High-Percentage of Early Resectable Pancreatic Ductal Adenocarcinoma is Unidentified on Abdominal CT Obtained for Unrelated Diagnosis

High-Percentage of Early Resectable Pancreatic Ductal Adenocarcinoma is Unidentified on Abdominal CT Obtained for Unrelated Diagnosis

Review Data

Q: Is the topic relevant to the journal area of interest? Is it contemporary and interesting for

researchers?

A: Good

 

Abstract & Keywords

Q: Are all required components included in the abstract? Are the keywords appropriately chosen?

A: Very Good

Comments: Since the Abstract was exceeding the word limit (according to the guidelines) it had to be trimmed.

 

Goal

Q: Is the goal explicitly stated in the Introduction? Is its formulation clear and unambiguous?

A: Very Good

 

Structure

Q: Is the paper's structure coherent? Is it in coherence with the goal of the paper?

A: Very Good

 

Tools and Methods

Q: Are methods the author uses adequate and well used?

A: Good

 

Discussion & Conclusion

Q: Is it related to the results presented before? Do you consider them as coherent?

A: Good

 

Comments: The Discussion establishes the importance of identifying the potential features of pancreatic ductal adenocarcinoma (PDAC) as early as possible, particularly in studies where pancreatic cancer is not suspected. It illustrates the early features of PDAC, which are critical for early diagnosis. The Discussion highlights the potential benefits derived from screening for PDAC while also focusing on the associated challenge. Although novel biomarkers for PDAC are currently being studied, nothing has yet been identified as sensitive and specific for early disease detection. The Discussion highlights that computed tomography (CT) is more accurate in determining tumor resectability. Data previously reported and of this study suggest that contrast-enhanced imaging is superior for diagnostic purposes. The study concludes that improving detection of early PDAC features on routine CT can potentially impact patient outcomes.

 

Literature

Q: Does the author utilize relevant literature?

A: Good

 

Author's knowledge

Q: What is the level of author’s knowledge? Does the author utilize all recent contributions relevant to the topic?

A: Good

 

Length

Q: Is the length of the paper adequate to the significance of the topic? Do you suggest shortening the paper without losing its value?

A: Good

 

Figures & Tables

Q: Does the author use them suitably? Are legend and notations clear?

A: Good

 

Writing style

Q: Is it clear and understandable?

A: Good

 

Further comments on the paper

Comments: This retrospective study aims at evaluating pre-diagnostic images, identifying the rate of under-detection for features of early pancreatic ductal adenocarcinoma (PDAC), and estimating the change in tumor resectability with delayed diagnoses. PDAC has high mortality when diagnosed late and currently, the best treatment for PDAC is early resection. The study evaluated 76 imaging studies on patients with PDAC prior to their diagnosis. Although there are several options for imaging, the most commonly used first-line modality is computed tomography (CT). The results of this study highlight the importance of identifying the potential features of PDAC as early as possible, particularly in studies where pancreatic cancer is not suspected. The findings of this study are clinically relevant as these imaging studies were acquired from community hospitals. The study illustrates that a real-time second observer is the most effective at improving detection, although the least cost-effective. The study concludes that improving detection of early PDAC features on routine CT can potentially impact patient outcomes. It illustrates the key CT features that will help during CT screening for abdominal symptoms. The development of computer-aided detection of PDAC is needed in the future.

 

Q: Would you recommend this manuscript for further publication?

A: Yes - Suitable to be published

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Author Info

Corresponding Author
John C. Chang
Department of Radiology, Banner MD Anderson Cancer Center, Gilbert, Arizona, USA

Article Info

Article Type
Research Article
Publication history
Received: Thu 09, Dec 2021
Accepted: Mon 27, Dec 2021
Published: Fri 31, Dec 2021
Copyright
© 2023 John C. Chang. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Hosting by Science Repository.
DOI: 10.31487/j.ACO.2021.02.03