Dosimetric comparison of graphical optimization and inverse planning simulated annealing for brachytherapy of cervical cancer

Modern Tools for Modern Brachytherapy

This review aims to showcase the brachytherapy tools and technologies that have emerged during the last 10 years. Soft-tissue contrast using magnetic resonance and ultrasound imaging has seen enormous growth in use to plan all forms of brachytherapy. The era of image-guided brachytherapy has encouraged the development of advanced applicators and given rise to the growth of individualised 3D printing to achieve reproducible and predictable implants. These advances increase the quality of implants to better direct radiation to target volumes while sparing normal tissue. Applicator reconstruction has moved beyond manual digitising, to drag and drop of three-dimensional applicator models with embedded pre-defined source pathways, ready for auto-recognition and automation. The simplified TG-43 dose calculation formalism directly linked to reference air kerma rate of high-energy sources in the medium water remains clinically robust. Model-based dose calculation algorithms accounting for tissue heterogeneity and applicator material will advance the field of brachytherapy dosimetry to become more clinically accurate. Improved dose-optimising toolkits contribute to the real-time and adaptive planning portfolio that harmonises and expedites the entire image-guided brachytherapy process. Traditional planning strategies remain relevant to validate emerging technologies and should continue to be incorporated in practice, particularly for cervical cancer. Overall, technological developments need commissioning and validation to make the best use of the advanced features by understanding their strengths and limitations. Brachytherapy has become high-tech and modern by respecting tradition and remaining accessible to all.

Plan quality score to evaluate the dwell time deviation restricted inverse planning by simulated annealing and graphically optimized treatment plans for template based interstitial brachytherapy

PURPOSE

To evaluate the impact of dwell time deviation constraint (DTDC) on the quality of IPSA-optimized treatment plans in comparison with graphical plans using plan quality scores (PQS).

MATERIAL AND METHODS

Seventy optimized plans (graphical & IPSA with different DTDC values) of ten cervical cancer patients were generated. Various DVH parameters like D₉₀, V₁₀₀, V₁₅₀, V₂₀₀, V₃₀₀ were compared to evaluate the impact of DTDC on target coverage and high dose regions inside target for different plans. Similarly, for the OAR dose, values of D_2cc were compared. Various planning parameters like CI, COIN, DHI, DNR, ODI, EI and gain factor (GF) for different OARs were calculated. Based on these indices a plan quality score (PQS) was formulated and calculated. PQS values were used to see the impact of DTDC on plan quality of IPSA in comparison with dosimetric quality of graphical plan.

RESULTS

We have found that target coverage is similar for IPSA and graphically optimized treatment plans. However, dose homogeneity was improved in IPSA compared to graphical optimization whereas conformality was better in graphically optimized plans. OAR dose was less in IPSA plans. High-dose regions inside the target were also reduced in IPSA comparatively. However, IPSA plans optimized with various values of DTDC did not necessarily reduce high-dose regions beyond 0.6. Plan quality scores (PQS) were 6.31, 6.31, 6.34, and 6.17 for the graphically optimized plan, IPSA with DTDC values of 0.0, 0.4, and 1.0 respectively.

CONCLUSION

We found that IPSA is dosimetrically advantageous over graphical optimization. IPSA with a DTDC value of 0.4 improved overall plan quality. However, DTDC value beyond 0.6 produces dosimetrically sub-optimal plans hence the use of DTDC should be very selective and limited.

Optimizing the IPSA Conditions to Improve the Treatment Plan Quality in Brachytherapy for Cervical Cancer

Recent prevalent use of three-dimensional image-guided brachytherapy (3D brachytherapy) has dramatically improved the treatment outcomes of cervical cancer. Inverse planning simulated annealing (IPSA) is one of the commonly used algorithms in 3D brachytherapy, but different conditions may affect the treatment plan quality. In this study, we compared HRCTV (high-risk clinical target volume) D90 (dose prescription) and HRCTV D95 D2cc (dose received by 2.0cc) of the rectum, bladder, and sigmoid in 30 patients with cervical cancer under four IPSA conditions. The HRCTV D90 (mean ± SD cGy) was 607.32 ± 37.86, 599.01 ± 23.62, 598.67 ± 13.07, and 596.45 ± 10.94 in four groups, respectively. The HRCTV D95 was 558.19 ± 38.51, 558.17 ± 25.72, 557.03 ± 16.12, and 555.26 ± 12.78, respectively. The sigmoid D2cc was 282.96 ± 44.84, 273.14 ± 60.69, 268.94 ± 62.32, and 292.69 ± 52.44. HRCTV D90, HRCTV D95, and sigmoid D2cc were not statistically different among the four groups (p > 0.05). However, the target fitness in group one, especially at the cervix, was poor. The rectum D2cc was 351.49 ± 32.90, 361.49 ± 28.09, 370.82 ± 24.44, and 375.33 ± 30.90. The rectum D2cc in group one was the lower than that in group three and group four ( $p<0.05$ ). The bladder D2cc was 423.59 ± 31.39, 380.75 ± 37.25, 383.27 ± 32.55, and 385.22 ± 25.79. The bladder D2cc in group one was higher than the other groups ( $p<0.05$ ). The maximum rectum limit dose (400cGy) is lower than the bladder (500cGy), and HRCTV is a whole in the IPSA algorithm; these result in the insufficiency or even absence of cervix dose that first need to meet in clinics. In conclusion, IPSA condition optimization can improve the quality of treatment plan in 3D brachytherapy and make it closer to clinical practice.

High-dose-rate brachytherapy using inverse planning optimization with tandem and ovoid applicators for locally advanced cervical cancer: a simulation study

The purpose of this study was to evaluate the dosimetric advantage of inverse planning optimization (IPO) in locally advanced cervical cancer using high-dose-rate (HDR) brachytherapy (BT). IPO was compared with point A plan and geometric optimization (GO). The three planning methods were evaluated using doses to the virtual organ-at-risk (OAR) and D90 (the minimum dose covering of 90% of the volume) to the virtual high-risk clinical target volume (HR-CTV) based on quantitative analysis. HR-CTV structures measuring 38.5 cm³ and 59.5 cm³ were created based on the outcomes of a European Group cohort study. The HR-CTVs were located either at the center of the cervix (cervical center model) or shifted toward the left (extensive disease model). The distances from the HR-CTVs to the rectum were set at 0 mm, 3 mm, 5 mm, 8 mm, 10 mm, and 15 mm. We analyzed 336 conditions in this study. All doses were evaluated by conversion to doses in 2-Gy fractions of conventional radiotherapy. The D90 of the HR-CTV using GO and IPO could achieve the desired dose in all conditions, providing better results than that of point A plan. IPO makes it possible to deliver a sufficient dose for the D90 of the HR-CTV while reducing OAR doses with smaller HR-CTV values (< 38.5 cm³) in HDR BT. However, taking into consideration the whole treatment planning time, IPO should be used only when the HR-CTV-to-rectum distance is ≤ 5 mm, and the use of GO cannot spare OARs.

Does inverse planning improve plan quality in interstitial high-dose-rate breast brachytherapy?

Purpose

To investigate the effect of input parameters for an inverse optimization algorithm, and dosimetrically evaluate and compare clinical treatment plans made by inverse and forward planning in high-dose-rate interstitial breast implants.

Material and methods

By using a representative breast implant, input parameters responsible for target coverage and dose homogeneity were changed step-by-step, and their optimal values were determined. Then, effects of parameters on dosimetry of normal tissue and organs at risk were investigated. The role of dwell time modulation restriction was also studied. With optimal input parameters, treatment plans of forty-two patients were re-calculated using an inverse optimization algorithm (HIPO). Then, a pair-wise comparison between forward and inverse plans was performed using dose-volume parameters.

Results

To find a compromise between target coverage and dose homogeneity, we recommend using weight factors in the range of 70-90 for minimum dose, and in the range of 10-30 for maximum dose. Maximum dose value of 120% with a weight factor of 5 is recommended for normal tissue. Dose constraints for organs at risk did not play an important role, and the dwell time gradient restriction had only minor effect on target dosimetry. In clinical treatment plans, at identical target coverage, the inverse planning significantly increased the dose conformality (COIN, 0.75 vs. 0.69, p < 0.0001) and improved the homogeneity (DNR, 0.35 vs. 0.39, p = 0.0027), as compared to forward planning. All dosimetric parameters for non-target breast, ipsilateral lung, ribs, and heart were significantly better with inverse planning. The most exposed small volumes for skin were less in HIPO plans, but without statistical significance. Volume irradiated by 5% was 173.5 cm³ in forward and 167.7 cm³ in inverse plans (p = 0.0247).

Conclusions

By using appropriate input parameters, inverse planning can provide dosimetrically superior dose distributions over forward planning in interstitial breast implants.