diff --git a/petric.py b/petric.py
index 42bb270..a240530 100755
--- a/petric.py
+++ b/petric.py
@@ -27,7 +27,7 @@
 
 import sirf.STIR as STIR
 from cil.optimisation.algorithms import Algorithm
-from cil.optimisation.utilities import callbacks as cbks
+from cil.optimisation.utilities import callbacks as cil_callbacks
 from img_quality_cil_stir import ImageQualityCallback
 
 log = logging.getLogger('petric')
@@ -38,17 +38,31 @@
     SRCDIR = Path("./data")
 
 
-class SaveIters(cbks.Callback):
+class Callback(cil_callbacks.Callback):
+    """
+    CIL Callback but with `self.skip_iteration` checking `min(self.interval, algo.update_objective_interval)`.
+    TODO: backport this class to CIL.
+    """
+    def __init__(self, interval: int = 1 << 31, **kwargs):
+        super().__init__(**kwargs)
+        self.interval = interval
+
+    def skip_iteration(self, algo: Algorithm) -> bool:
+        return algo.iteration % min(self.interval,
+                                    algo.update_objective_interval) != 0 and algo.iteration != algo.max_iteration
+
+
+class SaveIters(Callback):
     """Saves `algo.x` as "iter_{algo.iteration:04d}.hv" and `algo.loss` in `csv_file`"""
-    def __init__(self, verbose=1, outdir=OUTDIR, csv_file='objectives.csv'):
-        super().__init__(verbose)
+    def __init__(self, outdir=OUTDIR, csv_file='objectives.csv', **kwargs):
+        super().__init__(**kwargs)
         self.outdir = Path(outdir)
         self.outdir.mkdir(parents=True, exist_ok=True)
         self.csv = csv.writer((self.outdir / csv_file).open("w", buffering=1))
         self.csv.writerow(("iter", "objective"))
 
     def __call__(self, algo: Algorithm):
-        if algo.iteration % algo.update_objective_interval == 0 or algo.iteration == algo.max_iteration:
+        if not self.skip_iteration(algo):
             log.debug("saving iter %d...", algo.iteration)
             algo.x.write(str(self.outdir / f'iter_{algo.iteration:04d}.hv'))
             self.csv.writerow((algo.iteration, algo.get_last_loss()))
@@ -57,10 +71,10 @@ def __call__(self, algo: Algorithm):
             algo.x.write(str(self.outdir / 'iter_final.hv'))
 
 
-class StatsLog(cbks.Callback):
+class StatsLog(Callback):
     """Log image slices & objective value"""
-    def __init__(self, verbose=1, transverse_slice=None, coronal_slice=None, vmax=None, logdir=OUTDIR):
-        super().__init__(verbose)
+    def __init__(self, transverse_slice=None, coronal_slice=None, vmax=None, logdir=OUTDIR, **kwargs):
+        super().__init__(**kwargs)
         self.transverse_slice = transverse_slice
         self.coronal_slice = coronal_slice
         self.vmax = vmax
@@ -68,7 +82,7 @@ def __init__(self, verbose=1, transverse_slice=None, coronal_slice=None, vmax=No
         self.tb = logdir if isinstance(logdir, SummaryWriter) else SummaryWriter(logdir=str(logdir))
 
     def __call__(self, algo: Algorithm):
-        if algo.iteration % algo.update_objective_interval != 0 and algo.iteration != algo.max_iteration:
+        if self.skip_iteration(algo):
             return
         log.debug("logging iter %d...", algo.iteration)
         # initialise `None` values
@@ -89,21 +103,22 @@ def __call__(self, algo: Algorithm):
         log.debug("...logged")
 
 
-class QualityMetrics(ImageQualityCallback):
+class QualityMetrics(ImageQualityCallback, Callback):
     """From https://github.com/SyneRBI/PETRIC/wiki#metrics-and-thresholds"""
-    def __init__(self, reference_image, whole_object_mask, background_mask, **kwargs):
-        super().__init__(reference_image, **kwargs)
+    def __init__(self, reference_image, whole_object_mask, background_mask, interval: int = 1 << 31, **kwargs):
+        # TODO: drop multiple inheritance once `interval` included in CIL
+        Callback.__init__(self, interval=interval)
+        ImageQualityCallback.__init__(self, reference_image, **kwargs)
         self.whole_object_indices = np.where(whole_object_mask.as_array())
         self.background_indices = np.where(background_mask.as_array())
         self.ref_im_arr = reference_image.as_array()
         self.norm = self.ref_im_arr[self.background_indices].mean()
 
     def __call__(self, algo: Algorithm):
-        iteration = algo.iteration
-        if iteration % algo.update_objective_interval != 0 and iteration != algo.max_iteration:
+        if self.skip_iteration(algo):
             return
         for tag, value in self.evaluate(algo.x).items():
-            self.tb_summary_writer.add_scalar(tag, value, iteration)
+            self.tb_summary_writer.add_scalar(tag, value, algo.iteration)
 
     def evaluate(self, test_im: STIR.ImageData) -> dict[str, float]:
         assert not any(self.filter.values()), "Filtering not implemented"
@@ -120,16 +135,16 @@ def evaluate(self, test_im: STIR.ImageData) -> dict[str, float]:
         return {**whole, **local}
 
 
-class MetricsWithTimeout(cbks.Callback):
+class MetricsWithTimeout(cil_callbacks.Callback):
     """Stops the algorithm after `seconds`"""
-    def __init__(self, seconds=300, outdir=OUTDIR, transverse_slice=None, coronal_slice=None, verbose=1):
-        super().__init__(verbose)
+    def __init__(self, seconds=300, outdir=OUTDIR, transverse_slice=None, coronal_slice=None, **kwargs):
+        super().__init__(**kwargs)
         self._seconds = seconds
         self.callbacks = [
-            cbks.ProgressCallback(),
+            cil_callbacks.ProgressCallback(),
             SaveIters(outdir=outdir),
             (tb_cbk := StatsLog(logdir=outdir, transverse_slice=transverse_slice, coronal_slice=coronal_slice))]
-        self.tb = tb_cbk.tb
+        self.tb = tb_cbk.tb # convenient access to the underlying SummaryWriter
         self.reset()
 
     def reset(self, seconds=None):