scholarly journals Radiologic Measurements of Tumor Response to Treatment: Practical Approaches and Limitations

Radiographics ◽  
2008 ◽  
Vol 28 (2) ◽  
pp. 329-344 ◽  
Author(s):  
Chikako Suzuki ◽  
Hans Jacobsson ◽  
Thomas Hatschek ◽  
Michael R. Torkzad ◽  
Katarina Bodén ◽  
...  
Keyword(s):  
Tumor Response ◽  
Response To Treatment

NUMERICAL COEFFICIENT FOR ENDOMETRIAL CANCER INDIVIDUAL RISK EVALUATION IN POSTMENOPAUSAL WOMEN

2017 ◽  
Vol 63 (3) ◽  
pp. 461-465
Author(s):  
Lev Bershteyn ◽  
Dmitriy Vasilev ◽  
Tatyana Poroshina ◽  
Igor Berlev
Keyword(s):  
Breast Cancer ◽  
Endometrial Cancer ◽  
Risk Evaluation ◽  
Tumor Response ◽  
Molecular Genetic ◽  
Response To Treatment ◽  
Individual Risk ◽  
The Past ◽  
Genetic Landscape ◽  
Numerical Coefficient

Increased frequency of endometrial cancer (EC) since the beginning of this century exceeds that of breast cancer and to a large extent can be attributed to dynamics of parameters, which characterize hormonal and metabolic status of ill women and molecular genetic landscape of transforming endometrium. During the past few years there are suggested several options for a personalized assessment of the risk of EC. The aim of this article is to propose and justify own version of this score with the idea of its further not only retrospective but also prospective testing both in relation to the risk of developing endometrial cancer as well as an additional marker helping to predict tumor response to treatment.

scholarly journals A Comparison between Radiolabeled Fluorodeoxyglucose Uptake and Hyperpolarized 13C-Labeled Pyruvate Utilization as Methods for Detecting Tumor Response to Treatment

Neoplasia ◽  
2009 ◽  
Vol 11 (6) ◽  
pp. 574-IN11 ◽  
Author(s):  
Timothy H. Witney ◽  
Mikko I. Kettunen ◽  
Samuel E. Day ◽  
De-en Hu ◽  
Andre A. Neves ◽  
...  
Keyword(s):  
Tumor Response ◽  
Response To Treatment ◽  
Hyperpolarized 13C

Micronuclei Assay — A Predictive Variable for Tumor Response to Treatment

1990 ◽  
pp. 51-55 ◽  
Author(s):  
Homayoon Shidnia ◽  
William Crabtree ◽  
Ned Hornback ◽  
Peter Young ◽  
Mary Hartson ◽  
...  
Keyword(s):  
Tumor Response ◽  
Response To Treatment ◽  
Predictive Variable ◽  
Micronuclei Assay

scholarly journals The role of the neoadjuvant approach in the treatment of primary operable HER2 positive breast cancer

2020 ◽  
Vol 10 (2) ◽  
pp. 45-52
Author(s):  
M. A. Frolova ◽  
Е. V. Glazkova ◽  
A. V. Petrovsky ◽  
О. V. Krokhina ◽  
M. В. Stenina ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Response ◽  
Residual Tumor ◽  
Response To Treatment ◽  
Comprehensive Treatment ◽  
Her2 Positive ◽  
Ki 67 ◽  
Her2 Positive Breast Cancer ◽  
Neoadjuvant Systemic Therapy ◽  
Positive Breast Cancer

Neoadjuvant systemic therapy is an essential component of the comprehensive treatment of primary operable HER2‑positive breast cancer. Therefore, it is extremely important to search for treatment efficacy predictors and optimal system for assessing tumor response to treatment. The study analyzed factors predicting pathological complete response (pCR) in patients with luminal and non‑luminal HER2‑positive tumor subtypes. The morphological assessment of the tumor response to treatment was carried out using the RCB system; additional characteristics of the residual tumor were studied as well. It was shown that a comprehensive assessment involving the use of the RCB system and determination of the Ki ‑ 67 level helps to divide patients into prognostic groups and individualize the adjuvant therapy plan.

scholarly journals Pediatric Rhabdomyosarcomas: Three-Dimensional Radiological Assessments after Induction Chemotherapy Predict Survival Better than One-Dimensional and Two-Dimensional Measurements

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3808
Author(s):  
Giovanna Orsatti ◽  
Carlo Morosi ◽  
Chiara Giraudo ◽  
Alessia Varotto ◽  
Filippo Crimì ◽  
...  
Keyword(s):  
Tumor Response ◽  
World Health ◽  
Response To Treatment ◽  
Significant Prognostic Factor ◽  
Kaplan Meier ◽  
Maximal Diameter ◽  
Radiological Response ◽  
Early Tumor Response ◽  
Early Tumor ◽  
Better Than

Radiological response to neoadjuvant chemotherapy is currently used to assess the efficacy of treatment in pediatric patients with rhabdomyosarcoma (RMS), but the association between early tumor response on imaging and survival is still controversial. The aim of this study was to investigate the prognostic value of assessing radiological response after induction therapy in pediatric RMS, comparing four different methods. This retrospective, two-center study was conducted on 66 non-metastatic RMS patients. Two radiologists measured tumor size on pre- and post-treatment magnetic resonance (MR) or computed tomography (CT) images using four methods: considering maximal diameter with the 1D-RECIST (Response Evaluation Criteria in Solid Tumors); multiplying the two maximal diameters with the 2D-WHO (World Health Organization); multiplying the three maximal diameters with the 3D-EpSSG (European pediatric Soft tissue sarcoma Study Group); obtaining a software-assisted volume assessment with the 3D-Osirix. Each patient was classified as a responder or non-responder based on the proposed thresholds for each method. Tumor response was compared with survival using Kaplan–Meier plots, the log-rank test, and Cox’s regression. Agreement between methods and observers (weighted-κ) was also calculated. The 5-year event-free survival (5yr-EFS) calculated with the Kaplan–Meier plots was significantly longer for responders than for non-responders with all the methods, but the 3D assessments differentiated between the two groups better than the 1D-RECIST or 2D-WHO (p1D-RECIST = 0.018, p2D-WHO = 0.007, p3D-EpSSG and p3D-Osirix < 0.0001). Comparing the 5yr-EFS of responders and non-responders also produced adjusted hazard ratios of 3.57 (p = 0.0158) for the 1D-RECIST, 5.05 for the 2D-WHO (p = 0.0042), 14.40 for the 3D-EpSSG (p < 0.0001) and 11.60 for the 3D-Osirix (p < 0.0001), indicating that the volumetric measurements were significantly more strongly associated with EFS. Inter-method agreement was excellent between the 3D-EpSSG and the 3D-Osirix (κ = 0.98), and moderate for the other comparisons (0.5 < κ < 0.8). The 1D-RECIST and the 2D-WHO tended to underestimate response to treatment. Inter-observer agreement was excellent with all methods (κ > 0.8) except for the 2D-WHO (κ = 0.7). In conclusion, early tumor response was confirmed as a significant prognostic factor in RMS, and the 3D-EpSSG and 3D-Osirix methods predicted response to treatment better than the 1D-RECIST or 2D-WHO measurements.

CLO19-026: Determining the Treatment Decision of Tumors With Mixed Response

2019 ◽  
Vol 17 (3.5) ◽  
pp. CLO19-026
Author(s):  
Candice Baldeo ◽  
Tasneem Kaleem ◽  
Ricardo Paz-Fumagalli ◽  
John Copland ◽  
Michael Menefee
Keyword(s):  
Tumor Response ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Hematologic Malignancies ◽  
Current Treatment ◽  
Response To Treatment ◽  
Mixed Response ◽  
Line Of Therapy ◽  
Additional Agent

Introduction: Individuals receiving systemic anticancer therapies for advanced solid tumors routinely undergo imaging studies to assess the efficacy of the treatment. Mixed response (MR) to cancer therapy is a common but poorly described phenomenon. There is a paucity of data regarding both the incidence and possible mechanisms of this clinical quandary. Potential etiologies include tumor heterogeneity, differences in tumor microenvironment, and discrepancies in drug delivery to different tumor deposits. It is also possible that MR simply reflects differences in the rate of resistance emerging. MR represents a therapeutic dilemma for the clinician. Methods: Mixed tumor response was defined as: One tumor decreasing in size; one tumor increasing in size (classified as RECIST response/progressions), One tumor stable; another tumor progressing, One tumor stable; another tumor responding, New tumor; another tumor responding or remaining stable. Between 2015 and 2017, 120 restaging CT scans were reviewed of patients who had received at least 1 line of therapy for advanced cancer diagnosis which showed MR; hematologic malignancies were excluded. Charts were reviewed to determine the clinical decision that was made at the time of the MR. Results: A total of 120 scans with MR were reviewed from various solid tumor diagnoses. 38 scans were excluded due to loss of follow-up or death. Of the remaining 82 scans, therapy was switched in 30, the same therapy was continued in 50, and an additional agent was added to the current treatment in 2 cases (Table). Of the patients in which treatment was switched, 20% (6/30) showed response to treatment on the following scan. Of the cases that were kept on current treatment, none showed response on the following restaging scan which was done 6–8 weeks later. There were 4 (10%) deaths prior to the next scan in the group that had treatment switched and similarly 5 deaths (10%) prior to the next scan in the group in which treatment remained the same. Conclusion: MR is associated with a poor prognosis, irrespective of treatment decisions. These data are retrospective and our sample size is small, so definitive conclusions cannot be drawn. However, changing therapy when a MR is observed may be of benefit to some patients. A prospective evaluation to more accurately describe and understand the MR phenomenon is warranted.

Perfusion kinetics from clinical DCE mris increase the accuracy of predictions of tumor response to chemotherapy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e12651-e12651
Author(s):  
John A Cole ◽  
Joseph R Peterson ◽  
Tyler M Earnest ◽  
Micahel J Hallock ◽  
John R Pfeiffer ◽  
...  
Keyword(s):  
Exchange Rates ◽  
Tumor Response ◽  
Tissue Perfusion ◽  
Response To Treatment ◽  
Vascular Density ◽  
Modeling Framework ◽  
Spatially Resolved ◽  
Response To Chemotherapy ◽  
Tumor Modeling ◽  
Extravascular Volume

e12651 Background: Nutrient and drug penetration into any solid tumor are critical determinants of the tumor's response to treatment. They depend on both the density of microvasculature within the tumor microenvironment, as well as the exchange rates of nutrients between the microvasculature and the extracellular space. But these parameters are heterogenous, varying considerably from location to location within the tumor and surrounding tissues. The Toft's model and its analogues date back to the early 1990s, and have been used to estimate vascular density, exchange rates, and extracellular-extravascular volume in a spatially-resolved manner using dynamic contrast enhaced (DCE) MRI's. Unfortunately, accurately extracting kinetic parameters from a DCE time-series requires the images to have a time-resolution of just a few seconds, which is rarely done in clinical practice. Methods: We employ a custom designed parallel algorithm to fit DCE MRI data to an exactly-solved ODE model of tissue perfusion kinetics. Results: Here we describe a simplified model of tissue perfusion that can be fit to DCE time traces with temporal resolutions of 90 seconds or more. We show that for many breast tumors, the vascular density and tissue-vascular exchange rate are such that they give rise to a halo of fast-perfusing tissue on the tumor periphery, and slower-perfusing tissue inside. We then use this model as part of a more comprehensive tumor simulation methodology to predict how different patients will respond to neoadjuvant chemotherapy (NACT). We find that the incorporation of our microvascular model gives rise to significantly more accurate predictions of post-treatment tumor volume. Conclusions: Performing perfusion kinetics analyses on clinical MRIs is both challenging, but critical for accurately predicting how a patient will respond to treatment. Our model, which relaxes the requirement for fine DCE temporal resolution, allows for these analyses to be performed on a larger swath of patients without the need for small volumes of interest, or ultra-fast MRI techniques. Moreover, when used within a broader tumor-modeling framework, our model increases the accuracy of predictions of tumor response to NACT.

scholarly journals Assessing Tumor Response to Treatment in Patients with Lung Cancer Using Dynamic Contrast-Enhanced CT

Diagnostics ◽  
2016 ◽  
Vol 6 (3) ◽  
pp. 28 ◽  
Author(s):  
Louise Strauch ◽  
Rie Eriksen ◽  
Michael Sandgaard ◽  
Thomas Kristensen ◽  
Michael Nielsen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tumor Response ◽  
Response To Treatment ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Dynamic Contrast Enhanced Ct
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