857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery

2018 ◽  
Vol 154 (6) ◽  
pp. S-1289
Author(s):  
Jacob Antunes ◽  
Amrish Selvam ◽  
Kaustav Bera ◽  
Justin Brady ◽  
Joseph Willis ◽  
...  
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Inês Santiago ◽  
Bernardete Rodrigues ◽  
Maria Barata ◽  
Nuno Figueiredo ◽  
Laura Fernandez ◽  
...  

AbstractIn the past nearly 20 years, organ-sparing when no apparent viable tumour is present after neoadjuvant therapy has taken an increasingly relevant role in the therapeutic management of locally-advanced rectal cancer patients. The decision to include a patient or not in a “Watch-and-Wait” program relies mainly on endoscopic assessment by skilled surgeons, and MR imaging by experienced radiologists. Strict surveillance using the same modalities is required, given the chance of a local regrowth is of approximately 25–30%, almost always surgically salvageable if caught early. Local regrowths occur at the endoluminal aspect of the primary tumour bed in almost 90% of patients, but the rest are deep within it or outside the rectal wall, in which case detection relies solely on MR Imaging. In this educational review, we provide a practical guide for radiologists who are, or intend to be, involved in the re-staging and follow-up of rectal cancer patients in institutions with an established “Watch-and-Wait” program. First, we discuss patient preparation and MR imaging acquisition technique. Second, we focus on the re-staging MR imaging examination and review the imaging findings that allow us to assess response. Third, we focus on follow-up assessments of patients who defer surgery and confer about the early signs that may indicate a sustained/non-sustained complete response, a rectal/extra-rectal regrowth, and the particular prognosis of the “near-complete” responders. Finally, we discuss our proposed report template.


2020 ◽  
Vol 152 ◽  
pp. S573-S574
Author(s):  
A. Re ◽  
V. Picardi ◽  
F. Deodato ◽  
A. Ianiro ◽  
S. Cilla ◽  
...  

2015 ◽  
Vol 17 (7) ◽  
pp. 595-599 ◽  
Author(s):  
C. Shwaartz ◽  
N. Haim ◽  
D. Rosin ◽  
Y. Lawrence ◽  
M. Gutman ◽  
...  

2019 ◽  
Vol 51 (2) ◽  
pp. 610-610
Author(s):  
Sajad P. Shayesteh ◽  
Afsaneh Alikhassi ◽  
Farshid Farhan ◽  
Reza Ghalehtaki ◽  
Masume Soltanabadi ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jiazhou Wang ◽  
Lijun Shen ◽  
Haoyu Zhong ◽  
Zhen Zhou ◽  
Panpan Hu ◽  
...  

Abstract This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients’ radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment.


2019 ◽  
Vol 45 (2) ◽  
pp. e43
Author(s):  
K. Balog ◽  
Z. Kanyári ◽  
M. Tanyi ◽  
Z. Szentkereszty ◽  
L. Orosz ◽  
...  

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