Growth rate of small lung cancers detected on mass CT screening.

Hasegawa, Masatoshi; Sone, Shusuke; Takashima, S; Li, F; Yang, Zhongyi; Maruyama, Yoshihiro; Watanabe, Tomofumi

doi:10.1259/bjr.73.876.11205667

Cited by 482 publications

(336 citation statements)

References 19 publications

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“…Therefore, all CT's for restaging and planning purposes were analysed using the same method as described. For each patient the gross tumour volumes Vr and Vp were calculated and with the time interval T between CTr and CTp, the tumour volume doubling time Td could be estimated: Td ¼ Tln2/ln(Vp/Vr) (Hasegawa et al, 2000). According to our protocol, patients with stage III-B NSCLC receive palliative radiotherapy and with stage III-A high-dose radiotherapy with curative intent.…”

Section: Methodsmentioning

confidence: 99%

“…Data on tumour volume doubling time (Td) for human lung tumours are reported by Hasegawa et al (2000), Steel (1977), Usuda et al (1994), Fujimura et al (1979), Filderman et al (1986) and Geddes (1979). The data are summarised in Table 4.…”

Section: Repopulation and Tumour Doubling Timementioning

confidence: 99%

“…To our knowledge such a short mean Td value for lung tumours has not been reported earlier. Hasegawa et al (2000) determined growth rate of small lung cancers detected on mass CT screening. The shortest Td they found was 52 days.…”

Section: Repopulation and Tumour Doubling Timementioning

confidence: 99%

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Accelerated regrowth of non-small-cell lung tumours after induction chemotherapy

2003

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Induction chemotherapy of non-small-cell lung cancer (NSCLC) stage III with gemcitabine and cisplatin for downstaging of the tumour with the aim for further treatment with ionising radiation is one of the treatments for lung cancer patients. The purpose of this study was to investigate the influence of the waiting time for radiotherapy, that is, the interval between induction chemotherapy and radiotherapy, on the rate of tumour growth for patients with NSCLC. Interval times between the end of induction chemotherapy and date of diagnostic CT, planning CT and first day of radiotherapy were determined for 23 patients with NSCLC. Increase in gross tumour volume was measured for 18 patients by measuring the dimensions of the primary tumour and lymph node metastases on the diagnostic CT after induction chemotherapy and on the CT used for radiotherapy planning. For each patient, the volume doubling time was calculated from the time interval between the two CTs and ratio of the gross volumes on planning CT and diagnostic CT. The mean time interval between end of chemotherapy and day of diagnostic CT was 16 days, and till first day of radiotherapy 80.3 (range 29 -141) days. In all, 41% of potentially curable patients became incurable in the waiting period. The ratio of gross tumour volumes of the two CTs ranged from 1.1 to 81.8 and the tumour doubling times ranged from 8.3 to 171 days, with a mean value of 46 days and median value of 29 days. This is far less than the mean doubling time of NSCLC in untreated patients found in the literature. This study shows that in the time interval between the end of induction chemotherapy and the start of radiotherapy rapid tumour progression occurs as a result of accelerated tumour cell proliferation: mean tumour doubling times are much shorter than those in not treated tumours. As a consequence, the gain obtained with induction chemotherapy with regard to volume reduction was lost in the waiting time for radiotherapy. We recommend diminishing the time interval between chemo-and radiotherapy to as short as possible.

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Section: Methodsmentioning

confidence: 99%

Section: Repopulation and Tumour Doubling Timementioning

confidence: 99%

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Accelerated regrowth of non-small-cell lung tumours after induction chemotherapy

2003

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“…The purpose of lung cancer screening is to detect malignancy when it is preclinical, prior to the development of overt symptoms, providing the opportunity for treatment intervention that will prevent or delay death. There is clear evidence that lung cancer is not the product of one single molecular construct: there is considerable variation in lung cancer growth rates, as has been amply demonstrated by several observed phenomena: by calculations of tumor doubling time using CT (30,31), by the propensity of a subset of pathologic stage IA lung cancers to recur following presumed curative surgery (32,33), and by the indolent growth characteristics of certain subtypes of adenocarcinoma (34,35). Effectively, some lung cancers are biologically indolent and grow slowly; some lung cancers are biologically aggressive and grow and metastasize rapidly.…”

Section: Survival Versus Mortality Endpoints In Screeningmentioning

confidence: 99%

Lung Cancer Screening with CT

Aberle

Brown

2008

Clinics in Chest Medicine

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Lung cancer is the leading cause of cancer death in the United States. In 2007, it is estimated that 160,390 lung cancer deaths will occur in the US, representing 29% of all cancer deaths (1). Roughly 87% of lung cancers are attributed to cigarette smoking (2). Although cancer risk is attenuated by smoking cessation, the risk is not eliminated, and lung cancer now occurs with equal frequency in current and former smokers (3). Moreover, other factors clearly influence risk, including age; family history; chronic obstructive pulmonary disease; pulmonary fibrosis; and exposures to environmental radon, asbestos, and certain other occupational agents (4). Realistically, lung cancer will likely remain at epidemic proportions for decades to come.Non-small cell lung cancer (NSCLC), which accounts for 75-80% of all lung cancers, is typically diagnosed when disease is locally advanced or there are systemic metastases (5), explaining the dismal overall five-year survival of 15% (6). In contrast, the five-year survival of individuals with surgically resected, early stage NSCLC approaches 75% (6,7). These differences have fueled the impetus to find a screening test that can detect NSCLC in its early preclinical stages, when surgical resection is most likely to prolong life and potentially reduce lung cancer mortality. Although earlier randomized controlled trials of lung cancer screening using chest radiography and sputum cytology failed to show reduced lung cancer mortality, computed tomography (CT) is a much more sensitive test for detecting small lung nodules, and has generated considerable enthusiasm as a potential contemporary screening tool for lung cancer.

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“…To provide a standard method for lesion size measurement, the World Health Organization (WHO) proposed in 1979 the use of the product of the maximal diameter and its largest perpendicular [1], while the Response Evaluation Criteria in Solid Tumors (RECIST) working group in 1998-2000 proposed the use of the (uni-dimensional) maximal diameter as a more efficient standard estimator of lesion volume [2]. Another measure that has been seen in some present studies, [3,4], is the bi-dimensional Modified Schwartz equation (MS), first introduced by Usuda et al in 1994 [5]. This measure is similar to the WHO measure in using the maximal diameter and its largest perpendicular, but differs from WHO because the lesion is assumed to be an ellipsoid with a long axis equal to the lesion maximal diameter and with equal-length short axes equal to the largest perpendicular.…”

Section: Introductionmentioning

confidence: 99%

The Lung Image Database Consortium (LIDC)

Reeves¹,

Biancardi²,

Apanasovich³

et al. 2007

Academic Radiology

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Rationale and Objectives-To investigate the effects of choosing between different metrics in estimating the size of pulmonary nodules as a factor both of nodule characterization and of performance of computer aided detection systems, since the latters are always qualified with respect to a given size range of nodules.Materials and Methods-This study used 265 whole-lung CT scans documented by the Lung Image Database Consortium using their protocol for nodule evaluation. Each inspected lesion was reviewed independently by four experienced radiologists who provided boundary markings for nodules larger than 3 mm. Four size metrics, based on the boundary markings, were considered: a uni-dimensional and two bi-dimensional measures on a single image slice and a volumetric measurement based on all the image slices. The radiologist boundaries were processed and those with four markings were analyzed to characterize the inter-radiologist variation, while those with at least one marking were used to examine the difference between the metrics.Results-The processing of the annotations found 127 nodules marked by all of the four radiologists and an extended set of 518 nodules each having at least one observation with three-dimensional sizes ranging from 2.03 to 29.4 mm (average 7.05 mm, median 5.71 mm). A very high inter-observer variation was observed for all these metrics: 95% of estimated standard deviations were in the following ranges [0. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public AccessAuthor Manuscript Acad Radiol. Author manuscript; available in PMC 2008 December 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript the uni-dimensional, and the two bi-dimensional size metrics respectively (in mm). Also a very large difference among the metrics was observed: 0.95 probability-coverage region widths for the volume estimation conditional on uni-dimensional, and the two bi-dimensional size measurements of 10mm were 7.32, 7.72, and 6.29 mm respectively.Conclusions-The selection of data subsets for performance evaluation is highly impacted by the size metric choice. The LIDC plans to include a single size measure for each nodule in its database. This metric is not intended as a gold standard for nodule size; rather, it is intended to facilitate the selection of unique repeatable size limited nodule subsets.

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Growth rate of small lung cancers detected on mass CT screening.

Cited by 482 publications

References 19 publications

Accelerated regrowth of non-small-cell lung tumours after induction chemotherapy

Accelerated regrowth of non-small-cell lung tumours after induction chemotherapy

Lung Cancer Screening with CT

The Lung Image Database Consortium (LIDC)

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