Impact of the Ablative Margin on Local Tumor Progression after Radiofrequency Ablation for Lung Metastases from Colorectal Carcinoma: Supplementary Analysis of a Phase II Trial (MLCSG-0802)

Advancements in the application of ablative therapy and its combination with immunotherapy in anti-cancer therapy

Cancer is a significant health issue impacting humans. Currently, systemic therapies such as chemotherapy have significantly increased the life expectancy of cancer patients. However, some patients are unable to endure systemic treatment due to its significant adverse effects, leading to an increased focus on local therapies including radiation and ablation therapy. Ablation therapy is a precise, low-toxicity, and minimally invasive localized therapy that is increasingly acknowledged by clinicians and cancer patients. Many cancer patients have benefited from it, with some achieving full recovery. Currently, numerous studies have shown that ablation therapy is effective due to its ability to kill cancer cells efficiently and activate the body's anti-cancer immunity. It can also convert "cold cancers" into "hot cancers" and enhance the effectiveness of immunotherapy when used in combination. In this article, we categorize ablation therapy into thermal ablation, cryoablation, photodynamic therapy (PDT), irreversible electroporation (IRE), etc. Thermal ablation is further divided into Radiofrequency ablation (RFA), microwave ablation (WMA), high-frequency focused ultrasound (HIFU), photothermal therapy (PTT), magnetic heat therapy (MHT), etc. We systematically review the most recent advancements in these ablation therapies that are either currently used in clinic or are anticipated to be used in clinic. Then, we also review the latest development of various ablative therapies combined with immunotherapy, and its future development. CLINICAL RELEVANCE STATEMENT: Ablation therapy, an invasive localized treatment, offers an alternative to systemic therapies for cancer patients who cannot tolerate their adverse effects. Its ability to kill cancer cells efficiently and activate anti-cancer immunity. This article reviews recent advancements in ablation therapies, including thermal, cryoablation, PDT, and IRE, and their potential clinical applications, both standalone and in combination with immunotherapy.

Predicting Survival and Recurrence of Lung Ablation Patients Using Deep Learning-Based Automatic Segmentation and Radiomics Analysis

PURPOSE

To predict survival and tumor recurrence following image-guided thermal ablation (IGTA) of lung tumors segmented using a deep learning approach.

METHODS AND MATERIALS

A total of 113 patients who underwent IGTA for primary and metastatic lung tumors at a single institution between January 1, 2004 and July 14, 2022 were retrospectively identified. A pretrained U-Net model was applied to the dataset of pre- and post-procedure CT scans to segment lung zones. Following lung segmentation, a U-shaped encoder-decoder transformer architecture (UNETR) was trained to segment lung tumors from pre- and post-procedure CT scans, and radiomic features were automatically extracted. These features were input into a support vector machine (SVM)-based survival prediction model trained to assign rank scores to samples based on binary survival or recurrence label and follow-up time. C-index and time-dependent AUC were subsequently calculated to evaluate model performance.

RESULTS

Initial tumor segmentation using UNETR achieved a Dice score of 0.75. Applying a radiomics-based survivability prediction model to the post-procedure scans resulted in a c-index of 0.71 and a time-dependent AUC of 0.75. In contrast, when this model was applied to pre-procedure scans, it achieved a 0.56 for both metrics. For predicting time to recurrence, the radiomics-based model achieved a c-index of 0.65 and a time-dependent AUC of 0.72 on post-procedure imaging. In contrast, when this model was applied to pre-procedure scans, it achieved a 0.54 for both metrics.

CONCLUSION

Radiomic feature analysis of lung tumors following automatic segmentation by a state-of-the-art transformer-based U-NET may predict survival and recurrence following image-guided thermal ablation of pulmonary malignancies.

LEVEL OF EVIDENCE

Level 3, Retrospective cohort study.

Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation

PURPOSE

To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical decision making.

MATERIALS AND METHODS

The data of 360 patients with Stage Ia lung adenocarcinoma who underwent MWA were included in the training (n = 208), internal test (n = 90), and external test (n = 62) sets based on the inclusion and exclusion criteria. The predictors associated with local recurrence were identified using univariate and multivariate analyses of clinical information. The integrated radiomics features were extracted from pre-MWA and post-MWA (scanned immediately after the ablation) computed tomography (CT) images, and 10 radiomics features were selected by the t-test and least absolute shrinkage and selection operator. The L2-logistic regression of machine learning was applied for the clinical model, CT radiomics model, and combined model including clinical predictors and radiomics features. Model performance was evaluated by the receiver operating characteristic and decision curve analysis.

RESULTS

The ablative margin was an independent clinical predictor (P = 0.001; odds ratio [OR], 0.46; 95% CI, 0.29-0.73). The combined model showed the highest area under the curve value among the 3 models (training, 0.86; 95% CI, 0.81-0.91; internal test, 0.93; 95% CI, 0.87-0.98; external test, 0.89; 95% CI, 0.79-0.96).

CONCLUSIONS

The combined model could accurately predict the local recurrence of Stage Ia lung adenocarcinoma after MWA to better support a clinical decision.

2024 multidisciplinary consensus on image-guided lung tumor ablation from the Taiwan Academy of Tumor Ablation

In this article, the multidisciplinary team of the Taiwan Academy of Tumor Ablation, who have expertise in treating lung cancer, present their perspectives on percutaneous image-guided thermal ablation (IGTA) of lung tumors. The modified Delphi technique was applied to reach a consensus on clinical practice guidelines concerning ablation procedures, including a comprehensive literature review, selection of panelists, creation of a rating form and survey, and arrangement of an in-person meeting where panelists agreed or disagreed on various points. The conclusion was a final rating and written summary of the agreement. The multidisciplinary expert team agreed on 10 recommendations for the use of IGTA in the lungs. These recommendations include terms and definitions, line of treatment planning, modality, facility rooms, patient anesthesia settings, indications, margin determination, post-ablation image surveillance, qualified centers, and complication ranges. In summary, IGTA is a safe and feasible approach for treating primary and metastatic lung tumors, with a relatively low complication rate. However, decisions regarding the ablation technique should consider each patient's specific tumor characteristics.

Prospective Margin Estimates Predict Local Tumor Progression Following Microwave Ablation of Small Renal Masses

PURPOSE

To evaluate the relationship between prospectively generated ablative margin estimates and local tumor progression (LTP) among patients undergoing microwave ablation (MWA) of small renal masses (SRMs).

MATERIALS AND METHODS

Between 2017 and 2020, patients who underwent MWA for SRM were retrospectively identified. During each procedure, segmented kidney and tumor shapes were coregistered with intraprocedural helical CT images obtained after microwave antenna placement. Predicted ablation zone shape and size were then overlaid onto the resultant model, and a model-to-model distance algorithm was employed to calculate multiple ablative margin estimates. LTP was modeled as a function of each margin estimate by hazard regression. Models were evaluated using hazard ratios and Akaike information criterion. Receiver operating characteristic curve area under the curve was also estimated using Harrell's and Uno's C indices (HI and UI, respectively).

RESULTS

One hundred and twenty-eight patients were evaluated (median age 72.1 years). Mean tumor diameter was 2.4 ± 0.9 cm. LTP was observed in nine (7%) patients. Analysis showed that decreased estimated margin size as measured by first quartile (Q1; 25th percentile), maximum, and average ablative margin metrics was significantly associated with risk of LTP. For every one millimeter increase in Q1, maximum, and mean ablative margin, the hazard of LTP increased 67% (HR: 1.67; 95% CI = 1.25-2.20, UI = 0.93, HI = 0.77), 32% (HR: 1.32; 95% CI 1.09-1.60; UI = 0.93; HI = 0.76), and 48% (HR: 1.48; 95% CI 1.18-1.85; UI = 0.83; HI = 0.75), respectively.

CONCLUSION

Prospectively generated ablative margin estimates can be used to predict the risk of local tumor progression following microwave ablation of small renal masses. LEVEL OF EVIDENCE 3: Retrospective cohort study.

Optimizing Treatment Strategy for Oligometastases/Oligo-Recurrence of Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer, and nearly half of CRC patients experience metastases. Oligometastatic CRC represents a distinct clinical state characterized by limited metastatic involvement, demonstrating a less aggressive nature and potentially improved survival with multidisciplinary treatment. However, the varied clinical scenarios giving rise to oligometastases necessitate a precise definition, considering primary tumor status and oncological factors, to optimize treatment strategies. This review delineates the concepts of oligometastatic CRC, encompassing oligo-recurrence, where the primary tumor is under control, resulting in a more favorable prognosis. A comprehensive examination of multidisciplinary treatment with local treatments and systemic therapy is provided. The overarching objective in managing oligometastatic CRC is the complete eradication of metastases, offering prospects of a cure. Essential to this management approach are local treatments, with surgical resection serving as the standard of care. Percutaneous ablation and stereotactic body radiotherapy present less invasive alternatives for lesions unsuitable for surgery, demonstrating efficacy in select cases. Perioperative systemic therapy, aiming to control micrometastatic disease and enhance local treatment effectiveness, has shown improvements in progression-free survival through clinical trials. However, the extension of overall survival remains variable. The review emphasizes the need for further prospective trials to establish a cohesive definition and an optimized treatment strategy for oligometastatic CRC.

Does joint-sparing tumor resection jeopardize oncologic and functional outcomes in non-metastatic high-grade osteosarcoma around the knee?

BACKGROUND

We previously reported joint-sparing tumor resection for osteosarcoma with epiphyseal involvement in which transepiphyseal osteotomy went through the in situ ablated epiphysis. However, we do not know whether this is a safe approach when compared with joint-sacrificed tumor resection. Our objective was to compare oncologic and functional outcomes between patients who underwent joint preservation (JP) and joint replacement (JR) tumor resection. Furthermore, we identified the risk factors of local recurrence, metastasis and survival.

METHODS

Eighty-nine patients with non-metastatic high-grade osteosarcoma around the knee were treated with limb-salvage surgery (JP in 47 and JR in 42). Age, gender, tumor location, pathologic fracture, plain radiographic pattern, limb diameter change, perivascular space alteration, surgical margin, local recurrence, metastasis, death, and the Musculoskeletal Tumor Society (MSTS)-93 scores were extracted from the records. Univariate analysis was performed to compare oncologic and functional outcomes. Binary logistic and cox regression models were used to identify predicted factors for local recurrence, metastasis, and survival.

RESULTS

Local recurrence, metastasis and overall survival were similar in the JP and JR group (p = 0.3; p = 0.211; p = 0.143). Major complications and limb survival were also similar in the JR and JP group (p = 0.14; p = 0.181). The MSTS score of 27.06 ± 1.77 in the JP group was higher than that of 25.88 ± 1.79 in the JR group (p = 0.005). The marginal margin of soft tissue compared with a wide margin was the only independent predictor of local recurrence (p = 0.006). Limb diameter increase and perivascular fat plane disappearance during neoadjuvant chemotherapy were independent predictors for metastasis (p = 0.002; p = 0.000) and worse survival (p = 0.000; p = 0.001).

CONCLUSIONS

Joint-sparing tumor resection with the ablative bone margin offers advantage of native joint preservation with favorable functional outcomes while not jeopardizing oncologic outcomes compared with joint-sacrificed tumor resection. Surgeon should strive to obtain adequate soft tissue surgical margin decreasing risk of local recurrence. Novel drug regimens might be reasonable options for patients with obvious limb diameter increase and perivascular fat disappearance during chemotherapy.