Restaging oesophageal cancer after neoadjuvant therapy with 18F-FDG PET-CT: identifying interval metastases and predicting incurable disease at surgery

Findlay, John M.; Gillies, Richard; Franklin, James; Teoh, Eugene; Jones, Greg; Carlo, Sara Di; Gleeson, Fergus; Maynard, Nicholas; Bradley, Kevin M.; Middleton, Mark R.

doi:10.1007/s00330-016-4227-4

Cited by 26 publications

(28 citation statements)

References 38 publications

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“…Patients with avid nodal metastases following NAC had twice as poor a prognosis as those with non‐avid metastases. In the authors' previous study, these patients had a 25·6 per cent risk of occult unresectable disease and an abandoned resection. It now seems that patients in whom resection can be performed still have a very poor prognosis.…”

Section: Discussionmentioning

confidence: 93%

Metabolic nodal response as a prognostic marker after neoadjuvant therapy for oesophageal cancer

Findlay

Bradley

Wang

et al. 2017

British Journal of Surgery

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Section: Discussionmentioning

confidence: 93%

Metabolic nodal response as a prognostic marker after neoadjuvant therapy for oesophageal cancer

Findlay

Bradley

Wang

et al. 2017

British Journal of Surgery

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“…Categories were based on previously published cut-off points or estimated by receiver operating characteristic (ROC) curve analysis while maximizing sensitivity and specificity. Clinical factors available before initiation of treatment that have previously been identified as prognostic factors in oesophageal cancer included gender [19], age (dichotomized into <65 and ≥ 65) [20], Histology (adenocarcinoma versus squamous cell carcinoma [3, 20], histologic differentiation grade (good/moderate versus poor) [20, 21], signet ring cell adenocarcinoma [22, 23], EUS-based tumor length (dichotomized into <4.0 cm and ≥ 4.0 cm) [24, 25], nontraversability by EUS [15, 24], tumor location (upper/middle versus distal or gastro-oesophageal junction) [18], clinical T-status (T1b-2 versus T3–4) [19, 20], clinical N status (N0 versus N1–3) [20, 21], maximum lymph node diameter measured on axial CT image (<1.0 cm versus ≥1 cm) [26, 27], and 18 F-FDG avid nodes at baseline PET [15]. The maximum standardized uptake value (SUV max ) of the primary tumor was dichotomized into <9.6 and ≥ 9.6 based on ROC curve analysis.…”

Section: Methodsmentioning

confidence: 99%

“…sensitivity, specificity) and included only a small number of patients [6–8]. Also, studies that have assessed clinical predictors for interval metastases are scarce [15]. Accurate prediction of disease progression during and shortly after chemoradiotherapy would enable surveillance tailored to each patient’s underlying risk of developing systemic disease.…”

Section: Introductionmentioning

confidence: 99%

Prediction and diagnosis of interval metastasis after neoadjuvant chemoradiotherapy for oesophageal cancer using 18F-FDG PET/CT

Goense

Ruurda

Carter

et al. 2018

Eur J Nucl Med Mol Imaging

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ObjectiveDuring neoadjuvant chemoradiotherapy for oesophageal cancer, or in the interval prior to surgery, some patients develop systemic metastasis. This study aimed to evaluate the diagnostic performance of 18F-FDG PET/CT for the detection of interval metastasis and to identify predictors of interval metastases in a large cohort of oesophageal cancer patients.MethodsIn total, 783 consecutive patients with potentially resectable oesophageal cancer who underwent chemoradiotherapy and pre- and post-treatment 18F-FDG PET/CT between 2006 and 2015 were analyzed from a prospectively maintained database. Diagnostic accuracy measures were calculated on a per-patient basis using histological verification or clinical follow-up as a reference standard. Multivariable logistic regression analysis was performed to determine pre-treatment predictors of interval metastasis. A prediction score was developed to predict the probability of interval metastasis.ResultsOf 783 patients that underwent 18F-FDG PET/CT restaging, 65 (8.3%) were found to have interval metastasis and 44 (5.6%) were deemed to have false positive lesions. The resulting sensitivity and specificity was 74.7% (95% CI: 64.3–83.4%) and 93.7% (95% CI: 91.6–95.4%), respectively. Multivariable analysis revealed that tumor length, cN status, squamous cell tumor histology, and baseline SUVmax were associated with interval metastasis. Based on these criteria, a prediction score was developed with an optimism adjusted C-index of 0.67 that demonstrated accurate calibration.Conclusions18F-FDG PET/CT restaging detects distant interval metastases in 8.3% of patients after chemoradiotherapy for oesophageal cancer. The provided prediction score may stratify risk of developing interval metastasis, and could be used to prioritize additional restaging modalities for patients most likely to benefit.

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“…The development of mN stage and mNR have been described previously (15). mN stage (nodes visible discretely from the tumor, within a standard lymphadenectomy territory, with SUV max .…”

Section: Pet/ct Variablesmentioning

confidence: 99%

“…With this in mind, we recently explored the novel concepts of 18 F-FDG-avid nodal stage (mN stage) and metabolic nodal response (mNR) and demonstrated major clinical implications for identifying disease progression during NAC, independent of primary tumor stage and response (15).…”

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confidence: 99%

Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemotherapy: The Implications of Metabolic Nodal Response for Personalized Therapy

et al. 2016

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Only a minority of esophageal cancers demonstrates a pathologic tumor response (pTR) to neoadjuvant chemotherapy (NAC). 18 F-FDG PET/CT is often used for restaging after NAC and to assess response. Increasingly, it is used during therapy to identify unresponsive tumors and predict pTR, using avidity of the primary tumor alone. However, definitions of such metabolic tumor response (mTR) vary. We aimed to comprehensively reevaluate metabolic response assessment using accepted parameters, as well as novel concepts of metabolic nodal stage (mN) and metabolic nodal response (mNR).Methods: This was a single-center retrospective U.K. cohort study. All patients with esophageal cancer staged before NAC with PET/CT and after with CT or PET/CT and undergoing resection from 2006 to 2014 were identified. pTR was defined as Mandard tumor regression grade 1-3; imaging parameters included metrics of tumor avidity (SUV max/mean/peak ), composites of avidity and volume (including metabolic tumor volume), nodal SUV max , and our new concepts of mN stage and mNR. Results: Eighty-two (27.2%) of 301 patients demonstrated pTR. No pre-NAC PET parameters predicted pTR. In 220 patients restaged by PET/CT, the optimal tumor DSUV max threshold was a 77.8% reduction. This was as sensitive as the current PERCIST 30% reduction, but more specific with a higher negative predictive value (P , 0.001). DSUV max and Dlength independently predicted pTR, and composite avidity/spatial metrics outperformed avidity alone. Although both mTR and mNR were associated with pTR, in 82 patients with 18 F-FDG-avid nodes before NAC we observed mNR in 10 (12.2%) not demonstrating mTR. Conclusion: Current definitions of metabolic response are suboptimal and too simplistic. Composite avidity/volume measures improve prediction. mNR may further improve response assessment, by specifically assessing metastatic tumor subpopulations, likely responsible for disease relapse, and should be urgently assessed when considering aborting therapy on the basis of mTR alone.

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Restaging oesophageal cancer after neoadjuvant therapy with 18F-FDG PET-CT: identifying interval metastases and predicting incurable disease at surgery

Cited by 26 publications

References 38 publications

Metabolic nodal response as a prognostic marker after neoadjuvant therapy for oesophageal cancer

Metabolic nodal response as a prognostic marker after neoadjuvant therapy for oesophageal cancer

Prediction and diagnosis of interval metastasis after neoadjuvant chemoradiotherapy for oesophageal cancer using 18F-FDG PET/CT

Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemotherapy: The Implications of Metabolic Nodal Response for Personalized Therapy

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