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

Abstract

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.

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

“…mNR comprised: complete metabolic response (CMR); partial metabolic response (PMR; reduction in mN category or SUVmax by at least 30 per cent); stable metabolic disease (SMD; stable mN category or reduction/progression in SUVmax below 30 per cent); or progressive metabolic disease (PMD; progression of mN category or SUVmax by at least 30 per cent). Optimal metrics of mTR for predicting pTR were as described previously, using receiver operating characteristics (ROCs). In brief, these comprised: SUVmax −77·8 per cent, avid length −57·8 per cent, PET Response Criteria in Solid Tumors (PERCIST) –30 per cent, Metabolic response evalUatioN for Individualization of neoadjuvant Chemotherapy in oesOphageal and oesophagogastric adeNocarcinoma (MUNICON) –35 per cent, mean SUV (SUVmean) –36·8 per cent, peak SUV (SUVpeak) –69·8 per cent, metabolic tumour volume (MTV) –89·6 per cent, maximum tumour glycolytic volume (TGV) –93·8 per cent, mean TGV –89·2 per cent.…”

“…mNR comprised: complete metabolic response (CMR); partial metabolic response (PMR; reduction in mN category or SUVmax by at least 30 per cent); stable metabolic disease (SMD; stable mN category or reduction/progression in SUVmax below 30 per cent); or progressive metabolic disease (PMD; progression of mN category or SUVmax by at least 30 per cent). Optimal metrics of mTR for predicting pTR were as described previously, using receiver operating characteristics (ROCs) 20…”

Personalized therapy based on image for esophageal or gastroesophageal junction adenocarcinoma

“…The median overall survival was significantly longer for PETresponders than for PET-non-responders [hazard ratio (HR): 2.13; 95% confidence interval (CI): 1.14-3.99; P=0.015] (14). A large retrospective single institution study of 301 patients observed a relationship between SUVmax reduction and pathological response (17). As pathologic response was defined by the Mandard tumor regression grades (TRGs) 1-3 (19), SUV changes could identify pathologic response [odds ratio (OR) for each percentage reduction: 1.03; 95% CI: 1.01-1.06; P=0.003] (17).…”

Composite metrics in response assessment—new hope in oesophageal cancer?

“…Using SUV mean , the TGV mean was calculated, whilst using the SUV max the TGV max was produced. All these metrics can be calculated as baseline values or, ideally, as a composite metric such as ΔMTV, ΔTGV max and ΔTGV mean (7). Combination of spatial data with metabolic response resulted in improved prediction.…”