Optimization of Metabolic Tumor Volume as a Prognostic Marker in CAR T-Cell Therapy for Aggressive Large B-cell NHL

BACKGROUND

CD19-targeted chimeric antigen receptor (CAR) T-cell therapy has become a standard of care in relapsed/refractory (R/R) aggressive large B-cell non-Hodgkin lymphomas (B-NHL) though the majority of recipients do not receive durable disease benefit, prompting the need to better define risk factors for relapse/progression.

OBJECTIVES

We performed a single-center, retrospective analysis of patients treated with commercial CAR T-cell therapy to evaluate the impact of tumor burden, as measured by whole-body metabolic tumor volume (MTV) from 18F fluorodeoxyglucose PET imaging, on treatment outcomes.

STUDY DESIGN

Sixty-one patients treated with CAR T-cell therapy for R/R B-NHL between May 2016 and November 2021 were included.

RESULTS

Using a receiver operating characteristic curve-based MTV optimization cutoff of 450 mL, 1-year progression-free survival (PFS) was 22% for high MTV versus 54% for low MTV (P < .01), and 1-year overall survival (OS) was 37% and 73%, respectively (P = .01). In a subset of 46 patients, residual MTV of less than 106 mL at the day 30 (D30) disease assessment was associated with significantly improved outcomes (1-year OS 85% vs. 13%, P < .01). Incorporation of pretreatment MTV to the International Prognostic Index (IPI) scoring system significantly distinguished 2-year PFS and OS outcomes by 3 risk groups.

CONCLUSIONS

Our findings suggest that both pretreatment and D30 MTV are predictive of outcomes among R/R B-NHL patients treated with CAR T-cell therapy. These data indicate that efforts to reduce pretreatment tumor burden may improve longitudinal clinical outcomes. Furthermore, D30 postinfusion MTV quantification may aid clinicians in optimally identifying patients at high-risk for progression, and in whom closer disease monitoring should be considered. MTV also adds prognostic value to patients with high-risk IPI and holds promise for incorporation in novel risk scoring systems which can identify patients prior to CAR T-cell therapy at highest risk of adverse outcomes.

Predicting Response to Chemotherapy in Patients With Newly Diagnosed High-Risk Neuroblastoma: A Report From the International Neuroblastoma Risk Group

PURPOSE

Metaiodobenzylguanidine (MIBG) scans are a radionucleotide imaging modality that undergo Curie scoring to semiquantitatively assess neuroblastoma burden, which can be used as a marker of therapy response. We hypothesized that a convolutional neural network (CNN) could be developed that uses diagnostic MIBG scans to predict response to induction chemotherapy.

METHODS

We analyzed MIBG scans housed in the International Neuroblastoma Risk Group Data Commons from patients enrolled in the Children's Oncology Group high-risk neuroblastoma study ANBL12P1. The primary outcome was response to upfront chemotherapy, defined as a Curie score ≤ 2 after four cycles of induction chemotherapy. We derived and validated a CNN using two-dimensional whole-body MIBG scans from diagnosis and evaluated model performance using area under the receiver operating characteristic curve (AUC). We also developed a clinical classification model to predict response on the basis of age, stage, and MYCN amplification.

RESULTS

Among 103 patients with high-risk neuroblastoma included in the final cohort, 67 (65%) were responders. Performance in predicting response to upfront chemotherapy was equivalent using the CNN and the clinical model. Class-activation heatmaps verified that the CNN used areas of disease within the MIBG scans to make predictions. Furthermore, integrating predictions using a geometric mean approach improved detection of responders to upfront chemotherapy (geometric mean AUC 0.73 v CNN AUC 0.63, P < .05; v clinical model AUC 0.65, P < .05).

CONCLUSION

We demonstrate feasibility in using machine learning of diagnostic MIBG scans to predict response to induction chemotherapy for patients with high-risk neuroblastoma. We highlight improvements when clinical risk factors are also integrated, laying the foundation for using a multimodal approach to guiding treatment decisions for patients with high-risk neuroblastoma.

Implementation of a hybrid angiography-CT system: increased short-term revenue at an academic radiology department

PURPOSE

To analyze the financial impact following implementation of a hybrid Angio-CT system at a tertiary care academic medical center.

METHODS

Aggregate case types and volumes were compared 24 months before and 12 months after a hybrid Angio-CT system replaced a traditional interventional C-arm angiography suite at an academic medical center. Procedure revenues from this 36-month study period were derived from five payors mixes (Medicare, Medicaid, commercial insurance, out-of-pocket and managed care program) and Medicare-rate adjusted to each individual payor types.

RESULTS

Average case volume per month increased 12% in the hybrid Angio-CT suite when compared to the previous traditional angiography suite (P < 0.05). The variety of IR procedures in the hybrid Angio-CT suite also expanded to include more complex interventional radiology and interventional oncology procedures; the breadth of cases performed in the hybrid Angio-CT suite were associated with CPT codes of higher rates (average CPT value/case increased from $2,334.61 to $2,567.25). The estimated average annual revenue of the hybrid Angio-CT suite increased 23% as compared to previous traditional angiography suite.

CONCLUSION

A hybrid Angio-CT system is a financially feasible endeavor at a tertiary care academic medical center that facilitated higher complexity procedure codes and increased procedure-related revenue.

Predicting response to chemotherapy in neuroblastoma using deep learning: A report from the International Neuroblastoma Risk Group

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Background: Metaiodobenzylguanidine (MIBG) scans are a radionucleotide imaging modality used to evaluate neuroblastoma stage at diagnosis and also determine disease response following therapy. Curie scoring is used to semi-quantitatively assess disease burden from an MIBG scan on a scale from none (0) to widespread throughout the body (30). While a Curie score ≤2 after six cycles of induction chemotherapy has been shown to be prognostic of outcome, there is no established correlation between diagnostic Curie score and outcome. Deep learning models, such as convolutional neural networks (CNN), have been shown to learn generalizable patterns within images for successful classification of metastases and detection of multiple adult cancers. We hypothesized a CNN could be developed to predict response to induction chemotherapy, a proxy for outcome, using diagnostic MIBG scans. Methods: DICOM MIBG scans and associated clinical data from a Children’s Oncology Group (COG) pilot study for children diagnosed with high-risk neuroblastoma (ANBL12P1; NCT1798004) were deidentified and linked to clinical data by the Pediatric Cancer Data Commons and obtained from the International Neuroblastoma Risk Group Data Commons. Patients were defined as having a poor response to induction chemotherapy if their Curie score after four cycles of induction chemotherapy was ≥2. An independent external validation cohort was comprised of 29 images from 26 high-risk patients treated at the University of Chicago with clinically-annotated diagnostic and post-cycle six induction DICOM MIBG scans. The CNN was trained using 2D whole body MIBG scans obtained at diagnosis. We developed the CNN using a transfer learning approach using the Xception architecture as the base layer. Hyperparameter optimization was performed using an 80%-20% train-validation strategy. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC). Results: Among 146 patients with high-risk neuroblastoma enrolled on ANBL12P1, 104 had available diagnostic and end-induction MIBG scans. There were no differences in clinical or biological characteristics between included and excluded patients. The base model CNN was able to predict which patients had a poor response to induction chemotherapy with an AUROC of 0.72 in the validation set from the ANBL12P1 cohort. Additionally, the CNN was able to predict patient response to therapy with an AUROC of 0.64 in an independent external dataset from University of Chicago. Conclusions: Our study suggests it is feasible to apply machine learning of diagnostic MIBG scans to predict response to chemotherapy for high-risk neuroblastoma patients. Given these promising results, further work to improve AUROC and performance within larger datasets is ongoing.

Improved Utilization Following Conversion of a Fluoroscopy Suite to Hybrid CT/Angiography System

PURPOSE

To assess changes in operational utilization following conversion of a single IR suite to a hybrid CT/angiography (Angio-CT) system at an academic tertiary care center.

MATERIALS AND METHODS

The total number of interventional procedures and diagnostic CT examinations performed in 29 rooms (20 diagnostic radiology, 7 IR, 2 shared between divisions) was calculated in the 24 months before conversion of an IR suite to Angio-CT and 12 months after conversion. The total number of IR procedures (global IR/month) and diagnostic CT scans per month (global CT/month) in both before and after conversion periods was calculated and defined as baseline institutional growth. This was compared against the change in the number of IR procedures performed in the before and after periods in the converted room (Angio-CT/month) as well as the number of diagnostic CT scans performed in the shared rooms (shared CT/month).

RESULTS

The percent change in global CT and global IR from the before to the after periods was 39.2% and 3.1%, respectively. Shared CT per month and Angio-CT per month increased by 46.7% and 12.0% across the same time periods, respectively. The ratio of the percent increase in Angio-CT per month to percent increase in global IR per month was 3.87. The ratio of the percent increase in shared CT per month to percent increase in global CT per month was 1.19.

CONCLUSIONS

Operational utilization improved in both diagnostic radiology and IR sections following conversion of a conventional fluoroscopic IR suite to an Angio-CT room.

Interventional Techniques for the Ablation and Augmentation of Extraspinal Lytic Bone Metastases

In addition to being a major source of cancer-related pain, metastatic osseous lesions are frequently at risk for pathologic fracture and its accompanying morbidity. While bony metastases are commonly thought of as occurring within the vertebral column, over 80% are found outside the spine. Percutaneous interventional treatment options for nonspinal metastases offer a broad array of minimally invasive, image-guided procedures that are rapidly effective, reduce the need for opioids, and often work in complementary fashion with adjunct treatments in radiation oncology, orthopaedic surgery, and/or medical oncology. This article presents an approach to assess extraspinal metastases, reviews available interventional techniques in use today, and offers example cases as an introductory primer to the thought process used for selecting the appropriate interventional treatment.

Expert Consensus and Equipoise: Planning a Randomized Controlled Trial of Magnetically Controlled Growing Rods

STUDY DESIGN

Expert consensus building using combined Delphi method and Nominal group technique.

OBJECTIVES

To identify the current state of equipoise surrounding the use of magnetically controlled growing rods (MCGRs) and to determine consensus for planning a randomized controlled trial (RCT) with MCGRs.

BACKGROUND

The use of MCGRs for the treatment of early-onset scoliosis (EOS) is a new technology. Optimal use has not been thoroughly investigated and much uncertainty exists. Areas of uncertainty include construct architecture, timing of lengthenings, and amount of distraction per lengthening. Expert discussion and consensus is useful at this early juncture and necessary when designing an RCT.

METHODS

Two rounds of surveys were administered to a group of experienced pediatric spine surgeons, followed by a 2-hour, face-to-face meeting in November 2015 and a 1-hour, face-to-face meeting in February 2016. The first survey used example cases to establish agreement around the proper use of MCGRs and identified areas of equipoise and disagreement. The second survey again used example cases-this time selected for their equipoise status-to solicit trial arms for a potential RCT of MCGRs and identified important open questions in the use of MCGRs. Lastly, the face-to-face meetings employed iterative voting to preliminarily plan an RCT of MCGRs.

RESULTS

Following the Delphi survey rounds and the two Nominal face-to-face meetings, the group of experts decided on an MCGR RCT design that standardized all patients to bidirectional constructs, and randomized to a lengthening interval of 6 versus 16 weeks with a standardized equation for calculating the total yearly lengthening that approximates normal spine growth.

CONCLUSION

This endeavor indicates expert support for the use of MCGR in children older than 6 years, with curves greater than 60°. The uncertainty surrounding frequency of lengthening justifies an RCT of MCGRs.

LEVEL OF EVIDENCE

Level V.