The optimal tumor response assessment in patients with HCC after treatment of TACE.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 215-215 ◽  
Author(s):  
E. Jung ◽  
J. Kim ◽  
E. Yoon ◽  
H. Lee ◽  
Y. Lee ◽  
...  
Keyword(s):  
Treatment Response ◽  
Tumor Response ◽  
Univariate Analysis ◽  
Significant Risk ◽  
Response Assessment ◽  
Assessment Method ◽  
Hazard Ratios ◽  
Different Characteristics ◽  
Risk Factors For Survival ◽  
Optimal Tumor

215 Background: WHO or RECIST has been considered as suboptimal methods for tumor response assessment in HCC, especially receiving locoregional therapies. Recently, new modified methods having concept of viable tumor has been proposed. Herein we compared the efficacy to assess response and to predict prognosis between WHO, RECIST, EASL, mRECIST in HCC patients receiving TACE. Methods: We retrospectively reviewed 141 HCC patients who were newly diagnosed and received TACE between August 2005 and November 2006. Among them, 98 patients who were available for assessing treatment response were analyzed at 1 month after 2nd TACE. We evaluated intermethod aggreement between methods and assessed the efficacy predicting time to progression (TTP) and overall survival (OS). Results: The results of tumor responses (number of CR/ PR/ SD/ PD) by WHO/ RECIST/ EASL/ mRECIST were 1/ 14/ 74/ 9, 1/ 12/ 77/ 8, 34/ 34/ 25/ 5, 34/ 28/ 31/ 5, respectively. The κvalue of intermethod agreement for EASL vs WHO, EASL vs RECIST, mRECIST vs WHO, and mRECIST vs RECIST was 0.102, 0.088, 0.112 and 0.122, respectively. The κvalue for WHO vs RECIST and EASL vs mRECIST was 0.759 and 0.883 (p=0.00). Hazard ratios for TTP in responders compared with nonresponders were 0.313 (95% CI; 0.19-0.52, p=0.00) for EASL and 0.335 (95% CI; 0.21-0.54, p=0.00) for mRECIST. Hazard ratios for survival in responders compared with nonresponders were 0.208 (95% CI; 0.12-0.37, p=0.00) for EASL and 0.269 (95% CI; 0.15-0.48, p=0.00) for mRECIST. In the univariate analysis, tumor size, infiltrative type, PVT, EASL responder, and mRECIST responder were significant risk factors for survival. Multivariate analysis showed EASL responder (HR 0.165, 95% CI 0.056-0.486, p=0.001) and infiltrative type (HR 4.504, 95% CI 1.579-12.848, p=0.005) were independent predictable factors for survival. Conclusions: The recent proposed methods showed different characteristics from preexisting methods in assessing treatment response and furthermore, responder by EASL method was independent predictor for survival in HCC patients receiving TACE. EASL method should be applied as response assessment method for HCC patients receiving TACE. No significant financial relationships to disclose.

A novel morphologic and metabolic feature fused treatment response evaluation pipeline for pancreatic adenocarcinoma patients.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 311-311
Author(s):  
Yi Lao ◽  
John David ◽  
Arman Torosian ◽  
Wensha Yang ◽  
Richard Tuli
Keyword(s):  
Treatment Response ◽  
Pancreatic Adenocarcinoma ◽  
Tumor Response ◽  
Locally Advanced ◽  
Standardized Uptake Value ◽  
Predictive Marker ◽  
Response Assessment ◽  
Surface Registration ◽  
Response Evaluation ◽  
Pet Ct

311 Background: Adaptive radiation therapy for pancreatic adenocarcinoma (PA) relies on accurate treatment response assessment. Traditional RECIST criteria poorly characterize tumors with complex morphological features, while PET imaging inefficiently detects tumors with intrinsically low standardized uptake value (SUV). Here, we performed regional comparisons of 3D intact PA surfaces pre and post chemoradiotherapy (CRT) utilizing surface measurements containing both morphological and metabolic features to better assess response. Methods: Twenty-one locally advanced PA patients with pre- and 6-8 week post-CRT 18F FDG-PET/CT scans were evaluated. Boundaries of initial and post-CRT tumors were manually defined on respective CT images. On each of the tumors, 3D meshes were generated, followed by surface based registration to achieve vertex-wise correspondence. For each surface vertex, a multivariate vector was formed from two components: anatomic (deformation tensors resulted from surface registration), and metabolic (regional SUV obtained from radius to surface projections). To assess tumor response, paired mahabanobis distance (Mdist) between pre- and post-CRT tumor surfaces with previously formed multivariate vectors were calculated for each patient. Mdist was evaluated using Cox analysis correlated with overall survival (OS) and compared with measurements based on serum CA19-9, volume, SUVmax and SUVmean. Results: Among all the tested parameters, Mdist is the best predictor of OS, with a hazard ratio of 0.437 (p = 0.036). Post-CRT versus pre-CRT ratios based on volume and SUVmax both reached borderline significance (p = 0.0769 and 0.0799, respectively), while CA19-9 and SUVmean failed in predicting OS in our small cohort of patients. Conclusions: We introduced a PET/CT-based novel morphologic and metabolic pipeline for post-CRT response evaluation in locally advanced PA. The fused Mdist outperformed traditional morphologic, metabolic, and physiological measurements in OS prediction. The presented fused model may serve as a new biomarker to better characterize the heterogeneity of tumor response to CRT and a predictive marker for surgical resection.

scholarly journals Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Lu ◽  
Laurent Dercle ◽  
Binsheng Zhao ◽  
Lawrence H. Schwartz
Keyword(s):  
Colorectal Cancer ◽  
Deep Learning ◽  
Metastatic Colorectal Cancer ◽  
Treatment Response ◽  
Morphological Change ◽  
Tumor Size ◽  
Tumor Response ◽  
Treatment Decision ◽  
Response Assessment ◽  
Size Change

AbstractIn current clinical practice, tumor response assessment is usually based on tumor size change on serial computerized tomography (CT) scan images. However, evaluation of tumor response to anti-vascular endothelial growth factor therapies in metastatic colorectal cancer (mCRC) is limited because morphological change in tumor may occur earlier than tumor size change. Here we present an analysis utilizing a deep learning (DL) network to characterize tumor morphological change for response assessment in mCRC patients. We retrospectively analyzed 1,028 mCRC patients who were prospectively included in the VELOUR trial (NCT00561470). We found that DL network was able to predict early on-treatment response in mCRC and showed better performance than its size-based counterpart with C-Index: 0.649 (95% CI: 0.619,0.679) vs. 0.627 (95% CI: 0.567,0.638), p = 0.009, z-test. The integration of DL network with size-based methodology could further improve the prediction performance to C-Index: 0.694 (95% CI: 0.661,0.720), which was superior to size/DL-based-only models (all p < 0.001, z-test). Our study suggests that DL network could provide a noninvasive mean for quantitative and comprehensive characterization of tumor morphological change, which may potentially benefit personalized early on-treatment decision making.

scholarly journals Tumor response as defined by iRECIST in gastrointestinal malignancies treated with PD-1 and PD-L1 inhibitors and correlation with survival

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Peiyi Xie ◽  
Hong Zheng ◽  
Haiyang Chen ◽  
Kaikai Wei ◽  
Ximin Pan ◽  
...  
Keyword(s):  
Treatment Response ◽  
Tumor Response ◽  
Univariate Analysis ◽  
Imaging Biomarkers ◽  
Tumor Diameter ◽  
Cancer Type ◽  
Combined Surgery ◽  
Gastrointestinal Malignancies ◽  
Overall Response ◽  
Risk Of Death

Abstract Background Atypical tumor response patterns during immune checkpoint inhibitor therapy pose a challenge to clinicians and investigators in immuno-oncology practice. This study evaluated tumor burden dynamics to identify imaging biomarkers for treatment response and overall survival (OS) in advanced gastrointestinal malignancies treated with PD-1/PD-L1 inhibitors. Methods This retrospective study enrolled a total of 198 target lesions in 75 patients with advanced gastrointestinal malignancies treated with PD-1/PD-L1 inhibitors between January 2017 and March 2021. Tumor diameter changes as defined by immunotherapy Response Evaluation Criteria in Solid Tumors (iRECIST) were studied to determine treatment response and association with OS. Results Based on the best overall response, the tumor diameter ranged from − 100 to + 135.3% (median: − 9.6%). The overall response rate was 32.0% (24/75), and the rate of durable disease control for at least 6 months was 30.7% (23/75, one (iCR, immune complete response) or 20 iPR (immune partial response), or 2iSD (immune stable disease). Using univariate analysis, patients with a tumor diameter maintaining a < 20% increase (48/75, 64.0%) from baseline had longer OS than those with ≥20% increase (27/75, 36.0%) and, a reduced risk of death (median OS: 80 months vs. 48 months, HR = 0.22, P = 0.034). The differences in age (HR = 1.09, P = 0.01), combined surgery (HR = 0.15, P = 0.01) and cancer type (HR = 0.23, P = 0.001) were significant. In multivariable analysis, patients with a tumor diameter with a < 20% increase had notably reduced hazards of death (HR = 0.15, P = 0.01) after adjusting for age, combined surgery, KRAS status, cancer type, mismatch repair (MMR) status, treatment course and cancer differentiation. Two patients (2.7%) showed pseudoprogression. Conclusions Tumor diameter with a < 20% increase from baseline during therapy in gastrointestinal malignancies was associated with therapeutic benefit and longer OS and may serve as a practical imaging marker for treatment response, clinical outcome and treatment decision making.

scholarly journals OP0098 POLYPHARMACY IS ASSOCIATED WITH A POORER TREATMENT RESPONSE AND INCREASED RISK OF ADVERSE EVENTS IN EARLY RHEUMATOID ARTHRITIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 54.1-54
Author(s):  
S. Benamar ◽  
C. Lukas ◽  
C. Daien ◽  
C. Gaujoux-Viala ◽  
L. Gossec ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Adverse Events ◽  
Treatment Response ◽  
Univariate Analysis ◽  
Group Versus ◽  
Biological Database ◽  
Lower Probability ◽  
Research Support ◽  
Early Ra ◽  
Increased Risk

Background:Polypharmacy is steadily increasing in patients with rheumatoid arthritis (RA). They may interfere with treatment response and the occurrence of serious adverse events. Medications taken by a patient may reflect active comorbidities, whereas comorbidity indices usually used include past or current diseases.Objectives:To evaluate whether polypharmarcy is associated with treatment response and adverse events in an early RA cohort and to establish whether polypharmacy could represent a substitute of comorbidities.Methods:We used data from the French cohort ESPOIR, including 813 patients with early onset arthritis. Patients included the current study had to start their first disease modifying anti-rheumatic drug (DMARD) within 24 months of inclusion in the cohort. Disease activity data were collected at one, five and ten years from the initiation of the first DMARD. For each patient, treatments were collected at baseline and at five years. Medications count included all specialties other than background RA therapy, analgesics/NSAIDs and topicals. Polypharmacy was defined as a categorical variable based on the median and tertiles of distribution in the cohort. Treatment response was assessed by achieving DAS28 ESR remission (REM) at 1 year, 5 years and 10 years from the initiation of the first DMARD. The occurrence of severe adverse events (SAE) was measured by the occurrence of severe infection, hospitalization, or death during the 10-year follow-up. The association between patient’s characteristics and achievement of REM and occurrence of SAE were tested in univariate analysis. A logistic regression model was used to evaluate associations between polypharmacy and REM at 1 year, 5 years and 10 years (we used baseline polypharmacy for the 1-year analysis and five years polypharmacy for the 5- and 10-years analyses). Multivariate adjustment was made for age, sex, BMI, duration of disease, initial DAS28 ESR, initial HAQ, smoking status, rheumatic disease comorbidity index (RDCI).Results:The proportion of patients who achieved REM one year after the initiation of the first DMARD was 32.1% in the polypharmacy according to the median group (patients taken ≥2 medication) versus 67.9% in the non-polypharmacy group (p=0.07). At 5 years after the first DMARD, the proportion of patients with REM was 45.0% in the polypharmacy group versus 56.3% in the non-polypharmacy group (p=0.03). At 10 years the proportion of patients with REM was 32.5% in the polypharmacy group versus 67.5% (p=0.06). Patients who take greater or equal to 2 medications had a 40% lower probability of achieving REM (OR = 0.60 [0.38-0.94] p = 0.03) at 5 years from the first DMARD (if RDCI index was not included in the model). At 10 years, patients receiving multiple medications had a 43% lower probability of achieving REM (OR = 0.57 [0.34-0.94] p = 0.02). SAE incidence was 61 per 1000 patient-years. For patients who developed SAE all causes 71.4% where in the polypharmacy group versus 57.8% were in the non-polypharmacy group (p = 0.03; univariate analysis). These results are no longer significant after adjustment for comorbidities indices.Conclusion:In this early RA cohort, polypharmacy is associated with a poorer treatment response and increased risk of adverse events. Polypharmacy may represent a good substitute of comorbidities for epidemiological studies.Acknowledgements:We are grateful to Nathalie Rincheval (Montpellier) who did expert monitoring and data management and all theinvestigators who recruited and followed the patients (F. Berenbaum, Paris-Saint Antoine; MC. Boissier, Paris-Bobigny; A. Cantagrel, Toulouse; B. Combe, Montpellier; M. Dougados, Paris-Cochin; P. Fardellone and P. Boumier, Amiens; B. Fautrel, Paris-La Pitié; RM. Flipo, Lille; Ph. Goupille, Tours; F. Liote, Paris- Lariboisière; O. Vittecoq, Rouen; X. Mariette, Paris-Bicêtre; P. Dieude, Paris Bichat; A. Saraux, Brest; T. Schaeverbeke, Bordeaux; and J. Sibilia, Strasbourg).The work reported on in the manuscript did not benefit from any financial support. The ESPOIR cohort is sponsored by the French Society for Rheumatology. An unrestricted grant from Merck Sharp and Dohme (MSD) was allocated for the first 5 years. Two additional grants from INSERM were obtained to support part of the biological database. Pfizer, Abbvie, Lilly and more recently Fresenius and Biogen also supported the ESPOIR cohort.Disclosure of Interests:Soraya Benamar: None declared, Cédric Lukas Speakers bureau: Abbvie, Amgen, Janssen, Lilly, MSD, Novartis, Pfizer, Roche-Chugai, UCB, Consultant of: Abbvie, Amgen, Janssen, Lilly, MSD, Novartis, Pfizer, Roche-Chugai, UCB, Grant/research support from: Pfizer, Novartis and Roche-Chugai, Claire Daien Speakers bureau: AbbVie, Abivax, BMS, MSD, Roche, Chugai, Novartis, Pfizer, Sandoz, Lilly, Consultant of: AbbVie, Abivax, BMS, MSD, Roche, Chugai, Novartis, Pfizer, Sandoz, Lilly, Cécile Gaujoux-Viala Speakers bureau: Abbvie, BMS, Celgene, Janssen, Medac, MSD, Nordic Pharma, Novartis, Pfizer, Sanofi, Roche-Chugai, UCB, Consultant of: Abbvie, BMS, Celgene, Janssen, Medac, MSD, Nordic Pharma, Novartis, Pfizer, Sanofi, Roche-Chugai, UCB, Grant/research support from: Pfizer, Laure Gossec Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis et UCB, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis et UCB, Anne-Christine Rat Speakers bureau: Pfizer, Lilly, Consultant of: Pfizer, Lilly, Bernard Combe Speakers bureau: AbbVie; Bristol-Myers Squibb; Gilead; Janssen; Lilly; Merck; Novartis; Pfizer; Roche-Chugai; and Sanofi;, Consultant of: AbbVie; Bristol-Myers Squibb; Gilead; Janssen; Lilly; Merck; Novartis; Pfizer; Roche-Chugai; and Sanofi;, Grant/research support from: Novartis, Pfizer, and Roche-Chugai., Jacques Morel Speakers bureau: Abbvie, BMS, Lilly, Médac, MSD, Nordic Pharma, Pfizer, UCB, Consultant of: Abbvie, BMS, Lilly, Médac, MSD, Nordic Pharma, Pfizer, UCB, Grant/research support from: BMS, Pfizer

scholarly journals Risk Factors Associated with Retinopathy of Prematurity in Very and Extremely Preterm Infants

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 420
Author(s):  
Claudia Ioana Borțea ◽  
Florina Stoica ◽  
Marioara Boia ◽  
Emil Radu Iacob ◽  
Mihai Dinu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Preterm Infants ◽  
Gestational Age ◽  
Retinopathy Of Prematurity ◽  
Univariate Analysis ◽  
Significant Risk ◽  
Extremely Preterm ◽  
Extremely Preterm Infants ◽  
Surfactant Administration ◽  
Stage 1

Background and Objectives: Retinopathy of prematurity (ROP) is the leading cause of blindness in preterm infants. We studied the relationship between different perinatal characteristics, i.e., sex; gestational age (GA); birth weight (BW); C-reactive protein (CRP) and lactate dehydrogenase (LDH) concentrations; ventilation, continuous positive airway pressure (CPAP), and surfactant administration; and the incidence of Stage 1–3 ROP. Materials and Methods: This study included 247 preterm infants with gestational age (GA) < 32 weeks that were successfully screened for ROP. Univariate and multivariate binary analyses were performed to find the most significant risk factors for ROP (Stage 1–3), while multivariate multinomial analysis was used to find the most significant risk factors for specific ROP stages, i.e., Stage 1, 2, and 3. Results: The incidence of ROP (Stage 1–3) was 66.40% (164 infants), while that of Stage 1, 2, and 3 ROP was 15.38% (38 infants), 27.53% (68 infants), and 23.48% (58 infants), respectively. Following univariate analysis, multiple perinatal characteristics, i.e., GA; BW; and ventilation, CPAP, and surfactant administration, were found to be statistically significant risk factors for ROP (p < 0.001). However, in a multivariate model using the same characteristics, only BW and ventilation were significant ROP predictors (p < 0.001 and p < 0.05, respectively). Multivariate multinomial analysis revealed that BW was only significantly correlated with Stage 2 and 3 ROP (p < 0.05 and p < 0.001, respectively), while ventilation was only significantly correlated with Stage 2 ROP (p < 0.05). Conclusions: The results indicate that GA; BW; and the use of ventilation, CPAP, and surfactant were all significant risk factors for ROP (Stage 1–3), but only BW and ventilation were significantly correlated with ROP and specific stages of the disease, namely Stage 2 and 3 ROP and Stage 2 ROP, respectively, in multivariate models.

Multi‐parametric MRI (mpMRI) for treatment response assessment of radiation therapy

2021 ◽  
Author(s):  
Chunhao Wang ◽  
Kyle R. Padgett ◽  
Min‐Ying Su ◽  
Eric A. Mellon ◽  
Danilo Maziero ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Treatment Response ◽  
Response Assessment ◽  
Treatment Response Assessment

scholarly journals Direct Versus Calculated LDL Cholesterol and C-Reactive Protein in Cardiovascular Disease Risk Assessment in the Framingham Offspring Study

2019 ◽  
Vol 65 (9) ◽  
pp. 1102-1114 ◽  
Author(s):  
Hiroaki Ikezaki ◽  
Virginia A Fisher ◽  
Elise Lim ◽  
Masumi Ai ◽  
Ching-Ti Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Ldl Cholesterol ◽  
Disease Risk ◽  
Univariate Analysis ◽  
Significant Risk ◽  
C Reactive Protein ◽  
Cox Regression Analysis ◽  
Reactive Protein ◽  
Standard Risk

AbstractBACKGROUNDIncreases in circulating LDL cholesterol (LDL-C) and high-sensitivity C-reactive protein (hsCRP) concentrations are significant risk factors for cardiovascular disease (CVD). We assessed direct LDL-C and hsCRP concentrations compared to standard risk factors in the Framingham Offspring Study.METHODSWe used stored frozen plasma samples (−80 °C) obtained after an overnight fast from 3147 male and female participants (mean age, 58 years) free of CVD at cycle 6 of the Framingham Offspring Study. Overall, 677 participants (21.5%) had a CVD end point over a median of 16.0 years of follow-up. Total cholesterol (TC), triglyceride (TG), HDL cholesterol (HDL-C), direct LDL-C (Denka Seiken and Kyowa Medex methods), and hsCRP (Dade Behring method) concentrations were measured by automated analysis. LDL-C was also calculated by both the Friedewald and Martin methods.RESULTSConsidering all CVD outcomes on univariate analysis, significant factors included standard risk factors (age, hypertension, HDL-C, hypertension treatment, sex, diabetes, smoking, and TC concentration) and nonstandard risk factors (non-HDL-C, direct LDL-C and calculated LDL-C, TG, and hsCRP concentrations). On multivariate analysis, only the Denka Seiken direct LDL-C and the Dade Behring hsCRP were still significant on Cox regression analysis and improved the net risk reclassification index, but with modest effects. Discordance analysis confirmed the benefit of the Denka Seiken direct LDL-C method for prospective hard CVD endpoints (new-onset myocardial infarction, stroke, and/or CVD death).CONCLUSIONSOur data indicate that the Denka Seiken direct LDL-C and Dade Behring hsCRP measurements add significant, but modest, information about CVD risk, compared to standard risk factors and/or calculated LDL-C.

scholarly journals 18F-PSMA-1007 PET/CT for response assessment in patients with metastatic renal cell carcinoma undergoing tyrosine kinase or checkpoint inhibitor therapy: preliminary results

2020 ◽  
Author(s):  
L. M. Mittlmeier ◽  
M. Unterrainer ◽  
S. Rodler ◽  
A. Todica ◽  
N. L. Albert ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tyrosine Kinase ◽  
Cell Carcinoma ◽  
Treatment Response ◽  
Renal Cell ◽  
Systemic Treatment ◽  
Response Assessment ◽  
Recist 1.1 ◽  
Psma Pet ◽  
Pet Ct

Abstract Introduction Tyrosine kinase (TKI) and checkpoint inhibitors (CI) prolonged overall survival in metastatic renal cell carcinoma (mRCC). Early prediction of treatment response is highly desirable for the individualization of patient management and improvement of therapeutic outcome; however, serum biochemistry is unable to predict therapeutic efficacy. Therefore, we compared 18F-PSMA-1007 PET imaging for response assessment in mRCC patients undergoing TKI or CI therapy compared to CT-based response assessment as the current imaging reference standard. Methods 18F-PSMA-1007 PET/CT was performed in mRCC patients prior to initiation of systemic treatment and 8 weeks after therapy initiation. Treatment response was evaluated separately on 18F-PSMA-PET and CT. Changes on PSMA-PET (SUVmean) were assessed on a per patient basis using a modified PERCIST scoring system. Complete response (CRPET) was defined as absence of any uptake in all target lesions on posttreatment PET. Partial response (PRPET) was defined as decrease in summed SUVmean of > 30%. The appearance of new, PET-positive lesions or an increase in summed SUVmean of > 30% was defined as progressive disease (PDPET). A change in summed SUVmean of ± 30% defined stable disease (SDPET). RECIST 1.1 criteria were used for response assessment on CT. Results of radiographic response assessment on PSMA-PET and CT were compared. Results Overall, 11 mRCC patients undergoing systemic treatment were included. At baseline PSMA-PET1, all mRCC patients showed at least one PSMA-avid lesion. On follow-up PET2, 3 patients showed CRPET, 3 PRPET, 4 SDPET, and 1 PDPET. According to RECIST 1.1, 1 patient showed PRCT, 9 SDCT, and 1 PDCT. Overall, concordant classifications were found in only 2 cases (2 SDCT + PET). Patients with CRPET on PET were classified as 3 SDCT on CT using RECIST 1.1. By contrast, the patient classified as PRCT on CT showed PSMA uptake without major changes during therapy (SDPET). However, among 9 patients with SDCT on CT, 3 were classified as CRPET, 3 as PRPET, 1 as PDPET, and only 2 as SDPET on PSMA-PET. Conclusion On PSMA-PET, heterogeneous courses were observed during systemic treatment in mRCC patients with highly diverging results compared to RECIST 1.1. In the light of missing biomarkers for early response assessment, PSMA-PET might allow more precise response assessment to systemic treatment, especially in patients classified as SD on CT.

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