NRG Oncology Updated International Consensus Atlas on Pelvic Lymph Node Volumes for Intact and Postoperative Prostate Cancer

Hall, William A.; Paulson, E.S.; Davis, Brian J.; Spratt, Daniel E.; Morgan, Todd M.; Dearnaley, David P.; Tree, A.; Efstathiou, Jason A.; Harisinghani, Mukesh G.; Jani, Ashesh B.; Buyyounouski, Mark K.; Pisansky, Thomas M.; Tran, Phuoc T.; Karnes, R. Jeffrey; Chen, Ronald C.; Cury, Fabio; Michalski, Jeff M.; Rosenthal, Seth A.; Koontz, Bridget F.; Wong, Anthony; Nguyen, Paul L.; Hope, Thomas A.; Feng, Felix Y.; Sandler, Howard M.; Lawton, C.A.

doi:10.1016/j.ijrobp.2020.08.034

Cited by 100 publications

(63 citation statements)

References 72 publications

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“…In addition, 50% (5/10) of patients with left common iliac metastases had nodal metastases outside the NRG consensus recommendation corresponding to 6.7% (5/75) of all patients, when using a standard margin of 7 mm around the vessels. The NRG consensus recommendation gives the option to increase this margin to 10 mm particularly anterior to vessels, if clinically indicated ( 15 ). However, even when using this more generous margin, still 20% (2/10) of patients with left common iliac involvement or 2.7% (2/75) of all patients had common iliac metastases outside the NRG consensus CTV volume, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Regions of controversy were subsequently identified by evaluating nodal CTVs from all experts and a consensus was reached. The inclusion of all common iliac nodes up to the aortic bifurcation in the new NRG CTV certainly is the most significant modification over the previous RTOG-GU recommendation ( 15 ). To the best of our knowledge, the present study is the first to analyze the coverage of pelvic nodal metastases according to the new NRG consensus recommendation.…”

Section: Discussionmentioning

confidence: 99%

“…Consistent with our finding that the perirectal level was the most frequently involved region outside the NRG consensus, the largest share of lesions missed by the previous RTOG-GU CTV recommendation (10/20) was also located in the perirectal region in a PSMA-PET–based patterns of failure analysis by Schiller and coauthors ( 12 ). While NRG GU experts thoroughly discussed the inclusion of perirectal levels especially for T4 tumors, the majority of experts had opted against routinely including these lymph nodes in view of the corresponding increase in treatment volume ( 15 ). As the perirectal region has been a frequent site of nodal recurrence in multiple studies ( 12 , 14 , 26 ), it would be highly beneficial to identify reliable predictive factors for perirectal involvement to include perirectal nodes in high-risk patients but to avoid unnecessary toxicity in others.…”

Section: Discussionmentioning

confidence: 99%

“…These circumstances can lead to possible misinterpretation of study results. In the present analysis, NRG consensus lymph node level definitions were used wherever possible to allow for optimal interpretation of results in regard to radiotherapy field design ( 15 ). For the same reason, if metastatic nodal involvement extended beyond the recent NRG consensus, e.g., to inguinal and perirectal regions, we chose RTOG compartment definitions from other cancer types.…”

Section: Discussionmentioning

confidence: 99%

“…The results were reviewed by a second radiation oncologist and confirmed in all cases. For the definition of lymph node levels, the NRG consensus recommendations were used except for perirectal and inguinal regions, where the RTOG consensus for anorectal cancer was employed as these regions are not included in the NRG consensus for prostate cancer ( 15 , 24 ).…”

Section: Methodsmentioning

confidence: 99%

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The Distribution of Pelvic Nodal Metastases in Prostate Cancer Reveals Potential to Advance and Personalize Pelvic Radiotherapy

et al. 2021

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BackgroundTraditional clinical target volume (CTV) definition for pelvic radiotherapy in prostate cancer consists of large volumes being treated with homogeneous doses without fully utilizing information on the probability of microscopic involvement to guide target volume design and prescription dose distribution.MethodsWe analyzed patterns of nodal involvement in 75 patients that received RT for pelvic and paraaortic lymph node metastases (LNs) from prostate cancer in regard to the new NRG-CTV recommendation. Non-rigid registration-based LN mapping and weighted three-dimensional kernel density estimation were used to visualize the average probability distribution for nodal metastases. As independent approach, the mean relative proportion of LNs observed for each level was determined manually and NRG and non-NRG levels were evaluated for frequency of involvement. Computer-automated distance measurements were used to compare LN distances in individual patients to the spatial proximity of nodal metastases at a cohort level.Results34.7% of patients had pelvic LNs outside NRG-consensus, of which perirectal was most common (25.3% of all patients) followed by left common iliac nodes near the left psoas major (6.7%). A substantial portion of patients (13.3%) had nodes at the posterior edge of the NRG obturator level. Observer-independent mapping consistently visualized high-probability hotspots outside NRG-consensus in the perirectal and left common iliac regions. Affected nodes in individual patients occurred in highly significantly closer proximity than at cohort-level (mean distance, 6.6 cm vs. 8.7 cm, p < 0.001).ConclusionsBased on this analysis, the common iliac level should extend to the left psoas major and obturator levels should extend posteriorly 5 mm beyond the obturator internus. Incomplete coverage by the NRG-consensus was mostly because of perirectal involvement. We introduce three-dimensional kernel density estimation after non-rigid registration-based mapping for the analysis of recurrence data in radiotherapy. This technique provides an estimate of the underlying probability distribution of nodal involvement and may help in addressing institution- or subgroup-specific differences. Nodal metastases in individual patients occurred in highly significantly closer proximity than at a cohort-level, which supports that personalized target volumes could be reduced in size compared to a “one-size-fits-all” approach and is an important basis for further investigation into individualized field designs.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

The Distribution of Pelvic Nodal Metastases in Prostate Cancer Reveals Potential to Advance and Personalize Pelvic Radiotherapy

et al. 2021

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Evaluation of Hypofractionated Radiation Therapy Use and Patient-Reported Outcomes in Men With Nonmetastatic Prostate Cancer in Australia and New Zealand

et al. 2021

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Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application

Wen,

Chen,

Wang

et al. 2024

J Applied Clin Med Phys

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BackgroundRadiotherapy has been crucial in prostate cancer treatment. However, manual segmentation is labor intensive and highly variable among radiation oncologists. In this study, a deep learning based automated contouring model is constructed for clinical target volumes (CTVs) of intact and postoperative prostate cancer.MethodsComputed tomography (CT) data sets of 197 prostate cancer patients were collected. Two auto‐delineation models were built for radical radiotherapy and postoperative radiotherapy of prostate cancer respectively, and each model included CTVn for pelvic lymph nodes and CTVp for prostate tumors or prostate tumor beds.ResultsIn the radical radiotherapy model, the volumetric dice (VD) coefficient of CTVn calculated by AI, was higher than that of the one delineated by the junior physicians (0.85 vs. 0.82, p = 0.018); In the postoperative radiotherapy model, the quantitative parameter of CTVn and CTVp, counted by AI, was better than that of the junior physicians. The median delineation time for AI was 0.23 min in the postoperative model and 0.26 min in the radical model, which were significantly shorter than those of the physicians (50.40 and 45.43 min, respectively, p < 0.001). The correction time of the senior physician for AI was much shorter compared with that for the junior physicians in both models (p < 0.001).ConclusionUsing deep learning and attention mechanism, a highly consistent and time‐saving contouring model was built for CTVs of pelvic lymph nodes and prostate tumors or prostate tumor beds for prostate cancer, which also might be a good approach to train junior radiation oncologists.

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NRG Oncology Updated International Consensus Atlas on Pelvic Lymph Node Volumes for Intact and Postoperative Prostate Cancer

Cited by 100 publications

References 72 publications

The Distribution of Pelvic Nodal Metastases in Prostate Cancer Reveals Potential to Advance and Personalize Pelvic Radiotherapy

The Distribution of Pelvic Nodal Metastases in Prostate Cancer Reveals Potential to Advance and Personalize Pelvic Radiotherapy

Evaluation of Hypofractionated Radiation Therapy Use and Patient-Reported Outcomes in Men With Nonmetastatic Prostate Cancer in Australia and New Zealand

Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application

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