal loss was high (Figures 1a–1b). R2* values (=1000/T2*) were converted into LIC by (Garbowski, et al 2009): LICPennell=0.03·R2*Pennell+0.7 [Equation 1] Figure 1 a) and b) Screenshot of CMRtools software (region of interest definition in the left and signal decay fitting in the right) for a patient with moderate iron overload and for a patient with severe iron overload, respectively. For the patient with severe ... In our laboratory R2* measurements were performed using a custom-written software. The ROI included the entire liver profile in the slice, excluding the major hilar vessels. The signal in each pixel was fit to an exponential-plus-constant model, producing a R2* map (Figure 1c). The mean was calculated (R2*Wood). LIC values (LICWood) were calculated as: LICWood=0.0254·R2*Wood+0.2 [Equation 2] R2* assessment, by either method, is limited to LIC<40 mg/g because rapid signal decay precludes adequate characterization of the relaxation curve for higher iron concentrations. In order to compare the two approaches linear regression analysis and Bland-Altman technique were used. The results are indicated in Table I and Supplemental Figures 1, 2. Table 1 Comparison between R2*Wood and R2*Pennell values and between LICWood and LICPennell values for the two cohorts of patients. LIC values are expressed also in µmol/g/dw, calculated from values expressed in mg/g/dw. For both the cohorts the relationship between R2*Wood and R2*Pennell values was well described by a line. Results were unbiased for R2* R2*Pennell value. For the multi-centre cohort the mean difference was 59.5±76.7 Hz (95%CI, 36.9–81.9 Hz), corresponding to a relative difference of 8.5±13.8%. When the technique-appropriate calibration curves were used, this bias effectively disappeared, producing excellent agreement between the two approaches. For the single-centre cohort the mean difference was −0.8±1.5 mg/g/dry weight (dw) (95%CI, −1.3 to −0.3 mg/g/dw). Individual LIC estimates had 95%CI from −3.8 to 2.2 mg/g/dw. For the multi-centre cohort the mean difference was −1.0±1.4 mg/g/dw (95%CI, −1.4 to −0.6 mg/g/dw), indicating a small, systematic bias. Individual LIC estimates had 95%CI of −3.8 to 1.8 mg/g/dw. There is ongoing discussion as to which of the two decay models most closely describes the true tissue relaxation. By simulation (true value known), the key determinant is whether there is any other signal contribution besides iron. If there is any background signal from non-iron containing tissue, the exponential-plus-constant model is more accurate (Positano, et al 2009). If there is no signal contribution from bile, blood or fat, the truncated exponential is more appropriate (Beaumont, et al 2009). Given that the two approaches sample the liver differently, one could potentially attribute the observed R2* differences to systematic gradients in iron distribution with proximity to the hilum. This was demonstrated to be untrue (McCarville, et al 2010, Positano, et al 2009). The 0.8–1 mg/g residual bias between the two LIC estimates is clinically irrelevant at higher values, but could be important when assessing the risk of over chelation. Some of the bias is evident from inspection of Equations 1 and 2; the calibration curves have a 0.5 mg/g difference in y-intercept. To ensure good extrapolation into normal iron levels, the y-intercept in Equation 2 was constrained such that the calibration curve passes through the middle of the normal range (Wood, et al 2005), while Equation 1 was not. To illustrate the potential consequences of this difference, R2* values in healthy volunteers are typically reported to be 30–40 Hz. Equation 2 predicts LIC values of 1.0–1.2 mg/g and Equation 1 predicts LIC values of 1.4–1.6 mg/g. Practitioners who use Equation 1 should know that “normal” LIC corresponds to a value around 1.5 mg/g and base their therapeutic judgments about that set-point. In conclusion, both signal decay models yield clinically-acceptable estimates of LIC if the ROI’s are drawn correctly and the proper calibration curve is applied to correct for systematic differences in R2* estimation. Proper choice of technique at any given institution will depend on software availability and training. However, in the literature, R2* values should be converted into LIC values using the appropriate calibration curve to facilitate comparisons across studies.

Fast approximation to pixelwise relaxivity maps: validation in iron overloaded subjects.

PURPOSE Liver iron quantification by MRI has become routine. Pixelwise (PW) fitting to the iron-mediated signal decay has some advantages but is slower and more vulnerable to noise than region-based techniques. We present a fast, pseudo-pixelwise mapping (PPWM) algorithm. MATERIALS AND METHODS The PPWM algorithm divides the entire liver into non-contiguous groups of pixels sorted by rapid relative relaxivity estimates. Pixels within each group of like-relaxivity were binned and fit using a Levenberg-Marquadt algorithm. RESULTS The developed algorithm worked about 30 times faster than the traditional PW approach and generated R2* maps qualitatively and quantitatively similar. No systematic difference was observed in median R2* values with a coefficient of variability (CoV) of 2.4%. Intra-observer and inter-observer errors were also under 2.5%. Small systematic differences were observed in the right tail of the R2* distribution resulting in slightly lower mean R2* values (CoV of 4.2%) and moderately lower SD of R2* values for the PPWM algorithm. Moreover, the PPWM provided the best accuracy, giving a lower error of R2* estimates. CONCLUSION The PPWM yielded comparable reproducibility and higher accuracy than the TPWM. The method is suitable for relaxivity maps in other organs and applications.

Cardiac R2* values are independent of the image analysis approach employed.

To determine whether systematic differences were present between myocardial R2* values obtained with two different decay models: truncation and exponential + constant (Exp‐C).

Are cardiac R2* values dependent on the image analysis approach employed?

Background CMR R2* is the gold standard for monitoring cardiac iron overload in patients with hemoglobinopathies. The R2* value is obtained by fitting the signal at different echo times (TEs) to an appropriate decay model. Patients with heavy cardiac iron burden (R2*>100 Hz) exhibit rapid signal, leading to a plateau in the later images. Two approaches have been used to address this. The first one (truncation model) consists in discarding the late “plateau” points and fitting the remaining ones with a single exponential model. The second approach is to fit the signal to an exponential decay plus a constant offset (Exp-C). We aimed to determine whether systematic differences were present between R2* values obtained with these two approaches. Methods Single-center cohorts were used to compare black blood and bright sequences separately and a multi-center cohort of mixed bright and black blood studies was used to compare robustness and generalizability of the comparison. The R2* value within a region of interest (ROI) drawn in mid-ventricular septum was assessed using each of the two methods in turn. Truncated exponential estimates were calculated with CMRTools that uses a region-based approach (R2*CMRTools). Exp-C estimates were calculated using a rapid pseudo-pixelwise (PPW) implementation written in MATLAB. The mean and the median (R2*PPW-mean and R2*PPW-median) from the R2* distribution were obtained. To distinguish whether differences in measured R2* values resulted from the underlying fitting model or from the use of a PPW rather than a region-based approach, we performed Exp-C fits to a single ROI (R2*PPW-ROI_based). Results Table 1 shows the results for the two methods. No differences could be distinguished based upon whether a white or black blood sequence was examined. The two fitting algorithms gave similar R2* values, with R-squared values exceeding 0.997 and CoV of 3-4%. Results using the PPW method yielded a small systematic bias that became apparent in patients with severe iron deposition. This disparity disappeared when Exp+C fitting was used on a single ROI suggesting that the use of pixelwise mapping was responsible for 3% bias. In the multicenter cohort the strong agreement between R2* values obtained with the two approaches was reconfirmed. Conclusions Cardiac R2* values are independent of the signal model used for its calculation over clinically relevant ranges; pixelwise fitting generate insignificantly greater R2* estimates at high iron concentrations. The overall variability between the techniques is exceeding small allowing clinicians to compare results with confidence.

Cardiac R2* values are independent of the image analysis approach employed: Algorithms for Cardiac R2* Assessment

To determine whether systematic differences were present between myocardial R2* values obtained with two different decay models: truncation and exponential + constant (Exp‐C).

Cardiac R2* values are independent on the image analysis approach employed

To determine whether systematic differences were present between myocardial R2* values obtained with two different decay models: truncation and exponential + constant (Exp‐C).