Bupathi Manojkumar, Garmezy Benjamin, Lattanzi Michael, Kieler Minnie, Ibrahim Nevein, Perk Timothy G, Weisman Amy J, Perlman Scott B
Department of Medical Oncology, Rocky Mountain Cancer Centers, Littleton, CO 80120, USA.
Department of Medical Oncology, Sarah Cannon Research Institute, Nashville, TN 37203, USA.
J Clin Med. 2024 Oct 16;13(20):6168. doi: 10.3390/jcm13206168.
: Determining how a patient with metastatic cancer is responding to therapy can be difficult for medical oncologists, especially with text-only radiology reports. In this investigation, we assess the clinical usefulness of a new algorithm-based analysis that provides spatial location and quantification for each detected lesion region of interest (ROI) and compare it to information included in radiology reports in the United States. : Treatment response radiology reports for FDG PET/CT scans were retrospectively gathered from 228 patients with metastatic cancers. Each radiology report was assessed for the presence of both qualitative and quantitative information. A subset of patients ( = 103) was further analyzed using an algorithm-based service that provides the clinician with comprehensive quantitative information, including change over time, of all detected ROI with visualization of anatomical location. For each patient, three medical oncologists from different practices independently rated the usefulness of the additional analysis overall and in four subcategories. : In the 228 radiology reports, quantitative information of size and uptake was provided for at least one lesion at one time point in 78% (size) and 95% (uptake) of patients. This information was reported for both analyzed time points (current scan and previous comparator) in 52% (size) and 66% (uptake) of patients. Only 7% of reports quantified the total number of lesions, and none of the reports quantified changes in all lesions for patients with more than a few lesions. In the assessment of the augmentative algorithm-based analysis, the majority of oncologists rated it as overall useful for 98% of patients (101/103). Within specific categories of use, the majority of oncologists voted to use it for making decisions regarding systemic therapy in 97% of patients, for targeted therapy decisions in 72% of patients, for spatial location information in 96% of patients, and for patient education purposes in 93% of patients. : For patients with metastatic cancer, the algorithm-based analysis of all ROI would allow oncologists to better understand treatment response and support their work to more precisely optimize the patient's therapy.
对于肿瘤内科医生而言，判断转移性癌症患者对治疗的反应可能具有挑战性，尤其是在仅有文字的放射学报告的情况下。在本研究中，我们评估了一种基于新算法的分析方法的临床实用性，该方法可为每个检测到的感兴趣病变区域（ROI）提供空间位置和定量分析，并将其与美国放射学报告中包含的信息进行比较。：回顾性收集了228例转移性癌症患者的FDG PET/CT扫描的治疗反应放射学报告。对每份放射学报告的定性和定量信息进行评估。使用基于算法的服务对一部分患者（n = 103）进行进一步分析，该服务为临床医生提供所有检测到的ROI的综合定量信息，包括随时间的变化以及解剖位置的可视化。对于每位患者，来自不同医疗机构的三位肿瘤内科医生独立对额外分析在总体上以及四个子类别中的有用性进行评分。：在228份放射学报告中，78%（大小）和95%（摄取）的患者在至少一个时间点为至少一个病变提供了大小和摄取的定量信息。52%（大小）和66%（摄取）的患者在两个分析时间点（当前扫描和先前对照）均报告了此信息。只有7%的报告对病变总数进行了量化，对于有多个病变的患者，没有一份报告对所有病变的变化进行量化。在对基于增强算法的分析的评估中，大多数肿瘤内科医生认为它对98%的患者（101/103）总体有用。在特定的使用类别中，大多数肿瘤内科医生投票决定将其用于97%的患者的全身治疗决策、72%的患者的靶向治疗决策、96%的患者的空间位置信息以及93%的患者的患者教育目的。：对于转移性癌症患者，基于算法的所有ROI分析将使肿瘤内科医生能够更好地了解治疗反应，并支持他们更精确地优化患者治疗的工作。
