Title: Nuclear morphometry and chromatin texture changes in hepatocellular carcinoma samples
may predict liver transplant patients’ outcomes
Version: 2 Date: 20 Feb 2022
Reviewer's report:
The study by Jordan Boeira dos Santos et al tries to establish a relationship between
different parameters used to morphometrically assess nuclear and chromatin texture changes in
hepatocellular carcinoma (HCC) tissue samples and the outcome of liver transplant patients.
The authors used the image processing software ImageJ and an add-on for calculating fractal
dimension (FD). The study found several useful parameters  in discriminating between HCC
and surrounding tissue cellular nuclei. From those, only some could be correlated with survival
and survival-related parameters.
Some points that need addressing:
1. The authors state that 34 individuals were included, of whom 19 were male and 12 female,
reaching 100%. Three participants seem to be lost, while percentages still add up to 100.
2. The authors state that 20 samples were excluded as they could cause depletion of the material
stored, two more further excluded due to incomplete data records. Are these supplemental to the
34 included? If so, please provide a workflow diagram in order to understand the selection.
3. Please indicate the scale in figure 1.
4. Please consider adding a figure depicting binarization used for FD calculation. Properly
obtaining the masks by binarization is essential for calculating accurate FDs.
5. Please explain what "20 cores" refers to when stating that it took 40 minutes (per case? in
total?)
6. What is the difference between "hepatocellular" and "neoplastic" nuclei?
7. It is stated that only nuclei "with not sharp nuclear boundaries" were excluded. If one nucleus
was partially obstructed by another, but with a clear boundary, were both included in the
calculation, or only the suprajacent one?
8. Why only one image per case? Selecting an image with a high concentration of nuclei (above
20, as stated) did not introduce an unwanted bias in the analysis?
Title: Nuclear morphometry and chromatin texture changes in hepatocellular carcinoma samples
may predict liver transplant patients’ outcomes
Version: 2 Date: 20 Feb 2022
Reviewer's report:
The study by Jordan Boeira dos Santos et al tries to establish a relationship between
different parameters used to morphometrically assess nuclear and chromatin texture changes in
hepatocellular carcinoma (HCC) tissue samples and the outcome of liver transplant patients.
The authors used the image processing software ImageJ and an add-on for calculating fractal
dimension (FD). The study found several useful parameters  in discriminating between HCC
and surrounding tissue cellular nuclei. From those, only some could be correlated with survival
and survival-related parameters.
Some points that need addressing:
1. The authors state that 34 individuals were included, of whom 19 were male and 12 female,
reaching 100%. Three participants seem to be lost, while percentages still add up to 100.
2. The authors state that 20 samples were excluded as they could cause depletion of the material
stored, two more further excluded due to incomplete data records. Are these supplemental to the
34 included? If so, please provide a workflow diagram in order to understand the selection.
3. Please indicate the scale in figure 1.
4. Please consider adding a figure depicting binarization used for FD calculation. Properly
obtaining the masks by binarization is essential for calculating accurate FDs.
5. Please explain what "20 cores" refers to when stating that it took 40 minutes (per case? in
total?)
6. What is the difference between "hepatocellular" and "neoplastic" nuclei?
7. It is stated that only nuclei "with not sharp nuclear boundaries" were excluded. If one nucleus
was partially obstructed by another, but with a clear boundary, were both included in the
calculation, or only the suprajacent one?
8. Why only one image per case? Selecting an image with a high concentration of nuclei (above
20, as stated) did not introduce an unwanted bias in the analysis?
Please review this paper.
user
Title: Nuclear morphometry and chromatin texture changes in hepatocellular carcinoma samples
may predict liver transplant patients’ outcomes
Version: 2 Date: 20 Feb 2022
Reviewer's report:
The study by Jordan Boeira dos Santos et al tries to establish a relationship between
different parameters used to morphometrically assess nuclear and chromatin texture changes in
hepatocellular carcinoma (HCC) tissue samples and the outcome of liver transplant patients.
The authors used the image processing software ImageJ and an add-on for calculating fractal
dimension (FD). The study found several useful parameters  in discriminating between HCC
and surrounding tissue cellular nuclei. From those, only some could be correlated with survival
and survival-related parameters.
Some points that need addressing:
1. The authors state that 34 individuals were included, of whom 19 were male and 12 female,
reaching 100%. Three participants seem to be lost, while percentages still add up to 100.
2. The authors state that 20 samples were excluded as they could cause depletion of the material
stored, two more further excluded due to incomplete data records. Are these supplemental to the
34 included? If so, please provide a workflow diagram in order to understand the selection.
3. Please indicate the scale in figure 1.
4. Please consider adding a figure depicting binarization used for FD calculation. Properly
obtaining the masks by binarization is essential for calculating accurate FDs.
5. Please explain what "20 cores" refers to when stating that it took 40 minutes (per case? in
total?)
6. What is the difference between "hepatocellular" and "neoplastic" nuclei?
7. It is stated that only nuclei "with not sharp nuclear boundaries" were excluded. If one nucleus
was partially obstructed by another, but with a clear boundary, were both included in the
calculation, or only the suprajacent one?
8. Why only one image per case? Selecting an image with a high concentration of nuclei (above
20, as stated) did not introduce an unwanted bias in the analysis?
assistant