Computed tomography (CT)-guided thermal ablation is an emerging treatment method for lung tumors. Ablation needle path planning in preoperative diagnosis is of critical importance. In this work, we proposed an automatic needle path-planning method for thermal lung tumor ablation. First, based on the improved cube mapping algorithm, binary classification was performed on the surface of the bounding box of the patient’s CT image to obtain a feasible puncture area that satisfied all hard constraints. Then, for different clinical soft constraint conditions, corresponding grayscale constraint maps were generated, respectively, and the multi-objective optimization problem was solved by combining Pareto optimization and weighted product algorithms. Finally, several optimal puncture paths were planned within the feasible puncture area obtained for the clinicians to choose. The proposed method was evaluated with 18 tumors of varying sizes (482.79 mm³ to 9313.81 mm³) and the automatically planned paths were compared and evaluated with manually planned puncture paths by two clinicians. The results showed that over 82% of the paths (74 of 90) were considered reasonable, with clinician A finding the automated planning path superior in 7 of 18 cases, and clinician B in 9 cases. Additionally, the time efficiency of the algorithm (35 s) was much higher than that of manual planning. The proposed method is expected to aid clinicians in preoperative path planning for thermal ablation of lung tumors. By providing a valuable reference for the puncture path during preoperative diagnosis, it may reduce the clinicians’ workload and enhance the objectivity and rationality of the planning process, which in turn improves the effectiveness of treatment.

This paper evaluates the advantages of overlapping microwave ablation (OMWA) for the personalized treatment of large tumors, providing quantitative and technical references for conformal tumor eradication. A three-dimensional numerical model coupled with electromagnetic fields and Pennes’ biological heat transfer equation was constructed, comprehensively considering the nonlinear behavior of tissue electrical and thermal parameters with temperature changes. A simulation model was developed to predict temperature distribution and the formation of the coagulation zone under single-needle multiple-point and multiple-needle multiple-point OMWA strategies. The LiTS2017 public dataset of liver tumor cases and real clinical cases was selected for verification. The results showed that OMWA could achieve faster thermal accumulation, higher central temperature, and more conformal tumor coverage. Compared with the single-needle strategy, OMWA significantly reduces thermal damage to surrounding healthy tissues while achieving complete tumor coverage. Therefore, OMWA is more efficient and safer than the single-needle strategy in the personalized treatment of large tumors and can provide important references for clinical preoperative planning and parameter optimization.

Purpose: Although alpha-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP) have a certain predictive ability for the prognosis of hepatocellular carcinoma (HCC), there are still some cases of aggressive recurrence among patients with AFP and DCP double-negative HCC (DNHC) after local ablation. However, prediction models to forecast the prognosis of DNHC patients are still lacking. Thus, this retrospective study aims to explore the prognostic factors in DNHC patients and develop a nomogram to predict recurrence. Patients and methods: 493 DNHC patients who underwent the local ablation at Beijing You’an Hospital between January 1, 2014, and December 31, 2022, were enrolled. A part that was admitted from January 1, 2014, to December 31, 2018, was designated to the training cohort (n = 307); others from January 1, 2019, to December 31, 2022, were allocated to the validation cohort (n = 186). Lasso regression and Cox regression were employed with the aim of screening risk factors and developing the nomogram. The nomogram outcome was assessed by discrimination, calibration, and decision curve analysis (DCA). Results: Independent prognostic factors selected by Lasso-Cox analysis included age, tumor size, tumor number, and gamma-glutamyl transferase. The area under the receiver operating characteristic (ROC) curves (AUCs) of the training and validation groups (0.738, 0.742, 0.836, and 0.758, 0.821) exhibited the excellent predicted outcome of the nomogram. Calibration plots and DCA plots suggest desirable calibration performance and clinical utility. Patients were stratified into three risk groups by means of the nomogram: low-risk, intermediate-risk, and high-risk, respectively. There exists an obvious distinction in recurrence-free survival (RFS) among three groups (p< 0.0001). Conclusion: In conclusion, we established and validated a nomogram for DNHC patients who received local ablation. The nomogram showed excellent predictive power for the recurrence of HCC and could contribute to guiding clinical decisions.