Abstract CT317: Quantitative ultrasound for personalized chemotherapy in locally advanced breast cancer: Clinical trial results
Notice bibliographique
Résumé
Abstract Many cancer therapies are intended to induce cell death within a target tumour. A substantial body of research using in vitro and in vivo models has demonstrated that cell death can be detected via quantitative ultrasound techniques. This study investigated the potential to quantify tumour responses to therapy in patients, using quantitative spectral and textural biomarkers extracted from low-frequency ultrasound data (4-10 MHz). Results demonstrate for the first time in a large cohort of patients the ability to predict clinical responders from non-responders as early as one week after the start of chemotherapy with over 95% sensitivity and 95% specificity. A clinical study was undertaken investigating the efficacy of ultrasound to quantify cell death in tumor responses with cancer treatment. Patients (n = 100) with locally advanced breast cancer received anthracyline and taxane-based chemotherapy treatments over four to six months. Data collection consisted of acquiring tumor images and radiofrequency data prior to treatment onset and at 4 times during neoadjuvant chemotherapy (weeks 0, 1, 4, 8 and pre-operatively). Data collection was carried out using an Ultrasonix-RP and an L15-5 6cm transducer pulsed at frequencies of ∼5 and ∼7 MHz, respectively. The majority of patients went on to have a modified radical mastectomy and correlative whole mount histopathology. Results obtained from both ∼5 and ∼7 MHz data indicated considerable increases in ultrasound spectral backscatter power in patients who clinically responded to treatment within one week of starting their chemotherapy. This was accompanied by significant increases in quantitative ultrasound spectral parameters such as mid-band-fit (up to 9.1 ± 1.2 dBr) and 0-MHz intercept (up to 10.8 ± 2.4 dBr). Patients categorized as poor responders clinically demonstrated significantly lower increases (1.9 ± 1.1 dBr and 1.4 ± 2.7 dBr for mid-band-fit and 0-MHz intercept, respectively). Textural biomarkers extracted from quantitative ultrasound spectral parametric maps also demonstrated considerable differences in trend between treatment responding and non-responding patients early after the treatment initiation. Statistically significant differences were found between treatment responding and non-responding patient populations using quantitative ultrasound spectral biomarkers 4 and 8 weeks after treatment initiation. Applying quantitative ultrasound textural biomarkers in order to incorporate response heterogeneities resulted in statistically significant differences between these two populations only one week after the start of chemotherapy. There were also associated survival differences between the two groups of patients. Patients with ultrasound-detected responses at week 1 had an over 90+/-5% 3 year survival whereas patients with no ultrasound-detected response at the same time had a 30+/10% survival (p<0.05). This study demonstrates the potential of ultrasound to quantify changes in tumours in response to cancer treatment administration in a clinical setting. The results indicate that such responses can be detected early during a course of chemotherapy. This can potentially permit ineffective treatments to be changed to more efficacious ones potentially leading to improved treatment outcomes within a framework of personalized medicine. Citation Format: Gregory Jan Czarnota, Ali Sadeghi-Naini, Hadi Tadayyon, Lakshmanan Sannachi, Mehrdad Gangeh, William Tran, Frances Wright, Sonal Gandhi, Kathleen Pritchard, Sunil Verma, Maureen Trudeau. Quantitative ultrasound for personalized chemotherapy in locally advanced breast cancer: Clinical trial results. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr CT317. doi:10.1158/1538-7445.AM2015-CT317
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».